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VOL. 2, NO. 1 MARCH 2014 ISSN 2325-5987

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IEEE Electrification Magazine (ISSN 2325-5987) (IEMECM) is published quarterly by the Institute of Electrical and Electronics Engineers, Inc. Headquarters: 3 Park Avenue, 17th Floor, New York, NY 10016-5997 USA. Responsibility for the contents rests upon the authors and not upon the IEEE, the Society, or its members. IEEE Operations Center (for orders, subscriptions, address changes): 445 Hoes Lane, Piscataway, NJ 08854 USA. Telephone: +1 732 981 0060, +1 800 678 4333. Individual copies: IEEE members US$20.00 (first copy only), nonmembers US$123.00 per copy. Subscription Rates: Society members included with membership dues. Subscription rates available upon request. Copyright and reprint permissions: Abstracting is permitted with credit to the source. Libraries are permitted to photocopy beyond the limits of U.S. Copyright law for the private use of patrons 1) those post-1977 articles that carry a code at the bottom of the first page, provided the per-copy fee indicated in the code is paid through the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923 USA; 2) pre-1978 articles without fee. For other copying, reprint, or republication permission, write Copyrights and Permissions Department, IEEE Operations Center, 445 Hoes Lane, Piscataway, NJ 08854 USA. Copyright © 2014 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved. Periodicals postage pending at New York, NY, and at additional mailing offices. Postmaster: Send address changes to IEEE Electrificaton Magazine, IEEE Operations Center, 445 Hoes Lane, Piscataway, NJ 08854 USA. Canadian GST #125634188 PRINTED IN U.S.A.

MISSION STATEMENT: IEEE Electrification Magazine is dedicated to disseminating infor-mation on all matters related to microgrids onboard electric vehicles, ships, trains, planes, and off-grid applications. Microgrids refer to an electric network in a car, a ship, a plane or an electric train, which has a limited number of sources and multiple loads. Off-grid applica-tions include small scale electricity supply in areas away from high voltage power networks. Feature articles focus on advanced concepts, technologies, and practices associated with all aspects of electrification in the transportation and off-grid sectors from a technical perspec-tive in synergy with nontechnical areas such as business, environmental, and social concerns.

Why Microgrids Are Moving into the Mainstream Improving the efficiency of the larger power grid.

12 Advanced LVDC Electrical Power Architectures and MicrogridsA step toward a new generation of power distribution networks.

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Adaptive Protection System for Microgrids Protection practices of a functional microgrid system.

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2 ABOUT THIS ISSUE6 TECHNOLOGY LEADERS

94 DATES AHEAD95 NEWSFEED

104 VIEWPOINT

Emerging Models for Microgrid FinanceDriven by the need to deliver value to end users.

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Community Power and Fleet MicrogridsMeeting climate goals, enhancing system resilience, and stimulating local economic development.

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Microgrids: A Value-Based ParadigmThe need for the redefinition of microgrids.

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The value of a microgrid. Page 104

Smart Houses in the Smart GridDeveloping an interactive network.

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IEEE Electr i f icat ion Magazine / MARCH 20142

KNOW WHAT YOU ARE THINKING…ANOTHER SERIESof articles on the benefits and challenges of microgrids in the electric industry. We in the microgrid business see

a lot of chatter and positioning in this emerging marketplace. Are microgrids real? Can microgrids be financially viable? Will microgrids upset the 70-year-old electric monopoly business model? Will microgrids harm grid reliability? Such questions must be fun to debate since so many in the industry are engaged in the banter. Let’s step back and look at a few trends in the industry that suggest change is happening.

The U.S. Department of Energy Information Administration (EIA) tracks a lot of electric industry data. One of the trends over the last eight years is that U.S. electricity consumption is flat. Some industry leaders say that it is related to the recession, but the eight-year flat period extends to before and after the recession. The EIA trend in central-station fleet capacity factor has been declining steadily for the past 15 years. As of the 2012 data, the central-station fleet capacity factor is now 42.5%. The EIA trend in demand-side man-agement is increasing steadily. The actual peak load reduction is 29 GW, which is double the 2002 reduction, with energy savings at 138 GWh, nearly triple that of 2002. The EIA trend in commercial sec-

tor generation in New England and the middle Atlantic states increased by 27% in just one year (2012 versus 2011).

Navigant Research reports that, as of the second quarter of 2013, there are 219 operational, under construction, or planned microgrid projects in the United States. Industry analyst SBI Ener-gy reports that the worldwide

microgrid market was 2.4 GW in 2010 and projects that it will be 5.7 GW by 2020. At a macroview, consumption is flat, the central-station fleet is less competitive (decreasing capacity factor),

By Mohammad Shahidehpour and Steven Pullins

Is the Microgrid Buzz Real?

Digital Object Identifier 10.1109/MELE.2014.2301272Date of publication: 18 March 2014

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EDITORIAL BOARDSaifur RahmanEditor-in-ChiefVirginia TechVirginia, [email protected]

Iqbal HusainEditor, Electric VehiclesNorth Carolina State UniversityNorth Carolina, [email protected]

Eduard MuljadiCoeditor, Electric VehiclesNREL: Wind ResearchColorado, [email protected]

Herb GinnEditor, Electric ShipsUniversitiy of South CarolinaSouth Carolina, [email protected]

Robert CuznerCoeditor, Electric ShipsDRS Power and Control TechnologiesWisconsin, [email protected]

Eduardo Pilo de la FuenteEditor, Electric TrainsEPRail Researchand [email protected]

Jose Conrado Martine Coeditor, Electric TrainsDirectcion de Estrategia y Desarrollo [email protected]

Bulent SarliogluEditor, Electric PlanesUniversity of Wisconsin-MadisonMadison, [email protected]

Christine RossCoeditor, Electric PlanesRolls-Royce CorpIndiana, [email protected]

MohammadShahidehpourEditor, Off-GridIllinois Instituteof TechnologyChicago, [email protected]

Steve PullinsCoeditor, Off-GridHorizon Energy GroupTennessee, USAspullins@horizonenergy group.com

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The loss of electricity

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IEEE Electr i f icat ion Magazine / MARCH 2014 3

demand-side management is grow-ing, commercial sector generation is growing, and analysts are projecting double-digit annual growth rates for microgrids. This suggests two things: 1) the traditional approach to provid-ing electric services is being chal-lenged from within and 2) consumers are actively seeking alternatives for their electric services.

Having established that the indus-try is changing, do microgrids fit into this new electric service for a digital economy? Do microgrids measure up to the consumer’s objectives of reli-ability, resiliency, cost savings, and emissions reduction?

Are microgrids reliable? Lessons from the cadre of microgrids operat-ing today, as well as the lessons from highly automated distribution net-works around the world, suggest that microgrid reliability is on the order of 99.999–99.9999% uptime (commonly referred to as “5-nines” and “6-nines” reliability). This is compared to the U.S. grid at 3-nines and the European grid at 4-nines reliability. In compari-son, data centers design for 7-nines or greater reliability. Properly de-signed microgrids improve reliability for their customers.

Are microgrids resilient? The les-sons from Superstorm Sandy in 2012 in the northeastern United States demonstrated that microgrids are resilient to major events that chal-lenge the grid. All of the known microgrids in Maryland, New Jersey, New York, and Connecticut operated through the storm and its aftermath. Some became safe havens for dis-placed citizens as the region strug-gled to recover from Sandy. Our favorite example is The Brevoort in Manhattan. The Brevoort is a 20-story private residence with 700 residents, but that number increased to 1,500 for several days. It is important to note that a grid outage is not merely an inconvenience to some. Some of the residents in The Brevoort are retired and physically challenged. The loss of electricity to the elevator

in a tall building can isolate some residents from food and medical assistance. In interviews with The Brevoort residents, the continued building services were often men-tioned as necessities to sustain life.

Are microgrids economical? Some microgrids operating today are eco-nomical, and some are focused on reliability improvements without eco-nomic considerations. However, as the industry matures, technology costs will decrease, new business models will emerge, and designs will be refined. This will create more economical mi-crogrids in the near future. Our experi-ence in designing 22 microgrids to date is that microgrids be-tween 2 and 40 MWare more economical than being a 100% customer of the grid, and this is without monetizing the reli-ability and resiliency benefits. Many of the microgrids in the northeast that continued to oper-ate through Sandy and its aftermath were built for cost-saving reasons. The microgrids received resiliency as an additional benefit. Microgrids are not universally economical compared to the grid as an electric service, but there are many regions with above-average electricity rates, demand charges, and fixed infrastructure charges that create the economic en-vironment for microgrids to flourish. As microgrids mature as a technolo-gy/business solution, the cost of im-plementation and operation will decrease, making more regions eco-nomically viable with time.

Do microgrids reduce emissions? Some do when the consumer’s objec-tives include environmental goals. When microgrids include renewables, emissions are reduced. Also, when microgrids include high thermal effi-ciency combined heat and power (CHP) resources, emissions are

reduced. Thermal efficiencies for cen-tral-station generation range from 33 to 60%, while small CHP thermal effi-ciencies used in microgrids are com-monly above 80%. My experience with microgrids to date regarding emission reductions is that it is highly depen-dent upon the consumer’s objectives.

In This IssueIn this issue, you will find interesting articles about various aspects of the maturing of microgrids as an electric service tool. The seven articles and one column included in this special issue

are outlined as follows.The “Technology

Leaders” column by John McDonald states that many stakehold-ers are optimistic that the fundamental strengths of the tech-nology and its myriad applications will pre-vail over what appear to be surmountable hurdles for microgrids.

But to move beyond the hype, the tech-nology’s drivers and opportunities should be spelled out alongside an honest review of the barriers to implementation. McDonald defines microgrids in general terms and de-scribes some typical use cases. He then describes the recent efforts by the state of Minnesota to explore mi-crogrid drivers, opportunities, hurdles, and next steps. The discussion is rele-vant to not only Minnesota’s interest in microgrids but to other states, utili-ties, and microgrid sponsors.

The first article is by Asmus, who points out that microgrids are moving into the mainstream. He states that the future development of the U.S. grid will require the safe and econom-ical operation of the high-voltage meshed transmission grid since it is a US$800-billion asset that is fully amortized. Yet, the fundamental architecture of today’s electricity grid, which is based on the idea of a top-down radial transmission system

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predicated on unidirectional energy flows from large centralized power plants, is increasingly becoming obso-lete. The economies of scale that once favored such monopoly models no longer hold, as markets now favor dis-tributed and decentralized devices whose energy services are more cus-tomized and based on local availabili-ty and timing.

The second article by Ravindra et al. presents microgrids as a value-based par-adigm in developing countries. The au-thors point out that microgrids are not just a stopgap solu-tion for matching de-mand and supply in emerging economies and enabling access to modern energy in places like India. In the case of off-grid and remote areas, it is not to be assumed that microgrids will give way to central-ized grids if technologies make it possi-ble. Microgrids have to be seen as value-based entities that coexist with the centralized grid. They are potent entities that can operate essential ser-vices even in the case of emergencies such as natural calamities, as demon-strated by the Sendai microgrid, when the 9.0-magnitude earthquake struck off the northeastern coast of Japan and triggered one of the deadliest tsunamis, and San Diego Gas & Electric’s Borrego Springs microgrid during the intense thunderstorms on 6 September 2013. Microgrids are designed to be smart to incorporate innovative products and services together with intelligent moni-toring, control, communication, and self-healing technologies. Microgrids can better facilitate the connection and operation of generators of all sizes and technologies, allow consumers to play a part in optimal operation of the sys-tem, provide consumers with more in-formation and choice of supply, significantly reduce the environmental

impact of the whole electricity supply system, and deliver enhanced levels of reliability and security of supply at the local level.

The third article by Burr et al. dis-cusses the emerging models for microgrid finance. The authors point out that an understanding of both the costs and sources of economic value that microgrids can provide is critical to their financing success.

Historical projects offered emergency services and little more. They were not integrated or inter-connected with the grid and generally have served only a single facility. A more modern, integrated microgrid will pro-vide secure sources of power, with high levels of quality and reliability, through a combination of on-

site generation, storage, distribution, and energy management technolo-gies. Microgrids that make the most of each of these values and exploit the full range of revenue streams and incentive opportunities will be in a better position to attract third-party financing, especially if they consoli-date them in easily understood financial analyses. Moreover, the best financing opportunities might be obtained by combining multiple microgrid projects together into a portfolio. While an individual microgrid project might be too small to attract interest from private equi-ty and institutional investors, a microgrid portfolio could provide opportunities to raise equity or debt financing in public markets.

The fourth article by Roach is on a new distribution paradigm to meet climate goals, enhance system resil-ience, and stimulate local economic development. Roach points out that community power companies tradi-tionally originated from local

hydropower resources or were located in rural areas that for-profit utility companies did not want to serve because of the high cost of infrastruc-ture relative to demand. The article looks at potentials for a new para-digm of community power compa-nies that remain locally controlled and focused on serving community energy needs. Such operations avail themselves of the latest distributed energy resources, enabling distribu-tion technologies and market mecha-nisms to develop a local energy system that is more sustainable and secure and that generates more tangi-ble community economic benefits.

The fifth article by Dragicevic et al. discusses low-voltage microgrids. The authors discuss strategies to deal with a fundamental turnaround from ac to dc architecture at the grassroots levels of low-voltage distribution sys-tems. In that sense, a particular dc subsystem connected to a supreme ac distribution through a dedicated dc–ac converter automatically implies the lack of power quality issues initiated from the utility side. Furthermore, dc systems provide a natural interface for modern elec-tronic loads as well as most renew-able energy sources and energy storage systems like batteries. The possibility of islanded operation, which makes the system fully resis-tant to major blackouts in the main grid, is simpler in dc microgrids when synchronization problems and reactive power flows do not exist. Moreover, with the proper selection of nominal operating voltage, the dc system efficiency will generally be higher than its ac counterpart. The authors envisage that dc subsystems will constitute the core of future dis-tribution networks and that they will be gradually adopted in applications such as dc homes, hybrid electric vehicle charging stations, and com-mercial and industrial facilities.

The sixth article by Che et al. dis-cusses adaptive protection systems for microgrids. The authors point out

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that despite the numerous advantag-es of using microgrids, there are technical challenges regarding the control and protection of microgrids. One of the prominent challenges in microgrid operation is the design of a proper protection scheme for mi-crogrids. The integration of distribut-ed energy resources (DERs) and novel topologies embedded in microgrids would challenge the characteristics of protection schemes in microgrids as compared to those of conventional distribution systems. The conven-tional protection strategies in distri-bution systems rely on the radial topology of distribution networks with the supply located at one end. In this configuration, the fault cur-rent is provided by the utility grid with protective device (PD) settings adjusted accordingly to localize the impact of faults. PDs are coordinated based on unidirectional power flows from the feeder toward loads in radial distribution networks, in which fault currents would be lower as fault locations get farther from feeders. However, these unidirectional characteristics change in microgrids. The DER units located in microgrids can increase fault currents, change fault current flow paths, result in bidi-rectional power flows, and affect PD operations. The inclusion of DER units with power electronic interfaces, such as converters, would limit fault cur-rents and desensitize PDs to faults es-pecially in island mode. The large difference between fault currents in grid-connected and island modes presents new challenges in microgrid fault protections. Moreover, the mi-crogrid topology can be looped, meshed, or mixed networks, which could result in more complex fault current paths and affect protection

strategies in microgrids. The authors conclude the article with several ex-amples of a practical microgrid.

The seventh article by Dimeas et al. discusses the SmartHouse project in the European Union (EU). The authors point out that the infrastructure that will exist in the future smart houses is expected to be highly heterogeneous. However, it seems that, at some level, all devices—either by themselves or via gate-ways—will be able to communicate over the Internet protocol and participate in bidirec-tional collaboration with other devices and enterprise services. Similarly, multiple concepts for monitor-ing and controlling the smart houses and the smart grid will emerge, with different optimization and control algorithms. It is therefore imperative not to focus on a single one-size-fits-all approach but to prove that an amalga-mation of the existing approaches should be developed. The SmartHouse/SmartGrid project in the EU can be seen as the first step to developing mechanisms for “gluing” different monitoring and control approaches as well as empowering the next-genera-tion enterprise services and applica-tions. The authors point out that innovative technologies and concepts will emerge as power systems shift toward a more dynamic, service-based, market-driven infrastructure where energy efficiency and savings can be facilitated by interactive distribution networks. A new generation of fully interactive information and communi-cation technologies infrastructure has to be developed to support the optimal exploitation of the changing, complex

business processes and to enable effi-cient functioning of the deregulated energy market for the benefit of con-sumers and businesses.

Finally, in the “Viewpoint” column, Chiesa and Zirkelbach argue that mi-crogrids help utilities more than they hurt. They point out that microgrids are not coming; they are already here. From the innovations that created

Pearl Street to the transformations that are driving the grid innovations today, microgrids are here to stay and repre-sent a new business model for both con-sumers and utilities. The past is littered with old business

models, such as pay phones, and the companies that survived the introduc-tion of disruptive technologies are the ones that adapted and changed their business models appropriately, such as AT&T and Verizon. Therefore, utilities and customers need to continue to work together to find ways to adapt the old grid models to the new smarter grid realities.

In the EndWe believe that it is important to understand the end game. Are microgrids a silver bullet for the indus-try, replacing central-station genera-tion and the grid? No. There are many reasons for a vibrant, cost-effective grid and large-scale generation busi-ness. But, over time, microgrids will become a mature tool in the toolbox of cost-effective, reliable, resilient, and sustainable electric system design…and that is exciting!

Many of the microgrids

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its aftermath were built

for cost-saving reasons.

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T E C H N O L O G Y L E A D E R S


By John D. McDonald

O MOVE MICROGRIDSfrom the potentially irritat-ing “hype cycle” across the

dreaded “trough of disillusionment” and up the slippery “slope of enlight-enment” to reach the long-sought “plateau of productivity” might seem a daunting task, particularly given the obviously melodramatic language that often accompanies technolo-gy maturation and market accep-tance. Nonetheless, the promise of microgrids for achieving energy as-surance—essentially a measure of reliability—when coupled with other crucial value propositions, including environmental and economic goals, deserves review. While not all tech-nology advancements survive be-yond the hype cycle, every successful technology must endure a journey that begins in a giddy whirlpool of potential outcomes.

In the case of microgrids, many stakeholders are optimistic that the fundamental strengths of the technol-ogy and its myriad applications will prevail over what appear to be sur-mountable hurdles. But to move beyond the hype, the technology’s driv-ers and opportunities should be spelled out alongside an honest review of the barriers to implementation.

My own related work focuses on interconnections, where technology,

standards, and policies join grid to microgrid. To develop the proper con-text for interconnection-related issues, I will begin by defining microgrids in general terms and describing typical use cases. Then, Iwill turn to recent efforts by the state of Minnesota to explore microgrid drivers, opportunities, hurdles, and next steps. It is in that specific con-text that a description of ongoing changes to interconnection stan-dards and policies will make the most sense. The discussion is rele-vant not only to Minnesota’s interest in microgrids but to other states, util-ities, microgrid sponsors, and readers of IEEE Electrification Magazine.

Definitions, Drivers, and HurdlesDefinitions can be a perilous exer-cise, but let us try one. Microgrids are often conceived as self-con-tained energy systems with the abil-ity to operate independently of the grid, either as stand-alone systems or, if grid tied, by islanding—discon-necting from the grid while continuing to operate. Microgrids must possess their own generation source(s), typi-cally under the category of distribut-ed generation (DG), which could be fossil fuel-driven (likely diesel) gen-erators and/or renewable resources such as wind turbines, solar photo-voltaic (PV) cells, fuel cells, or other means. Microgrids include load

management functionality to bal-ance the supply/demand mix, per-haps aided by energy storage in chemical or thermal form.

Drivers are many, and they range from energy assurance, where that single benefit is sometimes deemed to outweigh high costs, to implemen-tations based on a variety of specific goals that offer a positive business case. Likely sponsors range from utili-ties to large customers such as cities and towns and military installations, universities, schools, and hospitals (MUSH). The fact that a microgrid can serve a nonutility sponsor by provid-ing a degree of self-sufficiency, of course, is often perceived to challenge utility interests by reducing volumet-ric sales, a traditional avenue for utili-ty revenue. That is a policy issue that must be addressed as such. But tech-nological challenges presented by microgrids must be overcome as well, particularly regarding their intercon-nection with the utility grid. In fact, amendments to fundamental inter-connection standards are ongoing, and all stakeholders will gain by tracking progress in this vital area.

Although this article focuses on interconnection standards and poli-cies, I will finish by discussing how regulatory reform to a more results-based approach can improve incen-tives for utilities to implement or accommodate microgrids. In fact, the path of least resistance to

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Microgrids Beyond the Hype: Utilities Need to See a Benefit

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accelerated adoption of microgrids will be the path that supports clear, attractive benefits for the affected utility. Certainly, the default position in a case where a microgrid is sought by an end user or a third-party devel-oper is, at the very least, to not adversely impact the affected utility.

Typical Use CasesIt is worth reviewing typical use cases to provide context for Minneso-ta’s exploration of microgrid opportu-nities. The U.S. Department of Defense (DoD) is a leading adopter of microgrids for stationary bases to meet its fundamental obligations to protect the American people, the homeland, and our allies, where our bases are located, overseas. The busi-ness case, which is so important to private enterprise, takes a backseat to mission criticality in this example.

In contrast, a variety of industrial facilities, such as ports, mines, refin-eries, airports, and campuses, require uninterruptible power to ensure the continuity of processes, the safety of patients and the public, and/or the protection of assets. Energy assur-ance and its costs in those cases are typically weighed in light of the cost of the consequences of power failure. On corporate campuses, especially in regions where the cost of grid-based electricity is high or very volatile, a self-contained system offering a mix of DG and load control creates an attractive business case. The same is true for isolated, off-grid communi-ties where fossil fuel must be shipped in at great cost.

On the utility side, a microgrid can provide the advantage of island-ing to reduce load on a stressed cir-cuit, defer capital investment in capacity (known as a “deferral opportunity”), or meet load growth through a line extension. Microgrids can provide a controllable means of managing DG, especially where intermittent renewable energy sources can lead to voltage instabili-ty and other operational issues.

Utilities in California and Maine are exploring the latter opportunities, while in Connecticut, nonutility actors, including municipalities, are considering microgrids to bolster sys-tem reliability in the wake of a series of devastating storms that culminated in 2012’s Hurricane Sandy. In contrast, Minnesota has a history of viewing energy assurance as a fundamental aspect of economic productivity and stability and energy innovations as a means to achieve environmental and self-sufficiency goals.

The Land of 10,000 LakesMinnesota is the 12th largest state and straddles the continental craton, which has been etched by glaciers, leaving innumerable freshwater lakes, thus its nickname, “Land of 10,000 Lakes.” Its population of roughly 5.5 million citizens is relatively highly educated and exhibit high voter turnout. More than half of the state’s residents cluster around the Twin Cit-ies of Minneapolis and Saint Paul, hubs of business, industry, transportation, edu-cation, government, and a thriving arts community. Itseconomy, historically based on agrar-ian pursuits and natural resource extraction, has evolved into a well-integrated mix of finished products and services. Thirty-three of the top 1,000 publicly traded companies in the United States by revenue were headquartered there in 2008. Minne-sota borders Canada to the north, the Dakotas to the west, Wisconsin and Lake Superior to the east, and Iowa to the south.

Whether those factors translate to the state’s policy support for DG, renewable energy resources, and energy alternatives I will leave to the experts on Minnesota. Suffice it to say here that state policy makers

determined last year to take a hard look at microgrids, which appeared to align with the state’s energy, environ-mental, and economic policy goals, with an emphasis on energy assur-ance as a pillar of the local economy.

American Recovery and Reinvestment Act Grant for Microgrid StudyThe Minnesota Department of Com-merce’s Division of Energy Resources sought and won a U.S. Department of Energy grant under the American Recovery and Reinvestment Act that funded many related smart grid proj-ects in the 2008–2009 time frame. (The fact that Minnesota’s Depart-ment of Commerce has a Division of Energy Resources reflects the fact that energy assurance is considered a mainstream, bread-and-butter issue

to the economic health and welfare of the state.) Policy mak-ers wanted to better understand the driv-ers, opportunities, and barriers associat-ed with microgrid adoption and the effects on the gamut of stakeholders. To that end, the state contracted with a

microgrid team led by Burr Energy LLC, to which I contributed my exper-tise on interconnection standards and policies. I was one of seven co-authors of the resulting study, “Minnesota Microgrids: Barriers, Opportunities, and Pathways Toward Energy Assurance,” which was pub-lished by the Minnesota Department of Commerce in September 2013. The white paper was incorporated as an annex to the official Minnesota Ener-gy Assurance Plan.

The six-point scope of the white paper (paraphrased for brevity) lays out the context here.

Review regulations and policies affecting microgrid development, ownership, and operation.

The path of least

resistance to

accelerated adoption

of microgrids will be

the path that supports

clear, attractive

benefits for the

affected utility.

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Identify applicable interconnec-tion standards and practices, including interoperability and control of distributed resources.Explain how traditional contract-ing, risk assessment, and financ-ing practices apply to microgrids and analyze Minnesota policies that affect microgrid development.Research and model potential electric loads available to mi-crogrids in Minnesota, and seg-ment those loads by user groups.Identify renewable resources in the state potentially accessible in microgrid applications and examine economic and opera-tional factors for possible renew-ables-based microgrids.Recommend policy steps that would capture microgrid benefits for Minnesotans and assist in the safe, cost-effective implementa-tion and integration into the util-ity system.

My charge, the focus of this arti-cle, can be articulated at slightly greater length. The importance of interconnection standards and poli-cies in this context was viewed as a fundamental, pragmatic matter. So the team was tasked with identifying Minnesota’s applicable interconnec-tion standards and practices, includ-ing interoperability and control of distributed resources. The team was also directed to compare and con-trast Minnesota’s standards and practices with current federal and industry standards and articulate dif-ferences that might affect microgrid development and optimization in utility systems.

The reference to standards regarding “optimization in utility sys-tems” in this element of the scope (as well as a similar reference in the final point listed previously) underscores that Minnesota is exploring microgrids for the benefit of its citizenry, with a clear intent to work with utilities. Minnesota public policy regarding microgrids reflects a commitment to make this innovation workable and

even beneficial from a utility stand-point. This wisely recognizes utilities’ prerogatives as well as the practical issues surrounding interconnections between microgrids and utility grids. Identifying mutual benefits makes sense because Minnesota’s current regulatory approach, which is based on cost-of-service rate making and vol-umetric pricing, initially puts investor-owned utilities and microgrids “squarely at odds,” as the white paper put it. As Minnesota clearly recognizes, utilities’ concerns about microgrids’ potential impact on their business model as well as impacts on opera-tional matters based on interconnec-tion issues are well founded and need to be addressed.

Utility Concerns on Microgrid Control, SafetyThe interconnection of a utility grid with DG systems is governed by a finite number of industry standards issued by the usual suspects, including the IEEE, Underwriters Laboratories, the International Electrotechnical Commis-sion, and the Federal Energy Regulatory Commission (FERC). All applicable standards are intended to address utili-ties’ concerns, for the simple reason that utilities operate the grid to which microgrids would interconnect and they have significant, regulated public responsibilities. Those concerns can be summarized in four categories:

1) Anti-islanding features are need-ed to prevent the unintentional flow of current from grid-con-nected DG onto a circuit that oth-erwise should not be energized, as in an outage.

2) Distribution systems do not all have protection equipment to safely prevent short circuits from DG running in synchronous, parallel interconnection to the utility grid.

3) Synchronized generators that fluctuate to follow microgrid loads or intermittent renewable energy sources can cause voltage instability, forcing the utility to

install expensive capacitor banks and voltage regulators to main-tain voltage stability.

4) Utility grid operators often have little or no visibility into custom-er-owned DG, resulting in subop-timal operations for both parties.

Recent developments in intercon-nection technologies and new approaches to microgrid control have provided cost-effective solutions to many utility concerns. And new methods of testing and simulation can rapidly prove the safety of microgrid-related technologies and practices. (The white paper’s appen-dices offer case studies in support of this statement.) That said, it certainly behooves utilities to have an active testing program to assess how new technology affects their systems, a precaution that can benefit their cus-tomers. However, cultural factors must be addressed as well. Power systems engineers’ experience has bred mistrust of new systems until exhaustive field testing has conclud-ed that they are effective and safe. Given utilities’ public obligations and the danger of high-voltage power, caution is justified. And, as we shall see, in Minnesota as elsewhere, cur-rent policies may give utilities the upper hand in facilitating or inhibit-ing microgrid development. Thus, the onus is on microgrid sponsors to demonstrate the safety, reliability, and cost-effectiveness of their sys-tem to the utility—if utility coopera-tion is to be expected.

Applicable Standards and New AmendmentsFor microgrid development in Minne-sota, the most important standard is IEEE 1547, Standard for Interconnect-ing Distributed Resources with Elec-tric Power Systems. IEEE 1547, approved in 2003, aims to provide a uniform set of criteria and require-ments for interconnecting the grid with DG. Its requirements relate to the testing, operations, maintenance, and safety of the grid-to-DG

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interconnection. IEEE members have approved eight complementary stan-dards, including IEEE 1547.4 and IEEE1547.8, which may be affected by a currently active amendment process.

In recognition of the measured pace that characterizes standards development and the speed with which microgrid technology is advancing, IEEE P1547a-Amendment 1 was introduced to speed up high pri-ority changes to IEEE 1547. This amendment updates practices regarding voltage regulation and responses to abnormal voltage and frequency conditions on the grid. As of this writing, the amendment has cleared the balloting process and is subject to a comments period. If approved, as expected, the changes in this amendment will go into effect in early 2014, followed by a compre-hensive overhaul of IEEE 1547 to resolve the additional issues that surfaced during work on IEEE P1547a-Amendment 1.

Two specific changes in IEEE 1547 address microgrids. DG systems henceforth may participate in volt-age regulation via changes in real and reactive power supplies, allowing utilities to integrate DG as grid-sup-porting resources. (Before this change, DG was not allowed to actively regulate voltage at the point of common coupling.) This change permits the microgrid sponsor to reg-ulate voltage and save energy in cases where the utility does not prac-tice conservation voltage reduction.

Whereas IEEE 1547 defined rec-ommended practices for DG system behavior in response to abnormal frequency conditions—i.e., spelling out when a DG system must stay connected and when it must discon-nect—amendments were fast tracked because of evolving con-cerns. A rapid increase in the pene-tration of PV rooftop systems in pockets around the country present-ed utilities with the possibility that perhaps hundreds of DG systems might disconnect at the same time

due to a dip in frequency on the grid. If an unscheduled outage at a major power plant caused the underfre-quency, then a sudden loss of DGpower could exacerbate the situation.

These amendments will enable microgrids to better meet utility inter-connection concerns to operate more efficiently and, thus, encourage their development. The first amendment provides for microgrid integration with dis-tribution control sys-tems and allows a microgrid to serve grid-support func-tions, a direct answer to specific utility con-cerns. The second amendment allows a microgrid to remain g r i d - c o n n e c t e d , which will preclude the introduction of unneeded backup generation for the utility. If an interconnected microgrid is feeding power onto the grid, the ride-through (second) amendment contributes to avoiding a bad-to-worse scenario.

Further work on standards will be needed. Standard information mod-els for microgrid control point func-tionality are in the early stages of development. The vision of a distribu-tion system comprising multiple, interactive microgrids in support of reliability for both distribution and transmission systems is getting clos-er to reality. These standards will take time, largely because technologies and applications are still maturing. Sophisticated smart grid applications in this context will require uniform standards as the need for interopera-bility increases.

Islanding and Anti-IslandingOne important clarification is in order here. The terms islanding and anti-islanding can be confusing.

IEEE 1547’s anti-islanding tenets were written to prevent unintention-al islanding of grid-connected gener-ation. Separate provisions provide

standards for intentional islanding. Pending changes in the standard should clarify how the two effects differ or relate.

Anti-islanding, a crucial safety function of protective systems, will remain as a provision of the amend-ed 1547 standard. Grid-tied, stan-dards-compliant DG systems typical-ly are grid activated, meaning that

they automatically shut down when an outage occurs, pre-venting unintention-al islanding.

An amended IEEE1547 will likely provide specific provisions to enable intentional islanding in cases where a microgrid or other islandable DG

source is designed to function both con-nected to and disconnected from the grid. For instance, IEEE 1547 originally encouraged highly sensitive trip-off set-tings. The downside of that approach is that a minor fault could lead to DGdeactivation. Given the high penetra-tion of DG, such hair-trigger settings for anti-islanding can lead to problems. Also, those settings represent a nui-sance for systems designed to isolate themselves and initiate backup genera-tion upon sensing a system fault. The proposed amendments to IEEE 1547 are focused on allowing a wider ride-through tolerance so that DG and microgrids can continue generation despite fluctuations in grid frequency.

In other words, the main differ-ence between anti-islanding and intentional islanding is that once a system is intentionally islanded, anti-islanding requirements no longer apply. The islanded DG system is dis-connected from the grid and, there-fore, is no longer a safety concern. IEEE 1547.4 will contain recommend-ed practices for intentional islanding, and the forthcoming 1547.8 standard addresses the functionality of small generators such as microgrids, which are designed to intentionally island.

Anti-islanding, a

crucial safety function

of protective systems,

will remain as a

provision of the

amended 1547

standard.

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In summary, islanding and anti-islanding features are designed to work in tandem in an amended IEEE1547. Furthermore, systems that com-ply with the amended version of IEEE1547 will allow for the stable intercon-nection of islandable microgrids while maintaining the safety of anti-island-ing features.

Interconnection CostsMany if not most states, including-Minnesota, have adopted regulations regarding (synchronous) intercon-nection based on IEEE 1547 and FERC’s small generator interconnec-tion procedures (SGIP), adopted in May 2005 under FERC Order 2006.

Several states that are concerned about the potential impacts of faults and unintentional islanding require the affected utility to study the impacts. This leaves the door open for utilities to delay a proposed microgrid via lengthy, expensive studies. Subse-quently, the microgrid developer might be required to pay for added protection measures on the grid to the tune of thousands of dollars per kilowatt of capacity. Such a cost in Minnesota, where retail electricity rates are rela-tively low, could easily sink a project. Knowing that such charges could be imposed and are largely unquantifi-able at the outset can deter developers from even proposing a microgrid proj-ect. These potential deterrents have led FERC and some states to simplify the impact study process and make it more transparent.

Changes in California’s regulations promise to provide a path forward in such circumstances. The California Public Utility Commission revised its “Rule 21” interconnection policies to set time limits for interconnection studies and mechanisms to resolve disputes between utilities and microgrid developers. California also established that interconnected DGon a distribution line segment can equal 100% of the segment’s mini-mum load. The previous policy limit-ed the interconnected DG to 15% of

the peak load on the segment in question. Both limits remain in place, but projects that do not meet the 15% of peak bar criterion remain eligible to proceed if they meet the 100% of the minimum load criterion.

While California’s revision of its reg-ulations was driven by high penetra-tion of DG, largely rooftop solar PV, it has implications for Minnesota. A large microgrid on a single distribution seg-ment could generate electricity at a level equal to scores of rooftop PVarrays. Standards that accommodate DG systems in which smart inverters provide voltage support can also apply to a microgrid acting as a DG source, a controllable load, or both. The best practices established by California and FERC illustrate how policies can make interconnection studies more trans-parent and certain.

FERC policies are relevant to Min-nesota’s case in that they cover DGprojects up to 20 MW in size and how they interconnect with interstate transmission systems, which is important if a Minnesota microgrid wishes to sell wholesale power into the Midwest Independent System Operator market. FERC has issued a notice of proposed rule making that it seeks to amend its SGIP and small generator interconnection agreement (SGIA) policies to, in FERC’s words, “ensure the time and cost to process small generator interconnect requests will be just and reasonable and not unduly discriminatory.”

Enter: Results-Based RegulationI have discussed the gamut of utility reactions to microgrid proposals, from an enlightened grasp of the opportu-nity for grid benefits and shared capi-tal investment to the use of impact studies to derail a proposal. We have reviewed the strengths and weak-nesses of existing and evolving stan-dards and policies to address the uncertainties that produce such a wide range of utility stances. Looming over these crucial details is each

state’s approach to traditional utility business models in the smart grid era.

A more flexible, results-based reg-ulatory scheme that accommodates and rewards utility actions that demonstrably benefit their customers has been proposed by my colleague, David Malkin, and his co-author, Paul Centolella, in their recent article, “Results-Based Regulation: A More Dynamic Approach to Grid Modern-ization” (Public Utilities Fortnightly,February 2014). The simplest notion in this realm, of course, is well-known as decoupling—creating a model for utility revenue that is independent of the utility’s volumetric electricity sales. Malkin and Centolella’s article provides a rationale for that thinking and advances it.

“Results-based regulation is designed to support investments that deliver long-term value to customers, reward utilities for exceptional perfor-mance, and remain affordable by encouraging operational efficiencies and sharing the cost savings with cus-tomers,” Malkin and Centolella write.

As one example in which results-based regulation would reward utilities for providing that long-term value to customers, Malkin and Centolella cite the fact that “distribution utilities are increasingly expected—and, in many cases, required—to perform funda-mentally new functions,” including resiliency in the face of extreme weather, the integration of distributed and variable, renewable generation, and cyber security. The limits of more typical cost-of-service regulation often fail to consider “the value of uninter-rupted electric service to different cus-tomers,” Malkin and Centolella write.

If a state such as Minnesota wishes to encourage microgrid development, regulatory policy will need to evolve along with standards not simply to enable microgrid adoption but to reward the cooper-ating utility for making possible a customer benefit that cuts into its revenue base. Thus, policy and stan-dards should work in tandem.

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Minnesota Standards PolicyInterconnection requirements in the state of Minnesota were issued on 28 September 2004 (Docket No. E-999/CI-01-1023). A subset of those regula-tions governs small, grid-tied DG. The IEEE’s consideration of IEEE 1547a amendment and more likely changes to come to existing IEEE 1547 stan-dards—plus FERC’s proposed revi-sions to its SGIP and SGIA—should lead Minnesota to review its own existing interconnection standards and tariffs. This should be an ongoing process for years to come, given the speed of change in standards, best practices, and technology in this space. If Minnesota continues to see value in microgrid adoption, it needs to institute a regular standards review process and swiftly adopt new, approved standards. On the utility side, some of Minnesota’s utilities have staff that serve on the IEEE Stan-dards Committee and, thus, are well aware of pending changes in these areas. Other utilities have dedicated distribution technology teams charged with reviewing standards and best practices, which will have to monitor and adapt to related changes.

One immediate change Minnesota needs to make in its own regulations is to change its restrictive definition for DG capacity. The state’s interconnec-tion requirements set thresholds and size limits on DG and microgrids, with thresholds at 40 and 100 kW and a sys-tem capacity at 10 MW, half the size of FERC’s 20-MW limit for small genera-tor treatment. That’s lower than most other states, several of which have no limits at all. The current rules force larger microgrid proposals to forge unique agreements with a utility at greater cost and uncertainty.

Next StepsShould the state of Minnesota decide that encouraging microgrid develop-ment aligns well with its policies regarding energy assurance as a pillar

of economic stability and growth, it has regulatory and legislative paths to achieve its aims. Currently, its inter-connection standards and tariffs are outdated. They do not accommodate grid-integrated microgrids with a com-bination of generation, storage, and load-management functionality, and they set outmoded thresholds and lim-its for size. An ongoing review and revision of the state’s interconnection policies will help it keep pace with evolving standards. As technology changes often outpace IEEE balloting and FERC rule-making processes, Min-nesota can look to other states whose standards and practices better reflect prevalent industry norms as a guide.

Of course, interconnection stan-dards and tariffs are but one set of con-cerns and opportunities for action in Minnesota and elsewhere. Minnesota’s microgrid road map includes many steps best taken simultaneously. One important step, among others, is to establish a working microgrid with stakeholders that include the state, a local utility, and a microgrid developer; make it a pilot project not a demon-stration project—the technology has been demonstrated; use the microgrid and its interconnection to satisfy utili-ty safety concerns and create a busi-ness case that demonstrates value to the utility as well as its shareholders and customers; and make sure that interconnection policy, standards, and practices are kept current to enable the technology’s potential.

We may be climbing that slippery “slope of enlightenment,” but the “plateau of productivity” beckons from the horizon, clearly visible. Many, including myself, believe that we can get there from here.

For Further ReadingD. Malkin and P. Centolella. (2013). Results-based regulation: A modern approach to modernizing the grid. GEDigital Energy/Analysis Group. [Online]. Available: http://www.

analysisgroup.com/uploadedFiles/Publishing/Articles/Centolella_GE_Whitepaper_Electricity_Regulation.pdf

K. Fox, S. Stanfield, L. Varnado, T. Culley, M. Sheehan, and M. Codding-ton, “Updating small generator inter-connection procedures for new market conditions,” NREL Technical Report, NREL/TP-5500-56790, National Renew-able Energy Laboratory, Dec. 2012.

M. A. Hyams, A. Awai, T. Bourgeois, K. Cataldo, S. A. Hammer, T. Kelly, S. Kraham, J. Mitchell, L. Nurani, W. Pentland, L. Perfetto, and J. Van Nostrand, “Microgrids: An assessment of the value, opportunities, and barriers to deployment in New York State,” Final Report, prepared for the New York State Energy Research and Development Authority (NYSERDA), Rep. 10-35, Sept. 2010.

M. T. Burr, M. J. Zimmer, B. Meloy, J. Bertrand, W. Levesque, G. Warner, and J. D. McDonald. (2013). Minnesota mi-crogrids: Barriers, opportunities and pathways toward energy assurance, Minnesota Department of Commerce. [Online]. Available: http://mn.gov/commerce/energy/images/MN-Microgrid-WP-FINAL-amended.pdf

(2013). Model interconnection pro-cedures, Interstate Renewable Energy Council. [Online]. Available: http://www.irecusa.org/wp-content/uploads/2013-IREC-Interconnection-Model-Procedures.pdf

P. Sheaffer. (2011, Sept.). Intercon-nection of distributed generation to utility systems: Recommendations for technical requirements, procedures and agreements, and emerging issues, Regulatory Assistance Project (RAP). [Online]. Available: www.raponline.org/document/download/id/4572

BiographyJohn D. McDonald ([email protected]) is the chair of the Board of the Smart Grid Interoperability Panel (SGIP) 2.0, Inc., and the Smart Grid Consumer Collaborative (SGCC). He is a Fellow of the IEEE.

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IEEE Electr i f icat ion Magazine / MARCH 201412 2325-5987/14/$31.00©2014IEEE

HE U.S. UTILITY GRID WAS GRADED A lowly D+ by the American Council of Civil Engineers in 2009. Although that was five years ago, the performance of the U.S. grid has actually declined since that grade was

issued. The Galvin Electricity Initiative estimates that the present antiquated dumb electric grid costs U.S. consum-ers US$140 billion annually because of power outages.

This declining quality of power service in the United States is contributing to a flood of interest in the concept of microgrids. These modular low- to medium-voltage distribution level networks can (theoretically) provide 24/7 energy services regardless of the status of any larger utility grid network. At the same time, microgrids can reduce carbon emissions regionally and improve the overall efficiency of the larger power grid—if they are authorized to do so by regulators and utilities. It is this latter possibility of providing ancillary services to the larger grid that is allowing microgrids to inch their way into the mainstream, sparking debate within the corpo-rate suites of utility executives as well as within the cir-cles of utility engineers.

No doubt, the future development of the U.S. grid will require the safe and economic operation of the high-volt-age meshed transmission grid since it is a US$800 billion

asset that is fully amortized. Yet, the fundamental archi-tecture of today’s electricity grid, which is based on the idea of a top-down radial transmission system predicated on unidirectional energy flows from large centralized power plants, is increasingly becoming obsolete. The econ-omies of scale that once favored such monopoly models no longer hold as markets now favor distributed and decentralized devices whose energy services are more customized and based on local availability and timing.

Perhaps the most glaring statistic gleaned from the U.S. Energy Information Administration is this: for every 1 MW of power consumed by U.S. commercial and resi-dential customers, rate payers are paying for 2.2 MW of generation and transmission capacity. That means that we are building twice as much wholesale supply capaci-ty as what is ideally needed. If instead, the utility power grid took advantage of new smart grid technologies as well as growing innovation on the financial side in the form of new transactive energy service business mod-els, these numbers would look very different. One answer to this inefficiency is networks of distributed energy resources providing a greater share of local needs, shrinking line losses associated with centralized power plants, and building greater resiliency into the overall system. In short, a greater reliance upon microgrids to aggregate and optimize distributed energy resources (DERs).

A clear definition of what is and what is not a microgrid is still open to debate. Do microgrids need to


Improving the efficiency of the larger power grid.

By Peter Asmus

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incorporate renewables? Must they deploy smart meters? Must they be able to seamlessly disconnect and then reconnect to the larger ac utility power grid? These are all open questions.

The only government agency to define a microgrid is the U.S. Department of Energy (DOE):

A microgrid is a group of interconnected loads and DERs within clearly defined electrical boundaries that act as a single controllable entity with respect to the grid. A microgrid can connect and disconnect from the grid to enable it to operate in both grid-con-nected and island-mode.Navigant Research has broadened this definition of

microgrids to include remote systems in its analysis. Remote microgrids are networks that are not typically interconnect-ed with any utility grid or may interconnect with a highly unreliable grid; therefore, they operate in island mode for a majority of the time. Paradoxically, it is these remote, off-grid

systems that were first called “microgrids” decades ago before anyone mentioned the phrase “smart grid.”

Why Microgrids Now?As noted at the outset, the recent performance of the U.S. power grid has highlighted the shortcomings of the status quo. Lawrence Berkeley National Laboratory statistics show that 80–90% of all grid failures begin at the distribution level of electricity service. This is the exact portion of the power system where microgrids can play an important role, bol-stering reliability from the bottom up, rather than from the top down. The U.S. average outage duration is 120 min annually, and that number is getting worse, while the rest of the industrialized world is less than 10 min and getting better. Since electricity travels almost at the speed of light, 186,000 mi/s, a power outage of just 1/60th of a second can crash critical radar systems at a military base or life support systems in a hospital, with catastrophic impacts.

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Instead of using a utility smart grid program to raise the level of homogeneous power quality for all captive cus-tomers of a regulated utility monopoly, microgrids that function within the developed world’s utility transmission and distribution networks offer the flexibility to provide heterogeneous power products and services to meet spe-cific end-user needs and requirements. Microgrids can also shrink the amount of fossil fuels consumed to create elec-tricity by networking generators as a system to maximize efficiency. In addition, they can be used to help integrate renewable energy resources (such as wind and solar) at the

local distribution grid level and even sell ancillary services back to either utility or transmission system operators.

It has become quite clear that the modern digital econo-my requires a more advanced, robust, and responsive power grid framework than what exists today, especially in North America, which is the world’s leading market for microgrids (see Figure 1). While many smart-grid technologies can help manage outages and allow power to be restored much more quickly than in the past, the most promising technology that has evolved to mitigate extreme weather events is, in my view, the microgrid. Potential on-site DER solutions, such

Capturing the Reliability Value Microgrids Provide

Until recently, the vast majority of microgrids coming online, whether grid-

connected or off-grid, have been pilot projects or R&D experiments. Now, the industry is moving into the next phase of project development, focusing on how to develop projects on fully commercial terms. It appears that the main technology components of a microgrid have made significant headway. The key to future growth now rests with greater creativity in both the public policy and business model arenas.

The increasing frequency of severe weather is prompting utilities in the United States and around the world to reconsider their historic opposition to customer-owned microgrids that can disconnect from the larger grid and island, allowing critical mission functions to stay up and running. Yet, utilities continue to worry about how a proliferation of customer-owned microgrids might complicate their job and whether regulators would instead allow utilities to build, own, or control these microgrids in some sort of coordinated enterprise-wide fashion.

Quantifying the benefits of reliability is both art and science. At this point in time, there is no widely recognized financial metric to monetize the value of energy security and reliability. An analysis conducted by the National Renewable Energy Laboratory looked at a military base, Fort Belvoir, and found the that value of electrical energy security (VEES) at that site ranged from US$2.2 million to US$3.9 million annually. This range reflected the mission of the respective loads within the base and recent performance metrics of each respective utility. Since each microgrid is a customized solution, it is also difficult to generalize about any VEES cost advantages

such networks can offer if compared to a host distribution utility (whose cost of service also varies per geography and utility market structure). Despite this diversity and complexity, the business cases for microgrids continue to mature as project performance is increasingly measured and quantified.

What About Remote Microgrids?The remote microgrid market epitomizes the promise and the perils attached to new business models that shake up the status quo. Although the term “microgrid” once applied almost exclusively to off-grid hybrid systems, it now refers more commonly to grid-tied systems that deploy smart grid technologies. From a vendor revenue perspective, remote systems are remarkably robust, thanks to their assumed 24/7 performance, which requires significant investments in both hardware and software. On a per-kilowatt basis, remote microgrids represent a 50–100% cost premium over equivalent grid-tied microgrid installations: the smaller the system, the higher the per-unit value.

Today’s remote microgrids’ target niche markets are the following: commodity extraction facilities—such as a mine—that are not connected to an existing grid, physical islands burning diesel fuel for power, rural villages in the developing world, and mobile and tactical applications for military agencies. The key market drivers of today’s remote microgrid market are:

■ declining cost of solar photovoltaic (PV) technologies

■ rising costs of diesel fuel, the default generation choice for much of the developing world and for physical and commodity extraction off-grid applications

■ investments in more advanced energy storage options, many of which are ideally suited to remote microgrid applications

■ efforts by nongovernmental organizations and governments to provide universal access to energy in the developing world

■ efforts by large technology companies, such as ABB, Boeing, General Electric, Lockheed Martin, Siemens, Samsung, SMA, and Toshiba, to secure their place in the emerging microgrid market

■ growing interest among financial institutions on new business models for energy delivery, including on-site power generation

■ the proliferation of cell phone technology, which is prompting demand for electricity in remote regions of the world, providing a model of technology dispersal that mimics the Internet, and is more in line with microgrids than traditional utility distribution systems.

The International Energy Agency estimates that by 2020, developing countries will need to double their electrical power output. The demand for energy, especially electricity, is growing much more rapidly in these nascent economies than the rate of expansion of conventional electricity grids in the major industrialized world. All told, the developing nations will represent 80% of total growth in energy production/consumption by the year 2035. One could safely assume that the majority of these new power supplies will be produced and distributed via remote microgrids and other related forms of DERs, offering substantial vendor revenues (see Figure S1).

Why Remote Microgrids MatterDOE-defined grid-tied microgrids offer significant societal value and billions of dollars in potential vendor revenues. But the

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as rooftop solar photovoltaic (PV) systems, combined heat and power (CHP) plants, batteries, and other storage devices (including electric vehicles), can become stranded assets that trip offline as the larger network of nuclear, coal, and natural gas plants also goes down in a storm. However, this is not the case if one incorporates this diverse set of DERwithin an islanding microgrid.

Thanks to advances with smart, bidirectional inverters, microgrids connected to utility distribution grids can now provide a level of reliability and sustainability not possible a decade ago. While resistance among utilities to allowing

these smart inverters to take action remains high, momentum is building within the regulatory and policy community to accommodate technology advances in decision making. If we can break away from past protocols that preclude intentional islanding and move toward inverter-based DER such as solar PV systems, small wind, fuel cells, or advanced energy storage—all key microgrid enabling technologies—the overall system can be cleaner, more efficient, and more reliable.

Current trends toward a more distributed energy future appear to make microgrids an inevitable augmentation of

best value proposition for microgrids today is remote islands. Thousands of these islands in Indonesia, China, the Caribbean, and the Mediterranean are still powered by dumb, dirty diesel generation. Others showcase smart and much cleaner combustion technologies capable of reducing diesel consumption by as much as one third, even without any renewable generation. When renewable distributed energy generation (RDEG) is added to the mix, these remote systems begin to look like the classic microgrids that have been the focus of most of the DOE and U.S. Department of Defense funding.

The closest analogy to remote microgrids funded by the U.S. government are the so-called “mobile microgrids” deployed at military forward-operating bases in Afghanistan and Iraq as well as at other temporary or remote bases throughout the world. Companies such as Lockheed Martin have developed hybrid controls, featuring both distributed and supervisory modes of operations. Sandia Labs and IPERC are experimenting with advanced artificial intelligence algorithms to make extremely complex decisions to develop super-secure microgrids. Boeing’s offering embeds cybersecurity down to the end-device level, something they developed decades ago for our nation’s satellite program.

These projects pencil out because diesel-power incumbent minigrids are so expensive (US$1–$30 per kWh) and the cost of solar PV has dropped so dramatically. The falling price of lithium-ion batteries is also playing a role. And perhaps most importantly, they are pioneering ways to aggregate and optimize microgrids. Generally speaking,

these systems tend to rely on a bottom-up distributed control model rather than the top–down centralized controls paradigm that dominates the larger power grid.

In the case of grid-tied microgrids, the utility grid offers inertia that can often help resolve supply, frequency, or voltage irregularities that can compromise service performance. In the case of remote systems, an existing grid—if there is one—often plays the opposite role due to poor reliability and may jeopardize the operations of the microgrid. To perform well, remote microgrids must rely on a fossil prime mover to set frequency or voltage, or employ advanced microgrid-enabling technologies such as a smart grid-forming inverter or some form of advanced energy storage. In either scenario, redundancy and resilience must be factored in during the design process.

The future of the microgrid market really rests on the controls and what they will cost. This is the black box, the secret sauce, the

critical path for microgrid commercialization. The diversity of companies and hardware and software solutions designed to solve these controls challenges grows almost weekly. Will CERTS become the common dominator, or will an ABB, GE, Siemens, or Schneider Electric become the Intel or Microsoft of the microgrid world?

It could all come down to the right controls philosophy. Whether remote microgrids will really reshape the vendor landscape for microgrids remains to be seen. The market is clearly best served by the diversity of controls approaches being deployed today. The entire global microgrid market could reach US$10, $20, or $36 billion in vendor revenue by 2020. In any case, this market is on the move despite a lack of clear standards and policies. I anticipate that the status quo will not prevail and that disruptive new business models will propel microgrids into the mainstream by 2020.

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Figure S1. The total remote microgrid revenue, all segments, base scenario, world markets from 2013 to 2020. (Source: Navigant Research.)

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today’s centralized grid infrastructure. (See “Capturing the Reliability Value Microgrids Provide.”) Aggregation plat-forms similar to microgrids will be absolutely necessary if energy infrastructure follows in the footsteps of telecom-munications and the evolution of today’s Internet. Without a doubt, the existing radial transmission grid will still pro-vide the majority of power supplies to the industrialized world in the near term. RDEG, never-theless, will also play a larger role in providing energy supply, reliability, security, and emergency care services when these and other DER are net-worked via microgrids.

The Top Four Microgrid Drivers TodayThis article focuses on the four prima-ry reasons why grid-tied microgrids are moving into the mainstream. These are briefly described and ad-dressed in more detail:

IEEE has played a vital role in increasing knowledge about tech-nology advances to the broader engineering community, updat-ing grid protocols to create room for modern microgrids.Engineering arguments on behalf of microgrids have also added momentum to a push to recognize advan-tages attached to medium-voltage dc.Instead of representing the departing load of attrac-tive commercial and industrial (C&I) customers to utilities, there is a growing recognition that microgrids can serve as the most reliable form of real-time demand response (DR) and, if compensated properly, can lower the environmental (and economic) cost of voltage and frequency balancing.Copying successful business models from the solar PV industry, a growing pool of microgrid developers/inte-grators is moving forward with power purchase agree-ment (PPA) contracts, some of which even anticipate

future revenue sharing between developer and system host from the provision of ancillary services.

Upgrades to IEEE 1547Utility engineers have historically opposed the concept of islanding, citing safety concerns. This opposition is embodied in the Underwriter Laboratories (UL) 1741 safety standard, which was originally devised in 1999 and requires disconnection of distributed inverter-based gen-eration systems during an outage. Officially titled “The Standard for Inverters, Converters and Controllers for Use in Independent Power Production Systems,” UL 1741 was updated in 2011 and is now a certification that verifies which distributed generation units will not backflow onto the larger utility grid when it goes down. Microgrids chal-lenge that anti-islanding assumption; yet, many new inverter devices gain UL 1741 certification and still enable islanding. This is a clear sign of the schizophrenic relation-ship DER has with utilities and power grids. Fears of being electrocuted while fixing outages at the distribution level still shape perspectives on microgrids for many older line workers in the trenches.

This preconception was most clear-ly expressed in IEEE Standard 1547, which requires an automatic and rapid disconnection of all distributed energy generation during grid outages. For well more than five years, the IEEEworked on developing a guide on islanding to round out this series of standards. This guide, IEEE Standard 1547.4, went into effect in July 2011 and is a major step forward for microgrids. It spells out safe utility pro-tocols for islanding while also putting into place standards for reactive power, which will allow microgrids to sell ancillary services to distribution utilities. Although 1547.4 may not become a binding standard for utility

operators for another five to ten years, it is a major mile-stone for this emerging industry.

Also approved in 2011, IEEE Standard 1547.6 addresses recommended practices for interconnecting microgrids with electric power supply distribution secondary net-works. Among the other related IEEE guides in this series that help build consensus support for the engineering impacts of microgrids are:

IEEE Standard 1547.5: Guidelines for interconnection of electric power sources greater than 10 MVA to the transmission power grid.IEEE Standard 1547.7: Draft guide for conducting distri-bution impact studies for DER interconnection. Among the long list of issues relevant to microgrids covered by this guide are voltage regulation schemes, unintentional islanding prevention, false inverter trips due to utility

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Figure 1. The total microgrid capacity, base scenario, world markets from 2013 to 2020. (Source: Navigant Research.)

Remote microgrids are networks that are not typically interconnected with any utility grid or may interconnect with a highly unreliable grid.

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line transients, reactive power control schemes for mul-tiple inverters, impact of cloud cover on solar PV, use of DR, and issues surrounding the reverse power flow on secondary grid networks.IEEE Standard 1547.8: Draft recommended practice for establishing methods and procedures that pro-vide supplemental support for implementation strat-egies for the expanded use of IEEE 1547 standards. The purpose of this guide is to segregate fast-tracked DER projects from those requiring deeper levels of analysis due to high penetrations of distributed solar PV. It seeks to make RDEG and other DER utility friendly, with the prime solution set revolving around advanced smart inverters. The top topics of inquiry by IEEE are voltage regu-lation and power quality and how best to optimize the group behavior of DER sized between 10 and 20 MW in scale.

This set of IEEE 1547 standards was being reviewed in December 2013 and will likely undergo further revisions and enhancements moving forward.

Another set of IEEE standards that would accelerate the deployment of microgrids is the Smart Grid Interop-erability 2030 Series, which repre-sents a draft guide for IT, electric power systems, and end-use loads and applications. An IEEE Working Group is currently building on the overall interoperability subjects embod-ied in IEEE Standard 2030. The latter covers the engineer-ing, communications, and IT industries’ products designed for the smart grid, including standards for EV integration (IEEE Standard P2030.1) and energy storage (IEEE Standard P2030.2 and IEEE Standard P2030.3).

The Buzz About dcThe world has changed over the past 100 years. While large centralized power plants will continue to play a role in providing ac power to the wholesale macrogrid, there is growing momentum at the distribution level of electric service to diversify power offerings and pursue dc–ac hybrid solutions. More and more, the loads served today by ac power grids are natively dc. In fact, according to some estimates, approximately 80% of loads in commer-cial and residential structures are now native dc. Given the enormous political and policy support for inverter-based native dc power sources such as solar PV, wind, fuel cells, and energy storage, it makes sense to reduce dc–ac–dc conversion losses and integrate dc distribution networks such as microgrids into the power supply infrastructure.

Many of the utility concerns and the subjects described by the aforementioned IEEE standards relating to microgrids can be mitigated in novel ways by medium-

voltage dc networks. Among the advantages of dc distri-bution network infrastructure are:

eliminated reactive power constraintseliminated need to synchronize diverse generation sources to a single ac grid frequencyoverall higher system efficiencyease of interconnection of dc generation sources (solar, wind, and fuel cells)ease of interconnection of electrochemical devices (flow and other forms of advanced battery systems).

Led by companies such as Intel, Johnson Controls, and Emerson Network Power, the EMerge Alliance is now

advocating for a return to dc systems in the developed world. These sys-tems would subsequently pave the way for state-of-the-art dc digital sys-tems in the developing world. Even today, companies like Nextek Power specialize in dc power distribution optimization. Nextek Power offers a direct coupling technology that dis-places the need for dc/ac inverters for microgrids interconnecting to the larger utility ac grid. In addition, ABB has been selling high-voltage dc transmission systems for about five decades and also offers a variety of dc-based products relevant to microgrids.

There is heated debate today about the advantages and disadvantages of dc. Here are just a few of the myths that need to be debunked, according to dc advocates, for this class of power distri-bution equipment to become widely accepted and help push dc microgrids into the mainstream:

DC is only 1% or 2% more efficient, so why bother? While this may be true at low-voltage levels, recent research by a variety of entities that include Intel shows that medium voltage (380 V dc) is 7–8% more efficient.DC requires large conductors and can only be trans-mitted for a few meters at a reasonable cost. Again, this is true for the majority of systems deployed today at the −12 V, −24 V, or −48 V level, it does not hold true at the same 380 V medium voltages now being devel-oped for distribution networks.If a network is run off of dc batteries, this eats up all of the efficiency gained by the dc current. While there is some validity to this fear, it is equally true that this may be an appropriate tradeoff for a reliability gain that can reach 1,000%.Arc flash is an unacceptable hazard for dc. Again, new technologies, such as magnetic arc breakers and switched interlocks, can address these safety concerns at a relatively modest cost.AC is safer because the voltage crosses zero at either 50 or 60 times/s (i.e., 50- or 60-Hz ac grids). This is

Current trends toward a more distributed energy future appear to make microgrids an inevitable augmentation of today’s centralized grid infrastructure.

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only true if the current is not leading or lagging. While components are currently more expensive to address such issues, these extra costs can be offset by the large cost savings at the higher voltage distribution level due to a 10–15% gain resulting from simplicity in system design.

At present, the majority of progress in developing dc-based technologies has occurred at either the high-voltage (more than 1,000 V) or low-voltage (less than 100 V) level of electricity service. Since microgrids typically operate at medium voltage (~380–400 V), much work needs to be done to bridge this voltage innovation gap.

As Figure 2 illustrates, interest in dc microgrids is high-est in the Asia Pacific region, with the vast majority of these being small remote microgrids featuring remote cell phone towers as anchor loads. Banks will finance this infrastructure. These networks can then be expanded to local communities. The modularity of the dc backbone to a microgrid is well suited to this application. The other most promising dc microgrid market is grid-tied data cen-ters, such as the 1-MW dc microgrid deployed by ABB in Zurich, Switzerland.

Emerging Organized Markets for Grid Ancillary ServicesA natural consequence of the growth in renewable gener-ation is the emergence of a new organized market for ancillary services required to keep the power grid in bal-ance. As carbon limits clamp down on the fossil genera-tion units that have historically been used to help mitigate swings in renewable supply, new technologies such as fast-acting DR are being called upon to the fill the void. Although regulators will always lag behind technology advances, there is movement in key markets throughout the world to open up to a greater diversity of third-party solutions from an equally diverse set of new technologies. The types of ancillary services that microgrids already address internally, but which could be provided externally

to the larger utility grid with the right combination of technology and regulations, include:

Frequency regulation: Contracted with traditional gen-erators, and/or new entrants to correct frequency vari-ations in the operation of the grid. These services are expensive to deliver, and generators, microgrids, battery storage, and renewables providers can participate, depending on the market structure.DR: Automated or manual kilowatt demand load cur-tailment services, contracted and called on by the util-ity or the grid operator.Voltage control: Manages reactive power to maintain the system at an acceptable range of voltage given its operating conditions; this is a service that lasts just seconds. In parts of Europe today, semiopen markets exist for voltage support. Response time, when called upon by grid operators, needs to be fewer than 1 min.Load-following reserves: Especially relevant to vari-able renewable energy generation, these services, typically provided by energy storage, are purchased on a 5-min basis.Spinning reserve: A service to restore generation and load balance; can take anywhere from seconds to almost 10 min.Supplemental reserve: Similar to spinning reserve; typically lasts fewer than 10 min.Replacement reserve: Less urgent service, but also designed to keep grid in balance; typically lasts fewer than 30 min.

Much more work needs to be done to create viable rev-enue streams for provision of these grid services, and many of these services can be provided without a microgrid. At the same time, microgrid deployments help bolster the business case for new DER-focused solutions, of which microgrids will become an increasingly attractive vehicle to bundle up services previously rendered by more conventional means such as gas-fired generators.

PPA Business ModelsThis is the business model that now dominates the U.S. residential and commercial solar PV markets, and, mov-ing forward, is expected to become the primary vehicle for commercial grid-tied microgrid projects. Similar to the energy service performance contract (ESPC) described previously, there are no upfront costs for the customer. In the case of solar PV, deep private-sector pockets own the hardware and lease out the systems until all tax credits and accelerated depreciation is maxi-mized. Some vendors in the commercial space are now moving forward with PPAs for microgrids, taking on the risk of performance in exchange for capturing revenue streams from ancillary service sales.

For this business model to work, the network controls element needs to use a streamlined and open architecture, limiting customized engineering costs as new hardware is added to the microgrid over time. Performance also

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needs to be monitored closely. For example, PPA solar projects outperform those installed by smaller contrac-tors since the financial success of these PPA projects hinges on good design, installation, and maintenance. Given that microgrids are much more complex than a simple solar PV system, companies willing to enter into long-term PPAs must be smart about risk and choose suppliers wisely, favoring simple, elegant controls that do not require ongoing customized engineering every time a new resource is integrated into the microgrid.

One of the most interesting vendors pursuing the PPAbusiness model is Green Energy Corporation, which merged with Horizon Energy in 2013. The two firms’ pre-merger shared an affinity for a “software as service” con-cept for microgrids and committed to an open-source controls platform.

The vast majority of microgrids tracked in Navigant Research’s Microgrid Deployment Tracker database are either funded by government agencies or academic insti-tutions as R&D projects or by the asset owners them-selves. The newly expanded Green Energy Corporation is instead serving as an integrator/developer, absorbing any risk of performance of the microgrid, while taking care of the financing. The combined company claims in excess of 15 projects on the drawing board, with four projects completed and one 11-MW project in Connecticut under current development that incorporates diesel, CHP, solar PV, small wind, and advanced energy storage, and which saves a significant amount of money in the long run.

Another company pursuing the PPA model is Leidos, a spin-off of SAIC, a Fortune 500 company. Leidos can

design, build, and help finance microgrids. Notably, it is among the most creative of the prequalified U.S. Depart-ment of Defense contractors when it comes to thinking through how microgrids can gain traction as vehicles for a broad array of services through PPA third-party financing schemes, focused on projects with low-cost natural gas base load deployments. The company believes the best way to create economic value via microgrids is to focus on base load generation, limit energy storage costs, and cap-ture new revenue streams with the greatest value embed-ded in thermal energy. Leidos sees microgrids as platforms for offering a full range of services—electricity, thermal energy, water, waste, and communications servic-es—a big picture vision. The company is also exploring how utilities can be willing partners in microgrids, espe-cially multiparcel C&I projects. Figure 3 shows how the company views a bundled PPA microgrid opportunity delivering on a variety of value propositions: better reli-ability, improved cost, improved sustainability, and enhanced security.

BiographyPeter Asmus ([email protected]) is a principal research analyst with Navigant Research and is a leading global authority on microgrids and virtual power plants. He has more than 25 of years experience as an analyst, con-sultant, and writer, having authored four books on energy and environmental topics.

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Figure 3. The financial model of an energy solution funded by a blended PPA structure. (Source: Navigant Research.)

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2325-5987/14/$31.00©2014IEEEIEEE Electr i f icat ion Magazine / MARCH 201420

NERGY, A CRITICAL INFRASTRUCTURE, FORMS A VITAL INPUT, ESPECIALLYin emerging countries like India. At present, the centralized grid-based elec-tricity is considered the most convenient and reliable form of energy for con-sumers but is unable to keep pace with the growing demand, which requires 100% reliability for a digital economy. With more than 1.3 billion people who

still have no access to modern forms of energy, this inability to meet consumer demand affects the energy security of the country at national and consumer levels. There is a need to consider augmentative mechanisms for bridging the demand–supply gap such that they meet the varying needs of different types of consumers in an effective and efficient way. Microgrids are poised to become the best augmenting technology to address these needs.

This article explains the need for the redefinition of microgrids in the context of emerging economies and sustainable development. The feasibility of different types of microgrids appli-cable in an emerging economy context is presented as case studies and lessons learned along with the potential barriers for implementation. We also demonstrate how microgrids can be a leapfrogging technology, given the energy landscape of emerging economies, as it is a value-based paradigm that caters to the varying needs of different stakeholders.

Energy Landscape of India and Emerging CountriesEnergy forms a vital input and critical infrastructure for the economic development of countries and for improving quality of life. The focus across the world has been to enable better access and use of modern energy sources to ensure increased productivity, better livelihoods, and a higher standard of living. This translates into a growing demand for energy and energy services. Some of the key drivers shaping the increasing demand and state of the global energy supply in the 21st century are population growth; economic and social development resulting in an increase in individual expectation for energy; financial and institutional conditions; local, regional, and global environmental concerns; efficiency of energy supply and use; technological innovation and deployment; dependency on fossil


By Kumudhini Ravindra, Balaraman Kannan, and Nagaraja Ramappa

Microgrids:A Value-Based

ParadigmThe need for the redefinition of microgrids.

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© CREATAS

fuels and their limited availability; climate change and its relation to energy supply; and access to mod-ern energy in the developing world.

It is often viewed that meeting the demands of con-sumers is the key to progress. Emerging economies have not been able to keep up with the rising demand because of existing supply shortages and other structur-al issues. In this regard, decisions taken in terms of the choice of supply resources, technology, site selection, operations and maintenance, and safety measures have a considerable impact on energy systems and on society. Individuals, communities, and also nations are rendered more or less vulnerable to systemic and environmental changes by such decisions. Given this situation, energy demand–supply matching takes on a strategic and sub-stantial role in ensuring the growth and development of a country.

Issues with Traditional SolutionsTraditional demand–supply matching has been achieved by increasing supply centrally. The motivation for this choice is that centralized grid-based electricity is per-ceived to be the most convenient, safe, efficient, and reli-able form of energy for consumers and communities across the globe. The advantage of centralized grid-based systems is that they capitalize on the economies of scale, which is the focus of policy makers and power utilities. These systems are amenable to the top–down policy-mak-ing framework exercised by most decision makers with the standardized management structure. They are con-sidered to have higher quality standards, and most of the innovations and R&D are also directed toward developing bigger and better systems with technology push strate-gies driving the decision-making process.

Energy systems in emerging economies and devel-oping countries are plagued by problems, such as the poor performance of the power sector and traditional fuels, the transition from traditional to modern econo-mies, and structural deficiencies in society and the economy. The growing demand for energy in these countries is not being adequately met by the central-ized systems. A significant gap exists between the energy supplied by the utilities and the energy demanded by consumers. Since increasing supply cen-trally requires high lead times, load shedding (load shedding is the manual cutting off of electric power to any locality by the utility due to power shortage) and planned and unplanned brownouts are the response used by power utilities to secure the grid and deal with the shortage of energy supply in the short term. This

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response impacts the activities of consumers and entails economic losses.

For example, India, an emerging economy with 17% of the world’s population, ranking second after China, only ranks fifth in the world in total energy consumption. India has been investing heavily in centralized power systems to meet its growing demand for energy, but it faces the criti-cal challenge of meeting a rapidly increasing demand for energy. The estimated peak shortage is about 10% across the country, and this figure is rising despite attempts to increase generation capacity. Also, the opera-tional efficiency of the power system is low given the high aggregate techni-cal and commercial (AT&C) losses (in the range of 30–40%). Therefore, utili-ties in India resort to load shedding in the short term to deal with energy shortages. The consumers connected to the grid have to invest in expensive backup systems to ensure acceptable power quality and reliability (PQR). Apart from the shortage in power, according to International Energy Agency estimates, more than 400 million Indians are with-out access to electricity or modern forms of energy.

The issues with centralized grid-based power systems for demand–supply matching are:

Centralized power systems are capital intensive and have long gestation periods. Difficulties in attracting such capital for energy investments impede economic development, especially in less developed countries. There is a fair amount of inertia with regard to the rate of change that can be introduced in the energy system. Decisions on centralized power plants are delinked from social and environmental aspects. There is an excessive focus on technology and economic aspects in the decision making rather than on resources and their availability.Centralized power systems are considered to be highly efficient. However, it can be shown that, for certain end uses, it may be more efficient to use local energy resources than grid-based electricity when the overall efficiency of the energy chain is considered.The dependence on external sources and imports increases the vulnerability of the dependent regions and nations to geopolitics and reduction in energy security. Rising energy prices for energy imports can lead to skyrocketing import bills, with adverse conse-quences for business, employment, and social welfare.The relationship between the cost of the system and PQR is exponential in nature. To improve PQR, redun-dancy needs to be introduced into the power system. There is an increasing order of magnitude of costs for every percentage point improvement in reliability.

Furthermore, utilities are often economically delinked from the demand side. Policy makers being supply and grid focused implies a lacuna in their understanding of consumer needs. The social and environmental impact of individual choices remains unknown. Engineering solu-tions are preferred to social solutions. Centralized power plants do not ensure access, affordability, and energy

security at the individual consumer and community level. On the micro-economic level, per-unit energy prices influence consumer choices and behavior, and this can affect macro-economic development and growth.

All of the above factors suggest the need to invest in additional systems that can adequately plug the existing demand–supply gaps and also provide access to modern energy to the mil-lions who are dependent on outmoded forms of energy.

Stakeholder NeedsDemand–supply matching of energy and power is not just a technical prob-lem as often perceived. It requires an

understanding of the intricate nature of the energy system at the economic, social, and environmental levels. The deci-sion is one of choosing between an optimal solution or a sat-isfying solution, an organic or an inorganic growth model, and an inclusive or an exclusive decision. It is about acknowledging individual consumers and communities as a significant part of the system with entitlements, rights, and duties and that the power system exists to serve their needs. All of this calls for a paradigm shift. Strengthening commu-nities to be self-sufficient or at least less dependent on grid power for their reliability would reduce vulnerability and adverse impacts on the economy, society, and the environ-ment. From this perspective, if one were to define the needs of energy consumers, it is for sustainable energy systems.

Sustainable energy systems imply:reliable and secure availability of quality power to all consumersmeeting the legitimate energy demands of all sections of the present and future generations at affordable prices with the least effect on the environmentenergy conservation using effective supply- and demand-side managementgeneration by using clean and renewable energy sourcesefficient handling and balancing of the conflicting equity, environment, and economy objectives under different spectral, spatial, and temporal conditions.

While making decisions, stakeholders have to consid-er the additional costs of the different sources of energy: logistics, safety, storage, and environmental costs. It is important to return to the basics of power generation and

Microgrids are not just a stopgap solution for matching demand and supply in emerging economies and enabling access to modern energy.

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storage technologies. Any decision made on energy has to be techno-economic from the first principles. The chal-lenge here is to identify which is the best solution. This implies that modeling and design of both centralized power systems and decentralized power systems must essentially be considered as a transportation prob-lem, where the tradeoff is between transmission of electricity and trans-port of fuel for energy needs. The choice is 1) between whether one invests in storage of the fuel (natural gas, coal, diesel, and biomass) or stor-age of electricity, which is the trans-mission medium; 2) how and from where this fuel is obtained; and 3) the logistics of transporting fuel versus the logistics of transmitting electrici-ty. These decisions also have to con-sider the environmental costs of designing the optimal systems.

In this regard, microgrids using renewable and clean energy resources and demand-side management are suitable decentralized alternatives to augment the centralized grid-based systems and enable demand–supply matching at the consumer and community level.

Microgrids and Their DefinitionThe last decade has seen an increased focus on microgrids. The current definitions of microgrids are as follows:

Microgrids, as first defined by Lasseter (2002) and later by Hatziargyriou et al. (2007), comprise a low-voltage(≈≤1 kV) or medium-voltage (usually ≈1–69 kV) locally controlled cluster of distributed energy resources that behave, from the grid’s perspective, as a single produc-er or load both electrically and in energy markets.A microgrid, as defined by the smart grid association, is an electrical system that includes multiple loads and distributed energy resources that can be operated in parallel with the broader utility grid or as an electri-cal island.The U.S. Department of Energy’s (DOE’s) official defi-nition of a microgrid is “a group of interconnected loads and distributed energy resources within clearly defined electrical boundaries that acts as a single controllable entity with respect to the grid (and can) connect and disconnect from the grid to enable it to operate in both grid-connected or island mode.” The microgrid includes integration and control of multiple local generation and storage assets [diesel generators, combustion turbines, photovoltaic (PV) arrays, battery systems, among others] to provide on-site generation for local loads in both grid-tied and islanded modes of operation.

Thus, microgrids are being predominantly seen as 1) an off-grid solution to improving access to remote areas, 2) a mechanism for locally improving the PQR of a specific consumer/area, 3) as a means of better control for the

combination of different distributed energy resources connected to the grid from a grid perspective, and 4) a means of operating in an islanded mode in case of grid failure when connected to the grid. All of these are true, but microgrids can be much more in the context of emerging economies, such as in India and some countries in Africa, where power systems have hardly made a dent in the economics of the region. Microgrids can be suitably designed to meet such needs as access to modern energy, energy indepen-dence, local resource utilization, specific consumer end-use require-ments, livelihood generation, PQRrequirements, sustainable develop-ment, and their combinations.

Furthermore, looking into defini-tions wherein microgrids constitute even liquid fuel generators and fossil

fuel sources if they are located at the consumer side of the grid make one feel that the microgrid is not a new con-cept. Historically, grids developed as isolated systems that were managed and controlled locally. These too could be viewed as microgrids.

The beginning of the 21st century heralded new situa-tions: global wars, susceptibility to terrorist attacks, energy security issues, and the breakdown of the grids at impor-tant junctures, all demanding a new thought process. These situations challenged the existing worldview of “bigger is better.” Suddenly having large power plants and extensive interconnected grids did not seem like such a smart move at all. Thinking began to shift toward smarter grids. Grids that were able to self heal, operate in islanded modes, and take advantage of the information and communication technologies (ICT) revolution became the favorite topic of academicians across the globe. In all of this, microgrids were touted as offering the potential of better control and management at the low-voltage level. It was like transition-ing back into the era of the small, isolated grids of yester-year. The novelty was in the communications and information technology piece of the system and access to renewable energy resources.

Looking into the above discussion, and given the need for moving away from greenhouse gas- (GHG-) intense systems to clean sources, we need to reexamine what constitutes a distributed energy system or microgrid. All of these con-siderations call for a redefinition of the microgrid based on the context.

Strengthening communities to be self-sufficient or at least less dependent on grid power for their reliability would reduce vulnerability and adverse impacts on the economy, society, and the environment.

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With the foregoing discussion and given the global context, microgrids can be defined as “a group of intercon-nected loads and distributed energy resources within clearly defined boundaries that acts as a single controlla-ble entity

designed on the basis of the local consumer’s or com-munities’ energy needs and end uses, where the loads and energy uses are qualified and segregated based on their reliability requirementsthat optimally matches these end uses and locally available clean environmentally friendly energy resources without the need for transporting the fuel, with or without the gridthat may or may not be connected to the centralized gridthat can connect and disconnect from the grid to enable it to operate in both grid-connected or island-mode (if it is connected to the grid)that can communicate with the grid using ICT and enable demand response.”

Microgrids for Emerging EconomiesThe traditional use of microgrids in emerging economies is to provide power to communities, specifically in times of emergency, and to supplement the main grid in times of peak usage or grid unavailability. Here, microgrids are still a norm, with every commercial establishment and closed residential community opting for backup systems

that are coordinated with the operations of the grid to ensure reliable access to power the essential services.

Microgrid choice in emerging economies depends on central grid power availability, the energy security needs of the region, and, at consumer levels, local conditions, technoeconomic efficiency requirements, power quality, and reliability requirements in the context of environmentally sustainable development. The growth perspectives are toward expanding reach of power into off-grid areas, manag-ing growth of existing systems, and transforming growth of the new regions. The main drivers are highlighted in Figure 1.

Taxonomy of Microgrids for Emerging EconomiesMicrogrids are the power systems configuration providing clear economic and environmental benefits compared to expansion of legacy modern power systems. The taxono-my of the types of microgrids suitable for emerging mar-kets are:

1) Energy independence model: focuses on independence from the centralized grid typically in areas that are remote or off the grid.

2) Resource-based model: the emphasis is to maximize usage of locally available resources such as solar, microhydel, wind, and other naturally available energy resources.

3) End-use-focused model: considers the energy end uses of communities, such as illumination, cooking, and

Microgrid Drivers for Emerging Economies

StakeholderNeeds

Consumer

Energy Security Techno-EconomicEfficiency

Power Quality andReliabilty

Cost

Participation inDecision Making

Specific EnergyEnd-Use Needs

Utility

Better Reliability

More “Smartness”(Lower AT&C Losses)

Better ControlOperations andManagement

Government(Society)

Energy Security

Local EmploymentGeneration

Governance

Access to ModernEnergy

Cleaner GreenerSolutions

Long-TermSustainability

Local Conditions

Grid Availability

ResourceAvailability

TechnologyAvailability

Figure 1. The microgrid drivers for emerging economies.

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water pumping, as the main criteria for the selection of the appropriate resources.

4) Livelihood model: can be a means for improving the livelihoods of poor commu-nities by providing opportunities for increasing the skill base of individuals.

5) PQR-based microgrids: the traditional microgrids that enable local definition of PQR requirements and are designed for the same.

6) Environment focused model: can be used for addressing environmental issues at the community level, targeting the carbon cred-its and GHG certificates.

Microgrids can also be designed for more than one purpose in which case a combination of the above models can be used.

Case Studies of Successful Microgrids Based on the Above TaxonomyFor countries like India, where, according to International Energy Agency estimates, more than 400 million people are without access to electricity, microgrids may be the next best alter-native and can coexist with central-ized grid systems. An example of such a microgrid is that developed by Greenpeace India in Bihar (Figure 2). The rural electrification microgrid project is based in the Dharnai Village in the Jahanabad district of Bihar. This solar-based technology model will have about 100 kW of solar panels that supply round-the-clock electrici-ty to 350 households in Dharnai on an affordable and sustainable basis. The microgrid is targeted to become operational by 2014.

Similar off-grid microgrid projects based on microhydro-systems have been successfully installed in the western coastal regions of India by Prakruti Hydro Labs (Figure 3).

Lessons Learned: Microgrids benefit all sections of the society, facilitating people’s access to modern energy resources and removing inequity in energy access. They empower people by allowing them a stake in their energy generation and distribution. This is the future of energy investment.

Globally more than 1.3 billion people are without access to electricity, and 2.7 billion people are without clean cooking facilities. More than 95% of these people are either in sub-Saharan Africa or developing Asia, and 84% are in rural areas. Microgrids, due to their proximity to the consumer and the ability to use process heat, have the potential to address specific end-use needs such as illumi-nation and cooking.

A case in point is the microgrid implementation in the Sagar Islands in the Sundarbans. Several solar initiatives,

wind-based systems, and biogas systems have been installed in this remote area to meet the energy needs of the consumers. The Sagar Islands’ 11 solar stations can each

produce between 25 and 100 kW, total-ing close to 800 kW distributed via power lines 2–3 km long. They supply 1,400 households and commercial establishments. The generation cost is about Rs 10 (US$0.20) per unit (1 kWh), which is then sold for Rs 7, and the difference of Rs 3 is borne by the government.

Lessons Learned: The sustainable and scalable solution to provide renewable electricity to the remote Sundarbans has led to some mean-

ingful cost savings, engaging the rural community in an energy-independent framework, and demonstrated the possibility of a path to zero kerosene. The use of

Figure 2. Greenpeace India’s solar project in Bihar. (Photo courtesy of Power Engi-neering International and Greenpeace India.)

Demand–supplymatching of energy and power is not just a technical problem as often perceived.

Figure 3. A microhydel in the western coastal district of India. (Photo courtesy of Prackruti Hydro.)

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kerosene and biomass in traditional ways have direct impacts on global warming. The success of this pilot proj-ect and multifaceted benefits enable larger-scale deploy-ments of solar energy units in the Sundarban region.

Microgrids can also address the livelihood issues of com-munities as demonstrated by the Gram Power microgrids and Gram Vikas Biogas-based systems. These microgrids aim to provide reliable, affordable power to the 2.7 billion world poor living without it. They also help skill building and ensure sustainable livelihoods in rural households.

Gram Power was involved in setting up India’s first solar-powered smart microgrid in the Rajasthan hamlet of Khareda Lakshmipura in March 2012, providing energy for rural households. Gram Power’s core innovation is their smart distribution technology with smart meters and grid monitoring systems to provide on-demand, theft-proof power with a unique pay-as-you-use schedule that is determined by the end user. The Gram Power systems enable local village entrepreneurs to purchase bulk energy credits from Gram Power and transfer them to individual smart meters in the village. Once recharged, the meters can be used to operate a variety of household appliances and other devices. Importantly, Gram Power’s microgrids can be integrated with the utility grid.

Gram Vikas is an Indian nongov-ernmental organization based in Oris-sa and founded in 1979. Gram Vikas works on creating livelihood-enabling infrastructure and renewable energy systems. The organization actively implements community-based renew-able energy programs using biodiesel, biogas, microhydro, smokeless chullas, and solar PV applications to provide energy access to rural households.

The Biomass Energy for Rural India Project, sponsored by the global environmental facility United Nations Devel-opment Program, India-Canada Environmental Facility (GEF-UNDP, ICEF), the Government of India, and the Gov-ernment of Karnataka, a 500-kW biomass power plant established near Kabbigere village in Thovinkere Gram Panchayat in the State of Karnataka, is another initiative with an aim of implementing a decentralized bioenergy technology for rural India. It uses locally available biomass to supply a high-quality, reliable power supply at a reason-able price. The project also provides tradable water rights to landless households that are equivalent to those held by land-holding members of the village, along with creat-ing employment, improving agro and village industries, and improving the livelihood of the people. Although the success of these types of projects depends on the various stakeholders, the main objective and spirit can be replicat-ed in rural areas.

Lessons Learned: Microgrids can be suitable mecha-nisms for improving the livelihoods of individuals, and new business models developed for microgrids can enable the growth of enterprises even in rural and remote areas,

as shown in Figure 4.Microgrids can also be designed

keeping in mind the type of consum-er using the system. Echelon and Valence Energy’s microgrid system for an apartment complex, Palm Mead-ows in Hyderabad, India, is designed to integrate distributed generation to compensate for disruptions in utility-supplied power. Palm Meadows is an 86-acre integrated gated community with 335 homes and residential ser-

vices. The Palm Meadows community gets its bulk power supply from a dedicated grid substation from the utility. In

(a) (b)

Figure 4. The improvement in livelihood as seen in the Sundarban Islands. (a) Solar street lamps. (b) Women empowerment through battery-backed solar power. (Photos courtesy of Subhendu Ghosh/HT Photo.)

Centralized power systems are capital intensive and have long gestation periods.

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case of a disruption in the grid supply, the community uses diesel generators for their needs as a distributed unit and will incorporate solar generation in the future. Resi-dences within the community are equipped with smart meters that connect into data concentrators at distribu-tion transformers and feed near real-time usage informa-tion to their energy system software.

Lessons Learned: Smart microgrids are an ideal way to integrate distributed generation at the community level and allow for customer participation in the elec-tricity enterprise. In this case, microgrids can act as an aggregation and optimization platform to extract the most value out of existing and new distributed energy assets, such as small wind generation and solar PV cou-pled with smart meters. They are also the building blocks of a smart grid whose modularity can reduce energy consumption by 10–15% through more intelli-gent networking.

Microgrids can also help engage in environmental sustainability initia-tives. Wipro’s Green Leaf Initiative, an Intelligent Automated Power Manage-ment, which identifies power savings, measures carbon reductions and the implementation of customer organiza-tions’ green goals, enables cleaner usage of its microgrid system, and targets savings of up to 30% of normal-ized energy costs, is one such example. Also, to achieve its ecological targets as part of its sustainability initiative, Wipro attempts to minimize its internal foot-print on energy, water, and waste. This is accomplished by incorporating 19% renewable energy into the energy portfolio and the use of energy-efficient measures. About 63 million kWh are pro-cured from renewable energy via rooftop solar PV at three campuses, and canteen food waste is converted into biogas and used as a source of cooking fuel, helping to avoid 100 tons of GHGs annually.

Lessons Learned: Microgrids can help institutions and communities participate actively in sustainable develop-ment by enabling the use of locally available renewable resources and better energy management.

Given the high loss of load probability (LOLP) in emerg-ing countries, it is a norm for commercial establishments and residential complexes to have expensive backup power systems. These microgrids focus on improved PQR. For example, the information technology enabled services (ITES), hospitality, and health-care industries in India require very high reliability and quality of power. Present-ly, institutions from all of these industries have backup with an in-house diesel generator, inverter, storage bat-tery-based system to ensure 24/7 PQR. Such microgrid sys-tems have the ability to work independently of the grid, and the loads are classified and segregated based on their

criticality. However, one has to make a distinction as to whether these are the types of systems that we need to propagate given that most of the backup systems are based on liquid fuel (GHG-intensive fossil fuel).

Lessons Learned: Microgrids have to be redefined in terms of what constitutes one. According to the current definition, liquid-fuel-based backup systems can also be classified as microgrid systems. But whether consumers should invest in such systems requires additional assessment.

Value PropositionMicrogrids, which in a way encapsulate the mindset “small is beautiful,” are much more than a new-age phenomenon. They enable the centralized grid operators and load dis-patch centers to view them as single entities, enabling bet-ter communication and management. The improvement in ICT also enables better control and management of power. Thus, demand response has a greater meaning when used

in conjunction with microgrids. Consumers can play a more active role in defining their needs in such systems.

The value propositions of microgrids, as put forth by the DOE, are 1) reduced cost of energy and better management of price volatil-ity, 2) increased resilience and secu-rity of power delivery, 3) improved reliability and power quality, 4) pro-motion of deployment and inte-gration of energy-efficient and environmentally friendly technolo-gies, 5) assisting in optimizing the power delivery system, including the

provision of services, and 6) service differentiation through different levels of service quality and value to customer segments at different price points.

The additional value propositions of microgrids in emerging economies can be explained from the perspective of LOLP (which is a measure of the reliability of an electrical grid, the probability that there is an insufficient generating supply to support electrical demand) and value of lost load (which is the estimated amount that customers receiving electricity with firm contracts would be willing to pay to avoid a disruption in their electricity service). Microgrids can improve the reliability of the power system locally at the consumer site without significant investment in the utility infrastructure. They improve the PQR of the system and, thus, significantly reduce the LOLP.

The value created by microgrids can be multifold. In terms of technology microgrids improve efficiency, reliabili-ty, access, and affordability and also enable local resource usage. Investing in local microgrids creates employment opportunities and livelihood options as they require addi-tional human capabilities and skills, which in turn requires education/training. This implies an increase in human and

Energy demand–supply matching takes on a strategic and substantial role in ensuring the growth and development of a country.

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social capital creation. Given that microgrids provide access to modern power, there is an increase in the economic cap-ital, including the gross domestic product, FDI, and GNP, of the region. When these systems use clean forms of energy, the natural capital of the regions is protected and improved. From all of these perspectives, it can be said that microgrids are value-enriching systems that have to be supported by all stakeholders.

In addition to improving PQR, mi-crogrids for developing countries like India provide flexibility, increased energy security, and access to mod-ern energy in remote areas. Accord-ing to a market research report published by Markets and Markets, the total market for microgrids is expected to reach a total installed capacity of 15.4 GW by 2022, growing at an estimated compounded annual growth rate (CAGR) of 17% from 2012 to 2022. The expected worth of the market is about US$27 billion. This study, however, only considers re-newable power generation, solar PVs, wind microturbines, battery, energy storage, and control systems from the traditional use of microgrids. Once we consider the other potential types of microgrids as explained earlier, the size of the market will be much larger.

Future of MicrogridsMicrogrids are not just a stopgap solution for matching demand and supply in emerging economies and enabling access to modern energy. In the case of off-grid and remote areas, it is not to be assumed that microgrids will give way to centralized grids if technologies make it possible. Microgrids have to be seen as value-based entities that coexist with the centralized grid. They are potent entities that can operate essential services even in the case of emergencies such as natural calamities, as demonstrated by the Sendai microgrid when the 9.0-magnitude earth-quake struck off the northeastern coast of Japan and trig-gered one of the deadliest tsunamis recorded (http://spectrum.ieee.org/energy/the-smarter-grid/a-microgrid-that-wouldnt-quit) and the San Diego Gas and Electric’s Borrego Springs microgrid during the intense thunder-storms on 6 September 2013 (http://www.utsandiego.com/sponsored/2013/nov/10/sgde-repair-crews-storm/). They can be designed to be smart to incorporate innovative prod-ucts and services together with intelligent monitoring, con-trol, communication, and self-healing technologies. Microgrids can better facilitate the connection and opera-tion of generators of all sizes and technologies, allow con-sumers to play a part in optimal operation of the system, provide consumers with greater information and choice of supply, significantly reduce the environmental impact

of the whole electricity supply system, and deliver enhanced levels of reliability and security of supply at the local level.

Currently, the centralized grids interact with individu-al consumers. This makes demand response and con-sumer inclusion in decision making a difficult proposition. The future architecture of a power system can actually consist of a centralized grids interacting

with a cluster of community-level microgrids. These microgrids with built-in intelligence, local generation facilities, and control mechanisms would be a better option to optimally operate the power system.

Potential Drivers and BarriersNot everything is perfect in the microgrid space. Several challenges and barriers exist for the creation of microgrids. These can be classified into operational, financial, social, tech-nological, governance, sustainability, and business-related issues. These are formulated in Figure 5.

The operational barriers include a lack of standards and options for the different microgrid technologies; acceptability by the industry and public; and operations, maintenance, and upkeep of systems. Some of the technological issues are the availability and maturity of tested and proven microgrid technology for different regions, technical issues such as connection issues (with the central grid), islanding, voltage regulation, and harmonics.

The financial barriers are affordability (consumers’ capacity to pay), cost and pricing models for microgrids, application procedures, exit fees, feed-in tariffs and metering, financing, load retention rates, interconnection, insurance, rate-based return on investment, siting and permitting, skilled labor, and standby fees. The sustain-ability issues are access, affordability, security, and envi-ronmental sustainability-related issues. There is also no clarity on the appropriate business models for the diffu-sion of microgrid technologies.

The social issues are the ignorance of stakeholders, the lack of education of consumers, cultural dimensions in terms of usage of energy technologies, the growing rich–poor divide, and a lack of interest. Governance-related barriers include stakeholder commitment, lack of harmo-ny and trust among the different stakeholders, lack of coordinated efforts by the different stakeholders, lack of accountability, political interference, and lack of regulatory and policy frameworks for implementing microgrids.

Presently, microgrids have only been showcased in test beds and pilot implementations. Models for the large-scale diffusion of technologies do not yet exist. There is no agreement of who does what and how. All of these

A significant gap exists between the energy supplied by the utilities and the energy demanded by consumers in most of the developing countries

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barriers and issues need to be addressed to ensure that microgrid technologies are adopted and suc-cessfully diffused in the markets.

ConclusionThere is enormous potential for set-ting up microgrids, and they can be a value proposition for emerging econo-mies. Several different options in microgrids are possible other than the traditional PQR model being consid-ered in developed countries. Given the differing scenarios and objectives of the various stakeholders, the chal-lenge will be to find suitable microgrid systems that will meet the objectives in a satisfactory way. If a good match is made, microgrids have the makings of a success story and can act as a leapfrogging technology in the energy industries of these countries.

For Further ReadingCentral Electricity Authority. (2013). Growth of electricity sec-

tor in India from 1947 to 2013. [Online]. Available: http://www.

cea.nic.in/

G. Venkataramanan and C. Marnay,

“A larger role for microgrids,” IEEE Power

Energy Mag., vol. 6, no. 3, pp. 78–82, May–

June 2008.

IEA. (2011). Energy for all: Financing

access for the poor. [Online]. Available:

http://www.iea.org/media/weowebsite/

energydevelopment/weo2011_energy_

for_all.pdf

Gram Power. [Online]. Available:http://www.grampower.com

BiographiesKumudhini Ravindra is a researcher involved in several initiatives in the clear energy technology and business analysis domain. She is a Member of the IEEE.

Balaraman Kannan ([email protected]) is the chief general

manager of PRDC in Bangalore, India. He is a Senior Mem-ber of the IEEE.

Nagaraja Ramappa is the managing director of PRDC, Bangalore, India. He is a Senior Member of the IEEE.

The traditional use of microgrids in emerging economies is to provide power to communities, specifically in times of emergency, and to supplement the main grid in times of peak usage or grid unavailability.

MicrogridBarriers

Financial

Affordability(Capacity to

Pay)

Cost andPricing

Proceduresand

Processes

Return onInvestment

Technological

Availability

Connectionto the Grid

Islanding

PowerQuality

Governance

StakeholderCommitment and

Accountability

Lack ofHarmony and

Trust

CoordinatedEfforts

Regulatory andPolicy

Frameworks

Sustainability

Access

Affordability

Security

Ignorance ofStakeholders

Lack of Education ofConsumers

CulturalDimensions

BusinessRelated

Clarity ofBusinessModels

Diffusionof Models

MicrogridOptions

Operations,Maintenance,and Upkeep of

System

Acceptabilityby Industry and

Public

Operational

Standards

Social

Rich-PoorDivide

Figure 5. Microgrid barriers.

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MICROGRID PRESENTS A CHALLENGING PACKAGE TO finance. The primary difficulty arises from the fact that a microgrid is not just one type of asset but rather a portfo-lio of assets that represent different value streams, tech-nology risks, and depreciation lives.

A microgrid includes generation, a distribution system, consumption, and often storage. The system is integrated and managed with advanced monitoring, control, and automation systems. Many microgrids will have almost 20–25% of their on-site generation from renewable technologies, often integrated with thermal energy storage and electric battery storage. Government incentives for energy efficiency, renewable power genera-tion, and electric infrastructure all might qualify for an investment stim-ulus for advanced energy infrastructure.

In addition to this array of factors, the implementation of a microgrid rarely occurs as one project and a common project investment. Instead, the value proposition of the microgrid evolves over multiple phases, cen-tered on demand and consumption reduction, on-site generation and storage, advanced control systems, and automatic grid independence. Each phase is not completely distinct from the others, and each phase


Emerging Models for Microgrid Finance

Driven by the need to deliver value to end users.

By Michael T. Burr, Michael J. Zimmer, Guy Warner, Brian Meloy, James Bertrand, Walter Levesque, and John D. McDonald

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does not have to be implemented in a rigid sequence. Often phases overlap, and newer tech-nologies might be considered later in the life cycle of the project.

Not all phases or assets will qualify for incen-tives or grants, and the overall capital invest-ment is substantial. The simple payback calculation might exceed 15 years. However, eco-nomic considerations are not the sole factors for investors or end users. Some are mostly interest-ed in resilient, reliable, and secure power; physi-cal and cybersecurity; planned transformation and growth; regional and sector benefits; tech-nology advancement and demonstration; envi-ronmental strategies; emission reductions; or some combination of value drivers, although all will include financial considerations. All such investments will be driven by the need to deliver value for end users.

Starting from that premise, securing affordable financing for a microgrid project depends first on clearly defining value drivers and seeking opportu-nities to improve the cost-benefit attributes of microgrid solutions and architecture while con-forming to project schedules that satisfy custom-ers’ requirements. The strongest business propositions will likely depend on the cost-effec-tive deployment of energy management systems, efficiency measures, and demand response (DR) technologies to minimize capital costs and operat-ing expenses. Efforts to reduce consumption of fuel, electricity, water, and other resources offer quicker payback and higher returns on investment (ROI) and can be compounded with simple DR pro-grams to further improve ROI.

As project sponsors and host customers seek to develop and finance cost-effective microgrid systems, they face a range of variables that change over time, from customer requirements to long-range trends in utility market structures. This article, adapted from Minnesota Microgrids, the final report in a 2013 study performed for the Minnesota Department of Commerce (see Burr et al.), seeks to address those issues as they relate to microgrid development and financing. While some examples and details are drawn from Min-nesota—a state in the U.S. upper midwest with a well-developed and mostly reliable utility

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system—the parameters of analysis apply to many loca-tions that have similar market characteristics.

Customer Needs and ApplicationsA variety of applications offer the potential for microgrid develop-ment, and each offers different options for project structuring and financing.

For example, customer groups in the military, universities, schools, and hospitals (MUSH) category, and other customers with a similar scale and attributes, have special needs for reliability and security and are willing to accept longer paybacks over an extended period. They include facilities that are considered critical for community services and, therefore, merit investment for stronger energy assurance. Such customers also might be interested in a range of values and benefits, including local economic development, as opposed to requiring only a bare financial calculus to drive their investment decisions. Finally, they might improve microgrid financing options by providing access to funding sources and structures inaccessible to strictly commercial projects.

Commercial and industrial customers also offer inter-esting possibilities for microgrid development, especially in cases where requirements for high resilience carry a high-value premium. In one microgrid example discussed in the Minnesota Microgrids report, the Treasure Island Resort and Casino places a high premium on resilience because its primary source of revenue, gambling, is entirely dependent on stable and reliable electricity. Such a customer also values the worry-free, turnkey nature of a third-party-managed microgrid and, thus, is well prepared to engage in a long-term contract arrangement for its full scope of utility services.

A third possible arrangement, although perhaps more complicated, offers interesting prospects for microgrid development: the cluster or community microgrid devel-oped through a special economic development or energy improvement district (EID) structure, perhaps in coopera-tion with a municipality. Such a cluster approach can combine a range of synergistic values and benefits, and maximize the utilization of generation resources by diver-sifying load profiles and criticality attributes. In some cases, it might be developed around a core asset, such as a combined heat and power (CHP) plant installed to replace an aging boiler that must be shut down to meet Clean Air Act regulations. A project of this type could deliver an attractive energy cost proposition while also capturing tangible incremental benefits such as tax-advantaged

municipal bond financing, renewable energy incentives, and technology and economic development grants and

loan guarantees.In one recent example, District

Energy St. Paul—a public–private part-nership that serves 100 buildings in downtown St. Paul, Minnesota, with district heating and cooling services—commissioned a study to explore the potential for combining resources and needs for energy planning in the Green Line light rail corridor. The study included development of a prefeasibility methodology, which was intended in part to help other system planners assess options and pursue opportunities for EID projects.

DBOOT Project Finance ApproachesMultiple financing options can be used or adapted to design, build, own, oper-ate, and transfer (DBOOT) microgrids

in exchange for agreements to purchase energy products and services. A financing framework for microgrid projects will focus on the following issues initially:

What is the best way to fund the early-stage microgrid designs and ownership and operating structure to secure project financing and attract third-party capital?Can lessons from public–private partnerships, bond financing, and infrastructure banks apply to strategies for microgrid funding?How should corporate finance and accounting practices treat microgrid assets, revenues, and service agreements? Do state or municipal governments have a role in entering or supporting long-term microgrid service contracts?Might an investor-owned utility acquire microgrids or their components as regulated rate-base assets or unregulated investments? Might cooperative or public power utilities support microgrid projects or contrib-ute infrastructure or services on behalf of their mem-bers/customers?What role might Property Assessed Clean Energy (PACE) 2.0 financing play in funding microgrid invest-ments for commercial purposes?What project structures will facilitate access to capital and credit enhancement?What roles will be played by various developers, engi-neering and construction firms, and vendors of equip-ment and services?

For the purposes of this analysis, a hypothetical microgrid project finance company will be a limited partnership (LP) or limited liability company (LLC) established by a developer to secure debt and equity financing needed to design and own

Multiple financing options can beused or adaptedto design, build, own, operate, and transfer microgrids in exchange for agreements to purchase energy products and services.

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the microgrid. Energy project development companies will likely contribute the equity investment necessary to com-plete the design of the microgrids and act as the general partner of an LP or company. Under this approach, microgrid end users—if other than the equity partner(s)—would pay little or no capital costs toward the development of the microgrid. The experience of the developer and its partners will be pivotal to attracting third-party capital.

A significant benefit of a DBOOT approach is that the LP or company can earn significant tax benefits that are not available to entities such as municipalities, special dis-tricts, and nonprofit and other government bodies that are not tax-paying entities. Businesses within the community can be offered options and assume roles as invest-ment partners in the LP or company and thereby earn federal tax incen-tives to lower their investment costs.

Under the DBOOT approach, ener-gy users served by a microgrid would enter into an Energy Services Agree-ment (ESA) with the company to pay charges for electric, heating, and cool-ing services, and to manage efficiency and DR measures. The ESA can have a term of up to 20 years and allow the LP or company that financed the microgrid to recover capital costs and expenditures for construction of the microgrid. After payback to the com-pany, sole ownership of the microgrid asset could transfer and vest to the end users in its entirety.

The company might guarantee that the ESA service charges would be no higher than the same rates that the energy users would have paid without the microgrid. Such charges could include costs to obtain qualitative benefits from the microgrid beyond bare costs for energy supply. This would guarantee that energy users in the microgrid never pay more than utility rates and other costs they would incur for the same set of benefits, but in the ESA, it does not limit the possibility that they would pay less. Atrue-up could be used annually, and any savings from actual costs would be shared among the company and the microgrid’s energy users.

Utility Models for FinancingUtility grid models have been evolving since the enact-ment of the Public Utility Regulatory Policies Act in 1978 and its implementation by the Federal Energy Regulatory Commission and the states by 1982. Technology advances have gradually affected the utility system, increasing opportunities for development and operation by nonutility stakeholders. Now technology is creating opportunities in electricity distribution.

Safe interconnection can occur using standardized and proven systems and procedures, fostering a new

technology revolution with microgrids. Ultimately, a change in distribution company business models could be fostered by these developments integrated with technolo-gy. These evolutionary trends resemble the changes and transformation that happened when decentralized tele-communications, information processing technologies, and cloud computing merged. Just as the telecom industry transformation led to the emergence of new service mod-els and a wave of investment in infrastructure, the indus-try’s evolution toward a more distributed model will bring new investment and business opportunities.

The effects on legacy central utility models might lead to utility stranded asset compensation claims. Theories of stranded cost recovery could appear at the state level for distribution assets, which could impose a chilling effect on the devel-opment of microgrids and distributed energy resources (DERs) in general if they prompt policy makers to reduce existing support for the increasingly distributed architecture of the power grid or even to erect additional regula-tory barriers and limits.

Additionally, however, utility companies will have new opportu-nities to earn returns—regulated or unregulated—on distribution assets serving independently managed microgrids. This precedent exists

where utilities earn a regulated rate of return on transmis-sion assets already in the utility’s rate base but indepen-dently managed by the regional transmission organization or independent system operators. In other cases, utilities’ unregulated affiliates earn revenues on nonutility assets, including independent power producers and merchant transmission systems.

In some cases, regulated utilities might initiate or par-ticipate in microgrid development. As in Connnecticut Light & Power’s participation in the Hartford Parkville Clus-ter microgrid, San Diego Gas & Electric’s Borrego Springs demonstration project, and initiatives at Duke Energy to develop neighborhood-level microgrid architectures, utili-ties might continue earning regulated rates of return on existing distribution assets used in a microgrid project as well as incremental revenue streams—regulated and unregulated—on additional related investments.

In some cases, environmental compliance obligations will necessitate replacing aging boilers, creating opportu-nities for utilities to participate and contribute toward optimizing new plants or repowering investments with integrated microgrid solutions. In other cases, load pock-ets requiring new transmission service might be better served with localized resources, of which microgrids or microgrid-type load-management and distributed genera-tion (DG) models might prove to be more effective.

Safe interconnection can occur using standardized and proven systems and procedures, fostering a new technology revolution with microgrids.

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For such projects, the utility could partner and operate or manage microgrid control systems. The utility’s role could be important in a campus microgrid, where microgrid wires or pipes serving a single campus cross a public right of way or other demarcation line in the utility franchise. The utility’s participation would also help reduce barriers encouraging previously unaffiliated customers to voluntarily join the microgrid for service by contract.

Joint ownership or cooperative structures could collectively own and operate a microgrid, and they could grow to add other customers. In each case, utilities could play a key role in making microgrids more cost effective by ensuring that they are planned and developed as part of the integrated distribution system. Moreover, utilities with investment-grade credit ratings and deep balance sheets would bring easier access to low-cost financing, making them logical partners in microgrid projects.

Other physical microgrid models or structures might emerge as they have already in some locations. Eventually, microgrids might be structured to also connect with each other and with other distributed resources. In such scenarios, a common pooled resource would emerge—i.e., a virtual power plant.

At this stage, no single party would own the network business or control the market’s growth and direction; an Internet-style model would emerge that would be federally regulated, if regional, or state regulated within the boundaries of a single distribution company. But ener-gy sale and purchase transactions could occur outside of the rate-regulated utility framework.

The ownership role of incumbent utility companies in such a scenario still bears scrutiny and remains to be determined. In the short- and medium-term future, utili-ties occupy a strong position as effectively sole providers of retail electric and gas services, but creeping disinterme-diation and new technology options will erode that posi-tion over time. Whatever the market structure and regulatory model, utilities increasingly will be forced to compete with other types of service providers, including consumer services companies in IT, cable TV, telecommu-nications, financial, independent power, energy technolo-gy, and related industries that offer more innovative solutions and that demonstrate a better ability to assume entrepreneurial risk than the incumbent utility industry has shown.

To the degree electric utilities choose to focus on pre-serving and protecting a rate-regulated commodity busi-ness with approved pass-through provisions, while other companies are offering enhanced customer service with

new technology options, they could face the prospect of a shrinking role in the market and, therefore, an eroding value proposition. Ultimately, this could lead to higher capital costs as investors shift resources toward compa-nies with more future-proof business models. On the con-

trary, utilities that pursue win-win approaches to exploit emerging technologies and resource opportu-nities, including microgrids, will be better positioned to benefit from those changes rather than be mar-ginalized by them.

Transactive Energy Market ModelsAlongside more sophisticated approaches to energy asset valua-tion and cost recovery, new opera-tional and market models are emerging in the electricity industry with advances in information pro-cessing technology, communication networks, and automated power systems. Collectively, these can be referred to as smart grid technolo-

gy, “big data” analytics, and transactive energy (TE).Utilities in some jurisdictions are applying smart grid

and big data analytics technologies to optimize real-time system performance and guide system planning and investment decisions. These technologies and practices lead toward a future in which system resources can be managed on a more granular, dynamic basis. While those capabilities serve traditional utility operational structures, they also could enable a new market model to emerge in which retail energy consumption and supply decisions are driven by competitive market pricing through a combina-tion of long-term contracts and spot- and forward-market bids and tenders.

Such a TE model could introduce market efficiencies and price transparency into an energy industry hereto-fore characterized by central dispatch methodologies and postage-stamp rate structures. Although those struc-tures historically brought reliable service at affordable prices, their ability to continue doing so is eroding in a market characterized by flat load growth, rising costs, and increasing competitive pressure. TE architects suggest that the transactive market model might be the natural next step in the utility industry’s evolution and, arguably, it would be better suited to allocating the fixed and variable costs of service in an increasingly distribut-ed operating structure.

TE could factor into microgrid planning in two ways. First, microgrids could demonstrate TE models in a micro-cosm, providing the opportunity to test automation and data processing systems and competitive energy market models in real time, and to gauge their ability to manage

The utility’s participation would also help reduce barriers encouraging previously unaffiliated customers to voluntarily join the microgrid for service by contract.

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energy sale and purchase transactions while maintaining reliable service. Second, microgrids and their asset compo-nents could operate as part of a larger TE market, maxi-mizing their cost-effective operation in a larger, deeper pool of resources that also are being traded in real time. Moreover, the TE vision proposes a new electricity market structure that exploits new technology capabilities to enable the cost-effective, market-based deployment of distributed resources while resolving the disin-centives, cross-subsidy concerns, and unintended consequences of disruptive forces.

Specifically, the basic principle of a TE market is for customers and sup-pliers to enter into long-term con-tracts or subscriptions for fixed quantities of electricity services (ener-gy, distribution, and transmission) for fixed payments. Then, automated agents and devices act-ing for customers would buy and sell electricity services as market prices and customer needs change.

TheTE idea is simple, with familiar analogs in wholesale commodities markets, where participants enter long-term contracts to secure commodity supply and transport capac-ity—e.g., natural gas—and then engage in spot-market and forward trades to manage fluctuating needs and price exposure. The TE model is foreign to the utility industry because historically the industry has been designed and operated under a strict central dispatch model with regulat-ed cost-of-service rates.

Market pricing within a central dispatch model has been less than satisfactory, especially in competitive retail markets, largely because end users can only make energy purchase decisions. They cannot sell their energy or capacity—or that ability is severely constrained—leaving market power in the hands of the central dispatcher. Par-ticipation in such central-dispatch markets is complex even for the largest customers.

Also, the TE market model has been impeded in part because storing electricity is expensive, and a key feature of most commodities markets has been the ability to store supply resources. However, the need for storage becomes less important in a system where market resources can be dispatched or curtailed very quickly, virtually in real time; where resources are increasingly modular and distributed; and where information processing power is sufficient to manage the real-time dispatch of localized resources through competitively priced transactions.

TE concepts and standards are being discussed and developed through such organizations as the GridWise Architecture Council, the Harvard Electricity Policy Group, the Open ADR Alliance, the Organization for the Advance-ment of Structured Information Standards, and the Smart Grid Interoperability Panel (SGIP). As such development

continues and TE concepts are demonstrated and deployed in operating energy markets, they might support or complement the emergence of microgrids as efficient systems for deploying and managing resources. And ulti-mately they could offer visionary approaches for trans-

forming regulatory and operational models to exploit the capabilities of new DER technologies.

Microgrid Organizational ModelsGenerally, three types of organization entities are best positioned to finance and govern the microgrid. Other organizational structures will likely follow with supportive federal or state legislation.

EIDsEnergy or special improvement dis-

tricts are organizations with one or more energy users enabled by state and local laws to self-generate and dis-tribute power for both heating and cooling services. The initial customer for a microgrid could choose to be the sole participant in the EID or add other neighboring partic-ipants to optimize microgrid efficiency and capacity utili-zation. The EID is formed for the following reasons:

It enables the initial customer and other participants (if any) to capitalize the microgrid with the same cash flows already allocated for traditional gas and electric service. The initial customer and each EID participant would sign an ESA to purchase a specific quantity of electric, heating, cooling, and energy management services from a microgrid company. This operates much like a performance contract. If structured as an operating lease, the ESA could avoid a liability on the balance sheet.It allows legal access to electric power from both the new microgrid and existing grid sources.It enables low-cost regulation as a municipal or coopera-tive utility.

Private Equity DBOOTIn a private equity DBOOT structure, the company uses private equity funding to design, build, own, operate, and transfer the microgrid. The DBOOT structure enables the participants to monetize federal tax credits, reduce com-munity and energy user exposure to project risk, avoid any liabilities on their books, and add a valuable asset to the community infrastructure once the company achieves payback. Especially when combined with PACE financing, this model offers substantial potential.

Microgrid Operating CompanyA microgrid operating company is commissioned to design, build, and operate the microgrid for the end users

A microgrid could qualify for federal or state tax incentives for certain discrete elements of the project.

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or community under what is effectively a concession or operating agreement. Mechanisms and contracts used in cases 1) and 2) in the “Microgrid Revenues and Expenses” section could also apply in a commissioned microgrid.

Microgrid Revenues and ExpensesThe value stream from microgrids is critical to generating revenues to retire debt service. Two sources of value arise from: 1) the benefits provided by the specific DER applica-tions that are used within a given microgrid and 2) the additional benefits created by the unique attributes and geographic location of the microgrid.

Several potential sources of revenue can be developed

to support adequate cash flow. These revenues, and their integration in firm ESAs, will provide the critical frame-work for accessing third-party capital in microgrid project financing structures.

Planning and building a microgrid will require capital investments, start-up spending, and ongoing expenses. These need to be accurately reflected in modeling. Table 1 outlines several examples of potential microgrid revenue streams and categories of expenses.

Attracting Third-Party CapitalA microgrid could qualify for federal or state tax incentives for certain discrete elements of the project. These include

TABLE 1. Microgrid Revenues, Costs, and Expenses.

Revenue Sources Capital and Development Costs Operating Expenses

A microgrid services fee can be assessed to all participants in the system for its management, operation, and maintenance.

Capital cost for procurement and instal-lation of on-site CHP systems, solar PV arrays, storage capacity, and thermal energy conduits, etc., and their associ-ated rights of way and permits.

Costs of fuel for generation systems, with associated hedging arrangements.

Payments for power and thermal energy sales (especially for CHP systems) can consist of fixed or variable rates per kilowatt hour, shared savings payments, or some combination of the two.

Capital costs and licenses for microgrid energy management and control sys-tems and software.

Operational costs, such as salaries of management and operational employees of the system, expens-es of physical premises of company (rent), and fees for professional advisors to the operator (accoun-tants, attorneys, etc.).

If a customer desires ultrareliable power, it can be provided under a special “ultrareli-ability” tariff as a premium service.

Fees of professional consultants in the development phase, such as engineers, financial advisers, attorneys, permitting specialists, and financial placement firms.

Fees of consultants and subcon-tractors employed to support operation and maintenance of the system.

Payments from building owners for the installation of energy-efficiency measures, such as upgrades of HVAC systems and lighting and installation retrofits, can con-sist of fixed payments for services and shared savings incentives. Grants from state and federal agencies also might be available.

Capital costs of protective relaying needed for interconnection, costs for in-terconnection and transmission studies for connecting microgrid systems to the utility grid, and for possible upgrades to utility substations for standby power and fault protection.

A management fee for the manag-ing general partner or operating manager.

Payments from third-party customers for thermal energy for heating and cooling if they wish to be connected to a district energy system.

Capital cost of equipment needed to implement energy-efficiency measures, such as new boilers, chillers, lighting, and insulation, and fees of service providers.

Standby service rates to be paid to the central grid for providing backup power.

Incentive payments from government agen-cies and private foundations.

A financing fee payable to the managing general partner or operating manager in connection with a successful raising of capital.

Insurance premiums, including for a new insurance product coupled with ultrareliable power covering busi-ness losses in the event of power loss (which is much less likely with reliable on-site generators).

Sales of renewable energy credits, emis-sion allowances, or emission reduction credits where applicable.

Source: Minnesota Microgrids: Opportunities, Barriers, and Pathways Toward Energy Assurance, Figure 4-1, p. 70.

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policy provisions and incentives for renewables, energy effi-ciency, energy storage, demand-side management, and CHP.

A commercial focus to the microgrid opportunity will be appealing to third-party developers because it will provide more effective access to private capital markets for microgrid hosts or government entities. Without such a business orien-tation, effective microgrid development will depend on direct funding by microgrid hosts, such as universities and public agencies, as well as utilities. The host-funding approach will restrict implementation and introduce uncertainties that will constrain microgrid applications. Critical support among a handful of states will also foster better market penetration with access to capital. Minnesota has tools to show leadership for microgrid development.

Critical to financing success will be an understanding of both the costs and sources of economic value that microgrids can provide. Historically, projects offered emergency services and little more. They were not integrated or interconnected with the grid and gener-ally have served only a single facility. Amore modern, integrated microgrid will provide secure sources of power with high levels of quality and reliability through a combination of on-site gener-ation, storage, distribution, and energy management technologies. Microgrids that make the most of each of these val-ues, and exploit the full range of revenue streams and incen-tive opportunities, will be in a better position to attract third-party financing, especially if they consolidate them in easily understood financial analysis.

Moreover, the best financing opportunities might be obtained by combining multiple microgrid projects togeth-er into a portfolio. While an individual microgrid project might be too small to attract interest from private equity and institutional investors, for example, a group of microgrids could achieve the scale needed to raise cost-effective financing—most likely through a secondary-mar-ket transaction after most or all of the assets are operating. Such a microgrid portfolio “YieldCo” could even provide opportunities to raise equity or debt financing in public markets.

Federal IncentivesExisting financing strategies are being adapted and imple-mented to accelerate access to funding under clean energy finance requirements for federal, state, and local financing. Several tools are emerging that can benefit microgrids, especially as the clean energy sector seeks alternatives to traditional tax-equity funding. Historical reliance on tax equity-driven structures has yielded one-off deals with high transaction costs and has subjected the renewable energy industry to feast-and-famine cycles that have hin-dered rational long-term success.

Treating microgrids as infrastructure investments will allow developers to begin accessing broader and deeper pools of funds, including bond financing. Numerous possible structures can be explored and exploited for specific projects, including public benefit funds, such as Xcel Energy’s Renew-able Development Fund; PACE loans and loan-loss funds; tax-equity pooling matched with bonds for debt; establishing new asset classes for infrastructure, especially to attract investment by pension funds; credit enhancement with bond financing; regional bond banks; special bonding for microgrids; statewide pools; and project or contract aggrega-tion. Credit enhancement will be key to reducing the risk of development. This will increase the credit rating of a project,

which reduces the cost of debt capital for financing.

Congress is also considering leg-islation (the Master Limited Partner-ships Parity Act) to extend master LPs (MLPs) to renewable energy assets. MLPs help project developers and investors avoid double taxation and thereby attract capital at lower costs. MLPs generally are publicly traded entities that operate like a corporation but do not pay corpo-rate income taxes. After raising cap-ital in the public markets, MLPs distribute the income to sharehold-ers, who pay taxes at their personal

income tax rate.Whether microgrids could qualify for MLP treatment will

depend on the legislative outcome as well as development approaches that structure projects specifically to qualify. The opportunity for microgrids might be substantial as it would create opportunities to access new investment pools.

Minnesota IncentivesMinnesota has tools to offer upon review that could provide support or credit enhancement value to microgrids. Minnesota has enacted a system benefits charge—via the Xcel Energy Renewable Development Fund, established in 1999 in legislation authorizing Xcel’s on-site storage of spent nuclear fuel—and legisla-tion to facilitate PACE bonding (H.F. 2695 and H.F. 3729). Minnesota is one of 15 states, along with Washington, D.C., and Puerto Rico, that have public benefits funds for renewables—projected to offer in the aggregate nation-wide US$7.7 billion by 2017. Minnesota raised US$19.5 million in 2012 and offered in the aggregate US$339 mil-lion from 1999 through 2017. The Minnesota fund does not have a current expiration date. One microgrid proj-ect advocated by the University of St. Thomas was con-ditionally selected for funding under the latest Xcel Energy Renewable Development Fund solicitation pro-cess. Clearer guidance on how future funding will be allocated by the state could help microgrids access

Critical to financing success will be an understanding of both the costs and sources of economic value that microgrids can provide.

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these resources. Future additions to the funds could be allocated to microgrid projects, and other funds could be sourced from financial penalties assessed by the Minnesota Public Utilities Commission for utility non-compliance under Minnesota renewable portfolio stan-dards (RPS) policies—if and when Minnesota utilities fall short of RPS goals.

PACE financing allows property owners to borrow money from newly established munici-pal financing districts to finance efficien-cy and renewable energy measures in retrofit projects. The loan is repaid through an annual special tax, which is usually assessed on property owners’ real estate tax bills. Minnesota enacted legislation (H.F. 2695) in 2010 that allowed cities, counties, and towns to offer PACEfinancing programs. These loans provide for energy conservation improvements, including upgraded heating, ventilation, and air conditioning (HVAC) equipment and investments in renewable energy systems. On-demand bond-financing structures are provided for smaller proj-ects, and pooled or interim financing structures are being developed. Subse-quently in H.F. 3729, Minnesota allowed a local government to designate another authority as an implementing entity to implement a PACE program.

Clarification for microgrids is start-ing to appear, while implementation issues are being ironed out. PACE tools are critical for microgrids in Minne-sota as they offer very low or zero risk of loss. Property tax liens are senior to mortgage debt, with 97% of property taxes current, and losses on PACE loans currently total less than 1%. PACE financing is beneficial to the community as it promotes local job retention and creation while impos-ing no credit or general obligations risk.

The St. Paul Port Authority recently approved the issu-ance of almost US$10 million in revenue bonds for PACEfinancing. The authority will issue the bonds to finance loans to cities throughout the state for projects to boost efficiency or install renewable energy systems. This financing builds from the Trillion BTU Program, in which Xcel Energy and a local nonprofit have teamed up to fund energy retrofits in commercial buildings for heating and lighting. These bonds have a repayment term of 20 years, and their issuance represents one of the first PACE financ-ing transactions in Minnesota since 2010.

Working with local governments in establishing EIDs would be a logical step for microgrid development. The inclusion of district heating and cooling systems along with microgrids as eligible community-based clean ener-gy systems would be an important next step. This would allow for equipment that is not permanently fixed to the

property to qualify for PACE financing. A broader defini-tion of eligible property or improvements would also rec-ognize that microgrids favor no specific technologies but instead focus on performance and results. They should not be penalized for access to financing as a community-based energy system that links multiple clean energy resources to multiple properties (building or owners).

Win-Win ScenariosIn states where microgrid develop-ers are pursuing project opportuni-ties, the lack of win-win business models for microgrid users, other utility customers, and utility com-pany shareholders often prevents projects from moving forward. Util-ity disincentives create a powerful barrier, and utilities wield potent tools for preventing or delaying microgrid development such as uncertain and excessive intercon-nection study requirements. How-ever, developers in a few states are finding microgrid use cases that clearly demonstrate safe, affordable islanding while providing net bene-fits to utility customers and share-holders. This is particularly true in the case where existing DG systems that cannot island to provide unin-terrupted power during utility out-

ages can be retrofitted with new interconnection technology and reconfigured as microgrids.

Several Minnesota utility companies have expressed interest in exploring win-win models. One example is the buy-all, sell-all proposal advanced by Xcel Energy. Such models offer promise, assuming that the valuation models are successfully developed to implement such an approach. Quantifying win-win benefits will depend on utility companies contributing data about the marginal cost of grid power at particular times and places.

However, such win-win models are meaningless with-out projects to implement them. Microgrids and other DERs are novel and disruptive technologies, and main-stream demand is not likely to emerge organically—especially in the face of arrayed challenges—without pilot projects by first adopters. As with other disruptive technologies, such as peer-to-peer computing and even the Internet itself, some states are finding that universities and the U.S. Department of Defense make ideal first adopters for microgrids. Other states, such as Connecticut and California, are assisting local communities in energy assurance efforts that involve microgrid development. In each case, pilot projects require supportive organizations and governments to help resolve complexities and craft win-win models.

Energy project development companies willlikely contribute the equity investment necessary to complete the design of the microgrids and act as the general partner of an LP or company.

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Finally, as projects emerge, market penetration will improve with a microgrid governance structure that enables multiple users to manage shared energy investments as an infrastructural commons. Like many other states, Minnesota has already begun activities within EID structures. A cooperative approach involving EIDs, local community leaders, utilities, and the state seems likely to result in a win-win framework that serves utili-ties, rate payers, and microgrids alike.

AcknowledgmentsThis article is adapted from Minnesota Microgrids: Opportu-nities, Barriers, and Pathways to Energy Assurance (Final Report), (30 Sept. 2013), prepared by a Microgrid Institute team for the Minnesota Department of Commerce, Divi-sion of Energy Resources. This material was based on work supported by the Department of Energy under award number(s) DE-OE0000096. This project was made possible by a grant from the U.S. Department of Energy and the Minnesota Department of Commerce through the Ameri-can Recovery and Reinvestment Act of 2009 (ARRA).

For Further ReadingM. T. Burr, M. J. Zimmer, G. Warner, B. Meloy, J. Bertrand,

W. Levesque, and J. D. McDonald. (2013, Sept. 30). Minnesota

microgrids: Opportunities, barriers, and pathways to energy

assurance (final report). Microgrid Institute for the Minnesota

Department of Commerce, Division of Energy Resources.

[Online]. Available: http://www.microgridinstitute.org/

resources.html

R. L. Dohn. (2011). The business case for microgrids: The

new face of energy modernization, white paper, Siemens

AG. [Online]. Available: http://www.energy.siemens.com/us/

pool/us/energy/energy-topics/smart-grid/downloads/The%

20business%20case%20for%20microgrids_ Siemens%

20white%20paper.pdf

U.S. Department of Energy. (2013, Apr. 29). DSIRE: Data-

base of State Incentives for Renewables & Efficiency. [Online]. Available: http://www.dsireusa.org/incentives/incentive.

cfm?Incentive_Code=MN09R&re=1&ee=1

M. A. Hyams, A. Awai, T. Bourgeois,

K. Cataldo, S. A. Hammer, T. Kelly,

S. Kraham, J. Mitchell, L. Nurani, W.

Pentland, L. Perfetto and J. Van Nostrand.

(2010, Sept.). Microgrids: An assessment

of the value, opportunities, and barriers

to deployment in New York State, final

report. Prepared for the New York State

Energy Research and Development

Authority (NYSERDA). [Online]. Avail-able: http://www.nyserda.ny.gov

T. Stanton. (2012, October). Are smart

microgrids in your future? Exploring chal-

lenges and opportunities for state public

utility regulators. National Regulatory Research Institute.[Online]. Available: http://www.nrri.org/documents/

317330/896d162c-efe2-4a76-9ffe-30be1bc745bd

R. G. Sanders, L. Milford, and T. Rittner. (2013, Aug.). Reduce risk, increase clean energy: How states and cities are

using old finance tools to scale up a new industry. Clean Energy

and Bond Finance Initiative. [Online]. Available: http://www.

cleanegroup.org/assets/Uploads/2013-Files/Reports/CEBFI-

Reduce-Risk-Increase-Clean-Energy-Report-August2013.pdf

BiographiesMichael T. Burr ([email protected]) is the director of the Microgrid Institute and editor-in-chief of Public Utilities Fortnightly.

Michael J. Zimmer ([email protected]) is the Wash-ington counsel for the Microgrid Institute and executive-in-residence at Ohio State University.

Guy Warner ([email protected]) is the founder and CEO of Pareto Energy LLC.

Brian Meloy ([email protected]) is a partner of Leonard, Street, and Deinard.

James Bertrand ([email protected]) is a partner of Leonard, Street, and Deinard.

Walter Levesque ([email protected]) is the microgrid director, DNV GL.

John D. McDonald ([email protected]) is the chair of SGIP 2.0, Inc. He is a Fellow of the IEEE.

The best financing opportunities might be obtained by combining multiple microgrid projects together into a portfolio.

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http://www.energy.siemens.com/us/pool/us/energy/energy-topics/smart-grid/downloads/The%20business%20case%20for%20microgrids_ Siemens%20white%20paper.pdf

http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=MN09R&re=1&ee=1

http://www.nyserda.ny.gov

http://www.nrri.org/documents/317330/896d162c-efe2-4a76-9ffe-30be1bc745bd

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OMMUNITY POWER” HAS BEEN A PART OF OUR ENERGY INFRASTRUCTUREfor as long as investor-owned electric utilities. These small community utili-ty companies often originated from local hydropower resources or were in rural areas that for-profit utility companies did not want to serve because of the high cost of the infrastructure relative to demand.

Today, most of these traditional community power utilities operate on a not-for-profit basis, and, just like for-profit electric utilities, they strive to provide reliable, safe, and rea-sonably priced electricity to their communities. Although demand is minor in community power markets compared to large urban centers, local demand has grown beyond the capacity of local generation sources so these utilities must purchase power in bulk elec-tricity markets.

To improve their negotiating position, many of these small utilities have joined suppli-er aggregators to receive better long-term prices and availability. Some of these


Meeting climate goals, enhancing system resilience, and stimulating

local economic development.

By Michael Roach

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aggregators, e.g., WPPI Energy, own generating facilities and acquire electricity through power purchase contracts. Their generation mix mirrors that of conventional utilities, with coal and nuclear supplying the bulk of the power and wind power augmenting the supply where it is available. Distributed resources usually do not factor into their sup-ply chain.

This article looks at the potential of a new paradigm of “community power” organization that still remains locally controlled and focused on serving community energy needs but avails itself of the latest distributed energy resources (DERs), enabling distribution technologies and market mech-anisms to develop a local energy system that is more sustain-able, more secure, and that generates more tangible economic benefits for the community.

An essential tool to implement this new paradigm is Consortium for Electric Reliability Technology Solu-tions (CERTS) microgrid technology, which generates power and heat from DERs, manages loads, main-tains stability, and goes into island mode when the main grid goes into fault and then resynchronizes auto-matically. To date, most CERTSmicrogrids have been designed for single-facility-level operation. We can envision three types of CERTSmicrogrids:

1) energy assurance microgrids:cover critical loads (30–60%)

2) energy independence microgrids:cover 100% of loads

3) revenue microgrids: cover 100% of loads plus considerably more capacity (100–300%) to sell excess power in different value streams into local distribution systems.

This article presents an overview of the pressures leading communities to examine a new energy paradigm and out-lines a rough framework on how a fleet of revenue microgrids could be used to provide different services for a municipal-owned distribution system. Elements of this new community power paradigm include:

1) capacity assessment for local generation and reconcili-ation with distribution system planning goals

2) standardizing microgrid project engineering, procure-ment, construction (EPC), and interconnection.

3) integrating fleet microgrids with advanced distribu-tion management and power control systems

4) interfacing microgrid secondary control networks for power dispatch

5) establishing distribution-level transactive markets for energy pricing and settlement

6) developing an integrated financial model that links microgrid project development, energy micromarkets, and distribution system operations.

Pressures Changing the Old ParadigmAn individual’s values and actions, when aggregated with other people, express themselves in two forms: consumer demand for products and services and voting behavior for all levels of government. Consumer demand creates bot-tom-up pressures for change, and political choices create top–down legislative and executive pressures. When one pressure does not work, sometimes the other does. Some-times they work together: in conjunction with external geopolitical events, they create pressure for changes that were once thought impossible or not even imagined, espe-cially in the power industry.

From Protests to SustainabilityThe political and consumer pressures to create a new energy

infrastructure paradigm to better serve community needs can be traced back 40 years to the seminal year of 1973. In Jan-uary of that year, the United States and Vietnam finally signed a cease-fire to the long-running war and, by March, the last U.S. troops had left Vietnam. In the Unit-ed States, after the end of the war, the massive social movement that opposed the war disaggregated and people moved on to more personal paths. In the late 1970s and 1980s, the antiwar politi-cal movement and its counterculture transposed into lifestyles of health and sustainability (LOHAS).

Many people went on to apply the critical social change ideas and organi-zational techniques that they learned during Vietnam War protests to domes-tic sectors such as the food industry,

health care and medicine, automobile efficiency and safe-ty, environmental issues concerned with air and water quality, and consumer product life cycles. By the 1990s, these disaggregated LOHAS movements focused on the concept of sustainability to unify what they learned into concepts and practices that brought tangible benefits to consumers, businesses, and government. Today, sustain-ability concepts and practices are embraced by many busi-nesses and governments around the world.

Oil Embargo of 1973 and Growth of Nuclear PowerAnother series of events in 1973 changed forever the con-cept of energy security around the world. When Egypt and Syria invaded Israel on the Yom Kippur holiday, a ferocious war ensued that only lasted a few weeks with Israel even-tually defeating its opponents. The aftermath of the war had an enormous impact on world energy markets. Dur-ing the war, the United States and the Soviet Union resup-plied their respective allies. This American foreign policy action led the Organization of Arab Petroleum Exporting Countries to proclaim an oil embargo against the west and

A fleet microgrid-enabled distribution system may increase the short-term LCOE while at the same time bringing counter-balancinglocal economic benefits.

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the United States in particular. Petroleum prices shot up, and gasoline shortages ensued. Politicians faced almost unbearable pressure to do something and do it quickly. Strategic oil reserves were called into play, and rationing was instituted to spread out supplies and buy time. Concerted efforts were made to revive domestic oil production, especially offshore wells.

The war and the resulting oil embargo forced unintended changes in other sectors of the U.S. economy. The “golden age of gas guzzlers” for the American auto-mobile industry came to an abrupt end. Consumers began to demand more fuel-efficient vehicles. Compact cars, mostly foreign manufactured, entered the American market in increasing volumes and retained large market shares to the present day.

Another industry that was profoundly changed was the power industry. Although petroleum was little used

in the electric generation industry, utility executives and the national security establishment pushed through a plan to massively scale up the installation of nuclear power stations to a one-year record of 41 new plants. (Most of the plants built during that time are still in oper-ation today.) The public was endlessly reassured that the plants would be built and operated absolutely safely. Citi-zens were told that the risk of incidents or a major catas-trophe was so remote that the public did not need to worry at all.

Only six years later, on 28 March 1979, those absolute assurances proved unwarranted when the Three Mile Island (TMI) nuclear plant in Pennsylvania experienced a major accident and a radioactive release. Although the incident was contained and a general evacuation was not called, the emergency evacuation plans proved to be total-ly inadequate. After TMI, the American public no longer

Figure 1. German nuclear facilities. (Image courtesy of picstopin.com.)

Name of the Facility

Nuclear Power Plant

Major Interim Storage Facility for Spent Fuel

Major Interim Storage Facility for Non-HGWOn-Site Interim Storage Facility

Final Disposal Facility for Non-HGW

Former Final Disposal Facilities

BrunsbüttelBrokdorf

Krümmel

Greifswald

Gorleben

Unterweser

Emsland

Ahaus

GrohndeKonrad

AsseMoresleben

Grafenrheinfeld

MitterteichBiblis

Philippsburg

Karlsruhe

Neckarwestheim

GundremmingenIsar

Jülich

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passively trusted the nuclear power industry and the con-struction of new plants ceased in the United States.

German Path to Renewable Power IntegrationIn Europe, after the 1973 oil embargo, the energy security push to build a huge fleet of nuclear power plants for baseload power proceeded as it did in the United States, especially in France and Germany (Figure 1). When Ger-many was ramping up its nuclear power plant fleet, the campaign encountered strong opposition from many local communities, especially with regards to the safety of oper-ating plants. This opposition to the siting of nuclear plants led local community leaders to start reassessing their local energy infrastructure and energy resource mix.

On 26 April 1986, during a routine system test, reactor number four of the Chernobyl plant on the border of the Ukraine and Belarus experienced a series of failures that led to the largest nuclear power accident in history. The cas-cading events resulted in a fire of the graphite moderator, and the resultant plume spread radioactive particles across Russia and western Europe for months (Figure 2). More than 350,000 residents surrounding Chernobyl had to be permanently evacuated and relocated.

In the United States, the Chernobyl disaster was a major media event that TV viewers watched with fascina-tion but with little real danger. In Germany, the danger was much more tangible, and the reaction was more visceral. Low-level radiation clouds swirled over Germany all the way to the French border. German citizens were warned not to consume milk, wild game, and vegetables. Although low-level radiation was their immediate worry,

the Chernobyl disaster made many German citizens ask a more fundamental and worrisome question: What would happen to their small country (approximately the size of New Mexico with a 1986 population of more than 77 mil-lion) if a nuclear catastrophe of Chernobyl scale happened within their borders rather than 1,000 km away?

German citizens of all political stripes now looked to other sources for energy security. Domestic coal, both lig-nite and hard-to-reach hard coal, were available but very expensive without large government subsidies. European Union (EU) courts forced the eventual removal of those subsidies. Natural gas supplies were not available domes-tically so Germany had to turn to the Soviet Union and Norway for supplies but at considerable economic cost and political risk.

The only alternative to fossil fuel supplies for Germany was renewable energy, a technology and industry still in its infancy. R&D programs and small pilot programs were launched to test the feasibility of developing a domestic renewable energy industry and integrating large-scale wind and solar into the resource mix of electricity generation.

In 1990, the Bundestag passed the Stromeinspeiegesetz (StrEG), the first feed-in law, with support from all parlia-mentary factions. The law mainly benefited small hydro-power producers in southern Germany and wind power companies in the north. From 1990 to 2000, wind power capacity increased almost 1,000% from 68 MW to more than 6,000 MW (Figure 3). Under the StrEG, solar power only received 10% of production costs and languished. Throughout the 1990s, vested interests waged a massive campaign to derail the program through legal challenges,

Figure 2. The radiation from Chernobyl. (Image courtesy of GRID Arendal.)

Radiation from Chernobyl

KiloBecquerels (KBq) Per Square Meter

More than 1,480185–1,48040–185

10–402–10Fewer Than 2No DataChernobyl Plant

0 500 1,000 km

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parliamentary maneuvers, and bureaucratic obstacles, but the renewable energy program slowly took hold and began to grow because of continued efforts of the burgeoning renewable energy industry and grassroots campaigns by citizens. Over the years, the economic growth benefits and the emerging export market convinced more people to support the program.

In 1998, after 16 years out of office, a coalition govern-ment of the Green Party and Social Democrats took over and set new goals for the percentage of renewable energy in electricity production: 12.5% by 2010 and 50% by 2050. They passed the 100,000-roof program that offered low-interest loans for photovoltaic (PV) development. They then worked to reform the original 1990 feed-in law through the Erneuer-bare Energie Gesetz of 2000. Reforms included: rates were fixed for 20 years (which increased investor confidence); rates were different for various sources, size, and location; rates increased (especially for solar); utilities were eligible to

participate with large-scale projects; there was an automatic decrease of rates going forward; there would be a review every four years to revise rates depending upon technological improvements; and additional costs of the program were to be spread across all utilities. The last remaining obstacle disappeared when the Euro-pean Court of Justice ruled that feed-in tariffs did not constitute state aid.

During the first decade of the 21st century, Germany embarked upon a massive technological effort to ramp up its manufacturing capacity for solar and wind while simultaneously striving to drive down costs. Germany became a global leader in both tech-nologies. In the northern parts of Germany with high wind power resources, some communities own all or a part of the wind turbines. Some of the areas where rooftop solar is com-bined with local wind power have become net energy exporters.

The key to Germany’s success was not merely its engineering and manufacturing prowess but also its financial acumen. The national feed-in-tariff that was instituted drove the ramp up of installations at a phenomenal pace while also reduc-ing costs. The success of the German feed-in-tariff model continues to be an energy policy that other countries have tried to emulate.

In 2010, the German government published their plan for the Ener-

giewende, which means energy transition (Table 1). The ener-gy transition program directed the country away from nuclear and coal to renewables over a 40-year schedule. On 11 March 2011, the Fukushima Daiichi nuclear disaster occurred in the wake of the tsunami created by the Tohoku earthquake. This was the largest nuclear disaster in history since Chernobyl. Three months later, in June 2011, the German Parliament, in an almost unanimous vote of ruling and opposition parties, confirmed Germa-ny’s long-range energy transition to renewables.

Technical Challenges of Integrating High-Penetration RenewablesThe tremendous growth of renewable energy in Germany brought with it many challenges, especially technical issues over grid stability, price volatility in wholesale electricity markets, and disruptions of the business model of investor-owned utility (IOU) companies.

Verteilung von Windkraftanlagenin Deutschland (2007)

Installierte Leistung< 3 MW

> 30 MW

3–10 MW10–30 MW

Hamburg

Berlin

München

SH

MV

NI

BB

ST

SN

TH

HE

RP

NW

SL

BWBY

0 100 km

Figure 3. The high penetration of renewables—German wind farms. (Image courtesy of the German Wind Power Association.)

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Both wind and solar technologies were intermittent by nature, but geographical dispersion in Germany mitigated some of their variability. On excellent days, wind and solar provide up to 40% of the national demand. On dark and dreary days with little wind, traditional fossil fuel generators need to be brought back online to maintain stability in the grid. Unfortunately, many of the power plants providing this capacity were never designed for such erratic rates of cycling.

Most of Germany’s wind potential is in the northern part of the country, and the best solar irradiation is in the south-ern part. Another technological solution to the intermitten-cy of these renewables and their geographical dispersion is to firm up their power via virtual power plants (VPPs). VPPs were originally developed to aggregate small DERs into a large enough capacity so that they could participate as a single unit in wholesale electricity markets.

VPPs are designed to aggregate DER sources from a widely dispersed region or even Germany as a whole. This wide dispersion helps to somewhat mitigate local weather conditions. For additional firming, biogas is the preferred energy source to fire gas turbines.

VPPs depend upon high-speed information and control technology for both primary and secondary control. This dependency upon information networks introduces both an operational and security risk. VPPs are designed to always be grid-tied and to be dispatchable (like any other utility generator source) from utility network control cen-ters. Numerous pilots are underway to prepare VPP tech-nology for large-scale ramp up such as the Combined Power Plant that links 36 geographically dispersed wind, solar, biogas, and hydro facilities into a VPP.

On good days, the displacement of peak demand by renewable energy generators has created havoc in the tra-ditional wholesale energy markets. Many fossil fuel peak-ing plants depend upon a very limited number of hours of operation per year at very high rates of remuneration. When the wind blows and the sun shines, peaker plants

sit idle and their return on investment plummets. This profitability decline has severely impacted the financial condition of German utility companies.

Changes in German Utility Business ModelThe global investment banking and credit rating commu-nity monitors the German utility market closely. Their recent assessments have been very pessimistic. Citibank, UBS, Deutsch Bank, and Moody’s have issued a series of reports documenting this decline of the industry.

Seeing the writing on the wall, RWE (the second largest German utility company) has decided to change its business model as a result of the high penetration of renewable ener-gy technologies and their disruptive impact on wholesale electricity markets. RWE plans to transform from a tradi-tional electricity provider into a renewable energy service provider, helping to manage and integrate renewables into the grid. EON, the largest utility in Germany, looks like it is now following the RWE path. No American utilities have fol-lowed RWE’s lead.

Energy Policy Quagmire in the United StatesIn the United States, over the last year, energy policy wonks and electric utility professionals have been in a frenzy con-templating the potential death spiral of IOUs due to the dis-ruptive effects of large-scale integration of renewables and microgrids. A multitude of solutions have been developed to assist the utilities to restructure their business models and progress into the smart grid of the 21st century.

Most IOUs have been highly resistant to embracing high penetration levels of renewable energy and adjusting their business models to facilitate the transition to a low-carbon-generation fleet. In advance of a larger fight against microgrids, many utilities are currently fighting the onslaught of DERs, especially solar PV, through contentious battles over net energy metering (NEM) and dragging their

TABLE 1. The Status Quo and the Main Targets of the Energiewende.

2011 2020 2030 2040 2050

Greenhouse Gas Emissions

Greenhouse gas (versus 1990) –26.4% –40% –55% –70% –90%

Efficiency

Primary energy use (versus 2008) –6% –20% –50%

Electricity demand (versus 2008) –2.1% –10% –25%

Heat in residential sector n.a. –20%

Energy use in transport (versus 2005) –0.5% –10% –40%

Renewable energy

Share in electricity consumption 20.3% 35% 50% 65% 80%

Share in final energy use 12.1% 18% 30% 45% 60%

Source: Agora, 12 Insights on Germany’s Energiewende.

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heels on renewable portfolio standards (RPSs). The Edison Electric Institute rec-ommended a range of counter-measures, including instituting new monthly service charges on all tariffs to recover costs, developing new (punitive) tariffs for DER customers, restructuring net energy metering to pay out at wholesale rates rather than at retail as is the current practice, adding stranded cost charges to customer bills, making customers pay in advance for new assets, and factoring in charges for dis-ruptive forces in requested rates.

At the federal level, the lack of a national energy plan leaves the United States’ energy future to long, drawn out political and legal battles that squander precious time and allow other countries to overtake the United States’ competi-tive advantage in intellectual property and new energy tech-nologies.

In Congress, Tea Party members and their Republican col-leagues allow even simple bills on energy efficiency to be killed or delayed indefinitely. It appears that passage of any bills to fight climate change are totally out of the question for years to come. The Obama administration’s only alternative to congressional energy and climate policy intransigence is to push executive actions that do not require congressional approval, such as the Environmental Protection Agency (EPA) restricting pollutants from electricity generating plants. Even these actions will be attacked politically and legally.

Crisis Management for Superstorm SandySuperstorm Sandy created devastating damage across the northeastern United States on 29 October 2012. The storm left an enduring legacy: indelible images of com-munities ravaged by massive flooding, almost unac-countable property damage from water and fire, extended loss of power and essential services, lower Manhattan in nearly complete blackout, and utility com-panies and political leaders with no credible alternatives when future storms strike again.

Since the storm, state and local political leaders, under immense pressure from their constituents, are compelling utilities to come up with new ways to deal with the ferocity of Mother Nature. The State of Connecticut has instituted two rounds of bidding for vendors to supply microgrids for municipalities in the state. Projects are starting to roll out, but the utility business model is inca-pable of dealing with this situation other than by man-date. No structural changes are anticipated in the business model of utility companies servicing the state.

Climate Change as the Tipping Point for Paradigm ChangeWhether it is extreme weather events or the long-term threat of global climate change, communities and their

leaders are seeking new solutions for their energy future that are not dependent upon national politics or incumbent utility companies.

In Europe, climate change responsi-bility has been embraced and national climate and energy policies have been designed and implemented. A decade ago, the EU mandated greenhouse gas reductions for all member states. Most EU members have been able to meet the standards on schedule.

In the United States, at the federal level, climate change policies have only

been possible by federal and state executive action. Con-gressional obstructionism has left a policy void, and real change is left up to local community leaders. Communities across the United States are starting to respond to this vac-uum of leadership.

FLEET MICROGRID PARADIGM

The Energy Future Plans of Boulder, ColoradoOne community that has taken leadership in gaining con-trol over its energy future is Boulder, Colorado, a town of more than 100,000 people in the foothills of the Rocky Mountains. Beginning in 2002, the city council passed a resolution with the goal of reducing the community’s greenhouse gas emissions to 7% below the levels of 1990.

In 2006, voters approved a Climate Action Plan tax to fund programs to meet their Kyoto emission reduction goals. The programs included residential and commercial energy efficiency, especially lighting and energy audits; ramping up solar installations; diverting more than 40% of waste into composting and recycling; and reducing vehicle miles. However, no matter how much they tried to use their energy as efficiently as possible, they could not meet their 2012 Kyoto greenhouse gas emission reduction goals because of something apparently outside of their control—the energy mix they received from their legacy utility company.

Xcel Energy serves Boulder and communities as far away as Minneapolis, Minnesota. Although Xcel complies with the Colorado state RPS, it could not meet the Kyoto goals of Boulder because the Xcel energy mix included 55% coal and 25% gas, and they could not (or would not) change that mix. This wall led Boulder to consider other options. From 2005 onward, the city commenced a series of public events and feasibility studies that analyzed whether Boulder could municipalize the distribution assets of Xcel and determine their own energy mix.

In 2011, voters approved ballot initiatives to create a munic-ipal utility company if certain metrics were met including:

rate stabilityservice reliabilityreduction of carbon emissions

In Europe, climate change responsibility has been embraced and national climate and energy policies have been designed and implemented.

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local control of energy decisions and maximum investments in local power.

During 2012 and 2013, additional feasibility studies were conducted to analyze the legal, financial, engineer-ing, and environmental issues to move ahead with municipalization. The City of Boulder and its consul-tants developed detailed models with various scenarios for demand and energy mix over 20 years.

The five stages of the modeling process included:

1) understanding how Boulder uses energy now and in the future

2) developing the options model that compared low- and high-cost resource mixes with different amounts of renewable energy

3) identifying the best resource options4) determining overall costs5) identifying and mitigating current and future risks,

including stranded and acquisition costs.As a baseline, the 2010 aggregated city load profile was

used:load factor: 68%peak demand: 236 MW in Julybase load: 116 MWannual energy: 1,396,234 MWhannual growth: 1.80%commercial and industrial (C&I) load: 82%C&I load: 1,114,986 MWh.

In 2017, the first year of municipal operation, the Boulder model envisions a low-cost option with a resource mix of:

45% gas35% wind13% coal4% solar3% hydro.

The wind power in the mix would be purchased through large contracted must-take power purchase agreements balanced with natural gas for reliability. Solar power would be funded through municipal finance at the rate of US$3.5–$7 million annually. This model assumes that Boulder would have approximately 20 MW of solar installed by 2017. The model projects that the city would retain approximately US$24 million (in 2011 dollars) annu-ally from operating the distribution system themselves.

Another option that the city considered is a “Local-ization Portfolio Standard (LPS) for Electricity and Natu-ral Gas.” This option is intended to meet or beat the incumbent energy economics, a difficult task given that electricity is relatively inexpensive (US$0.943/kWh 2013) in Boulder. The LPS option focused primarily on demand-side resources including energy efficiency, conservation, and residential and commercial demand response.

On 11 October 2013, a referendum passed by a three-to-one margin to create a new municipal utility that was to be an energy services provider for Boulder customers, not just a com-modity provider of fossil fuel energy. The new energy future for Boulder rests upon the traditional business model used by countless other municipalities and electric co-ops around the country, where distribution assets are locally owned but energy is purchased in the bulk market. The is the same business model that Denton Municipal Electric

(Denton, Texas) uses: 40% from the Wolf Ridge wind farm; 50% from the Gibbon’s Creek coal plant; and the remainder from a landfill gas project and supply contracts through NRGPower Marketing LLC.

Boulder’s variation is to purchase as much electricity as possible from distant utility-scale wind farms and wheel the energy through Xcel’s transmission grid. There is a finite level (approximately 40%) to the percentage of wind power acquired due to intermittency issues and the resulting grid stability problems. To firm the wind power beyond 40% requires either that Xcel balances the intermittency (with fossil generators) or Boulder uses a gas turbine plant. Either way, fossil fuels remain a major component of the energy mix and high levels (e.g., 80%) of renewables are not possible.

Without a fundamental change in the business model paradigm, even local ownership of distribution assets lim-its the ability of communities to pursue a low-carbon future. The rest of this article examines a business model paradigm in which distribution assets are owned locally; DERs, especially microgrids, become the prime energy source; and the bulk power market is used only as a last supply resort or for selling energy services from the micro-grid-enabled distribution system back into the bulk power market just as demand-response programs have been doing for years.

Framework for Fleet Microgrid-Enabled Municipal Distribution

We use Boulder as a conceptual framework for two reasons:Boulder will own their distribution assets, and the city distribution company, in coordination with Boulder internal departments, could set up expedited permit-ting and interconnection protocols that could speed the time to market for microgrid projects and result in lower installation costs that, in turn, help to lower the help to lower the levelized cost of energy (LCOE).Because of the many consulting studies that Boulder has conducted in its due diligence to determine the feasibility of municipalization, sufficient data are avail-able to rough out a vision of a distributed generation system and how it could be integrated and managed by the distribution company.

The success of the German feed-in-tariff model continues to be an energy policy that other countries have tried to emulate.

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The first step in our framework involves looking at the total number of buildings in Boulder and the square feet per sector (Table 2). In the 2010 baseline, the total private and public square footage was 46,984,398 ft2. The pri-vate sector accounts for 75.3% of the square footage (35,357,542 ft2) and 89.3% of the buildings (1,618). In the following framework, we only use private sector data for the sake of simplicity.

Boulder’s C&I electricity annual demand is estimated at 1,114,900 MWh (82%) of the 2010 total demand baseline of 1,396,324 MWh. This level of C&I demand is significant-ly above the national average of 62% C&I demand. Boul-der’s higher level is attributed to a high number of industrial process companies with higher energy intensity in their consumption.

Microgrid Fleet Generation Capacity and RolloutThe microgrid fleet that we propose is a simple PV solar and combined heat and power (CHP) hybrid system based on CERTS architecture that embeds primary control in each distributed resource. The CERTS model of microgrids is based on the pioneering research work of Prof. Robert Lasseter of the University of Wisconsin, Madison. Prof. Lasseter’s solutions allow a new class of true plug-n-play and peer-to-peer implementations of DERs into an inte-grated on-site energy system without the need for a dedi-cated command and control system. CERTS microgrids leverage the best available microscale power generation and load management technologies to optimize the per-formance of local supply and demand.

The fundamental technological design advantage of the CERTS microgrid technology is that the software algorithms used to control individual DER units are embedded in the firmware of each DER unit at the manufacturing stage. This approach allows the microgrid system to respond dynami-cally to balance the DER performance and load adjust-ments without depending upon custom command and control software. CERTS microgrids eliminate command and control system single points of failure and immensely simplify the design of microgrid projects, thereby providing the basis to compress the economic value chain and reduce project costs significantly over custom engineered systems. The CERTS approach provides a solid basis upon which to construct a new class of plug-n-play DER units, cost-effective on-site facility microgrid systems, and the basis for building out networks of coupled microgrids. Because of this lean and ultraefficient design, CERTS microgrids pro-vide the most cost-effective choice of enhanced reliability, power quality, and energy savings.

For the solar component, with the above commercial property inventory, we estimate that more than 88 MW of rooftop solar capacity could be installed and that the solar systems could generate 128,931,277 kWh/year. Additional solar carport space is available but not used in this esti-mation. Therefore, solar PV could generate approximately 11% of 2010 C&I demand.

The CHP component would be composed of 1,900 100-kW Tecogen InVerde units and they would be installed in 772 buildings (tier 2 and tier 3 buildings over 10,000 ft2). Tecogen CHP units are widely implemented

TABLE 2. The Boulder Private Building Inventory.

Size Category Number Bldgs Total ft2 Average ft2/Bldg % Total ft2 % Number Bldgs

Tier 1

Fewer than 1,000 69 35,344 512 0.1% 4.3%

1,000–4,999 437 1,273,455 2,914 3.6% 27.0%

5,000–9,999 340 2,449,221 7,204 6.9% 21.0%

Subtotal 846 3,758,020 4,442 10.6% 52.3%

Tier 2

10,000–19,999 300 4,212,723 14,042 11.9% 18.5%

20,000–29,999 173 4,198,069 24,266 11.9% 10.7%

Subtotal 473 8,410,792 17,782 23.8% 29.2%

Tier 3

30,000–39,999 92 3,257,714 35,410 9.2% 5.7%

40,000–49,999 57 2,540,362 44,568 7.2% 3.5%

50,000 and above

150 17,390,654 115,938 49.2% 9.3%

Subtotal 299 23,188,730 77,554 65.6% 18.5%

Total 1,618 35,357,542 21,853 100.0% 100.0%

Data from Boulder County Assessors Records.

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and they were one of the only available power sources in lower Manhattan following Superstorm Sandy.

CHP capacity is estimated at 190 MW with an electricity output of 1,139,194,827 kWh/year (at a maximum 90% run rate). The CHP output is calculated only for its electricity gen-eration. The Tecogen units generate large amounts of waste heat that can be economically used in building heating or air conditioning (through absorption chillers). This very signifi-cant additional energy efficiency is not included in the esti-mation of load coverage. Also, although many legacy on-site generators could be incorporated into microgrids, they are not included in the total capacity estimation.

When the solar PV systems and the CHP systems are combined into a fleet of CERTS microgrids, the combined systems could generate 100% of the annual load for the entire city of Boulder distribution grid. Conceptually, this microgrid fleet rollout would convert every commercial building in Boulder into a net-zero smart building with 100% on-site generation and flexible load management and many sites would also have the capacity to export excess energy for other Boulder grid customers. The entire distribution grid could become net zero energy system producing as much as it consumes.

The process of installing commercial PV solar and CHP systems is well known. With the standardization of per-mitting and components, and with large competitive pro-curement contracts, systems could be installed for US$2.50 per watt or less. Buildings below 10,000 ft2 would only have PV solar, and all buildings more than 10,000 ft2

would also include from one to five CHP units. This public/

private works programs would have an enormous eco-nomic impact on the city of Boulder over many years.

Although the installation of 772 CERTS microgrids would be a daunting task, they could be completed in less time than the permitting and EPC costs of a gas turbine plant (approximately five years) that would be necessary for balancing very high levels of wind power as envisioned in the Boulder energy future plans. Also, the construction of a gas turbine plant would generate very little local eco-nomic development.

Microgrid Fleet ManagementAssuming that such a large fleet of microgrids could be designed, financed, and installed, how could the munici-pal distribution company manage the fleet?

Currently, most companies that focus on microgrid control and optimization have concentrated on the host side of the meter to optimize a single facility microgrid or an aggregated campus microgrid, such as the University of California at San Diego. Companies such as Power Analyt-ics have developed sophisticated packages for these types of stand-alone microgrid host sites.

However, fleet management must be considered from the perspective of the distribution company. Major system inte-gration vendors (e.g., Schneider Electric, Siemens, ABB, and GE) serving the utility industry have developed new solutions to integrating large numbers of distributed resources into mod-ern distribution grids (Figure 4).

As an example, from the perspective of Schneider Elec-tric, the business objectives of a smart grid advanced

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Figure 4. A framework for microgrid fleet management. (Image courtesy of Schneider Electric.)

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distribution management system (ADMS) that could accommodate a large fleet of microgrids includes:

integration of supply-side and demand-side resources, including microgrids, into real-time and day-ahead operationsautomation and optimization of dispatch of resources.

Schneider’s ADMS and Power Control System includes applications for:

economic dispatchload forecastrenewables generation forecastautomatic generation controlinterchange transaction schedulerunit commitmentfast load sheddingplanning and operation of distribution grid.

The integration of a high number of microgrids into a distribution system presents numerous technical chal-lenges (Figure 4) including:

Protection and stability of distribution circuits: As everyone in the electric industry knows, distribution systems have been designed as one-way power flow systems. When traditional PV solar systems are installed, they are required to automatically disconnect from the distribu-tion grid when a fault is detected, and then they must come back online from a black start authorized by the distribution operator. In contrast, with their built-in safe-ty technology, CERTS microgrids do not present them-selves as energized hazards to utility work crews. With fast, intelligent switches, they automatically disconnect into island mode and then automatically resynchronize

when grid stability is detected. While they are in island mode, CERTS microgrids automatically balance their internal generation and loads and maintain stability within their circuits.Variability: Variability is a major problem with traditional solar and wind systems. In contrast, CERTS microgrids are “good citizens” of the grid and always balance DERvariability internally so that they do not present them-selves as a problem to the distribution operator.Overvoltage: A problem that microgrids will present is overvoltage on local circuits. Currently, under NEM, utility companies have limited customers from sending energy back into the system of no more than 105% of their load. Under a fleet microgrid system, the basic concept is to generate 100% of local load and to be able to generate excess energy that can be economically dispatched by the distribution operator. Some microgrids may have the capacity to export significant amounts of energy.Monitoring and control of each source on each microgrid: To determine the available capacity of the microgrid fleet, the distribution operator needs to know the capacity, status and forecasted production of each source so that planning and operation of distribution meets supply requirements and conventional power flow constraints. This secondary control requires a secure communica-tions network that can process a large number of control points in real time.Dispatchability of microgrids: The key to the economic and power supply roles of revenue microgrids is that a portion of their predictable capacity can be dispatched reliably by the distribution operator (Figure 5). The

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problem is to “determine the generator set points so that the overall cost of power generation is mini-mized, while respecting limits on generator’s capacity and transmission power flow constraints.” For most utilities, the traditional unidirectional flow of electricity shapes system con-trols, analytics, energy markets, and operations. With the growth of downstream demand-side management, distribution utili-ties are now looking to defer con-ventional T&D costs. Con Edison analyzed three years of historical data from a 7.5-MW CHP system at 4-s intervals before they would include the source in their long-term planning.Distribution system management:When integrating large numbers of microgrids, the communica-tions, analytical, and operational requirements are more complex and time sensitive because of the narrower margins of relatively small supply resources (fewer than 10 MW) relative to traditional supply sources (hundreds of MWs). The distribution system operator needs advanced communications and distribution manage-ment system (DMS) software to maintain a fleet of microgrids (Figure 6).Transactive local energy market structures and operations: Even if the technical power management challenges created by microgrid supply and distribu-tion management can be overcome efficiently, the question remains as to whether this can be accom-plished economically and equitably for all participating parties. Transactive energy market concepts have been developed to solve the participation and economic

challenges of thousands, or even millions, of customers that are both consumers and suppliers of energy.

ConclusionAlthough a framework can be envi-sioned of a net-zero energy distribu-tion system based upon a fleet of microgrids for supply, it will take a considerable amount of effort to attach hard numbers to each component of the system and determine its overall economic viability in the marketplace. Tradeoffs may be needed in the mar-ketplace to balance supply, reliability, efficiency, and economics. A fleet microgrid-enabled distribution system may increase the short-term LCOEwhile at the same time bringing coun-ter-balancing local economic benefits. In some markets with high retail rates, a microgrid-enabled distribution sys-tem may be received more favorably, especially in markets were power resil-

iency has also become a high priority. Whatever happens, community power will never be the same again.

For Further ReadingAdvanced Energy Economy Institute (AEEI). (2013, Apr.). Accelerating advanced energy in America: Perspectives of advanced energy business leaders on U.S. Energy Policy. PAConsulting Group, Inc., prepared for: Advanced Energy Economy Institute (AEEI). [Online]. Available: http://www.aee.net/acceleratingAE

Agora Energiewende. (2013, Feb.). 12 Insights on Germany’s Energiewende. [Online]. Available: http://www.agora-energiewende.org/topics/the-energiewende/detail-view/article/12-insights-on-the-energiewende/

K. Beckman. (2013, Oct.). RWE sheds old business model. Embraces energy transition. [Online]. Available: http://www.energypost.eu/exclusive-rwe-sheds-old-business-model-embraces-energy-transition/

R. Binz. (2013, June 26). Utility sector disruptive changes (in eleven pictures), Public Policy Consulting, Presentation at: Electric Markets Impact Michigan’s Energy Decisions, Ann Arbor, MI. [Online]. Available: http://erb.umich.edu/SlidePresentations/Energy-Futures-Conference-2013/Binz-Michigan-Presentation062613.pdf

R. Binz and R. Lehr. (2013, Mar. 28). New utility business models: Implications of a high-penetration renewable energy future. Presented to the Western Governor’s Associ-ation. [Online]. Available: http://www.westgov.org/wieb/meetings/crepcsprg2013/briefing/Lehr-Binz.pdf

A. Bredenberg. (2011, June 27). German combined power plant demonstrates real-time integration of renewables. Thomasnet News, Green & Clean Journal. [Online]. Avail-able: http://news.thomasnet.com/green_clean/2011/06/27/Figure 6. The distribution control room using ADMS. (Photo courtesy

of Schneider Electric.)

The microgrid fleet that we propose is a simple PV solar and combined heat and power (CHP) hybrid system based on CERTS architecture that embeds primary control in each distributed resource.

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BiographyMichael Roach ([email protected]) is the CEO of MicroGrid Horizons, a consulting and project devel-opment company dedicated to commercializing microgrid technology and developing sustainable business models for integrating distributed energy resources into the smart grid.

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http://cal-ires.ucdavis.edu/files/events/2011-resco-symposium/washom-byron_cal-ires-resco.pdf

http://www.youtube.com/watch?v=oZ74Rqh7yDE

http://www.wppienergy.org/media/WPPIEnergy_AnnualReport_2012_web.pdf


http://www.pserc.wisc.edu/documents/publications/papers/2013_general_publications/

http://mseia.net/site/wp-content/uploads/2012/05/Roach_HurricaneSandyandtheEmperorsNewClothes_2012_wRefs.doc






URRENT TRENDS INDICATE THAT WORLD-wide electricity distribution networks are experiencing a transformation toward direct current (dc) at both the generation and consumption level. This tendency is

powered by the outburst of various electronic loads and, at the same time, the struggle to meet the lofty goals for the sharing of renewable energy sources (RESs) in satisfying total demand. RESs operate either natively at dc or have a dc link in the heart of their power electronic interface, whereas the end-point connection of electronic loads, bat-teries, and fuel cells is exclusively dc. Therefore, merging these devices into dedicated dc distribution architectures through corresponding dc–dc converters is an attractive option not only in terms of enhancing efficiency because

of reduction of conversion steps but also for realizing power quality independence from the utility mains. These kinds of systems generally provide improved reliability in comparison to their alternating current (ac) counterparts since the number of active elements in dc–dc power elec-tronic devices is smaller than in dc-ac converters. Control design in dc systems is also significantly simpler since there are no reactive and harmonic power flows or prob-lems with synchronization.

Historical Perspective: Return to dcThe present electrical power supply systems are the product of a long-term technological development that started at the end of 19th century. The trigger for its rapid uprising was the invention of the transformer, the first device that was able to transform ac voltages to different values and, hence, keep the line losses at low levels, even when transmitting electric power at long distances. The


A step toward a new generation of power distribution networks.

By Tomislav Dragicevic, Juan C. Vasquez, Josep M. Guerrero, and Davor Škrlec

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transformer was the main reason for the victory of ac in the famous “Battle of the Currents,” in which Thomas Alva Edison and George Westinghouse publicly debated the merits of their newly proposed dc and ac power sys-tems, respectively. The outcome of this industrial war was strongly influenced by the work of Nikola Tesla, who invented a number of breakthrough ac-based devices and principles, maintaining the vital importance in industrial applications up to the present. The final result was a glob-al acceptance of ac as the fundamental architecture for electricity generation, transmission, and distribution. Shortly thereafter, electricity became a publicly accessible commodity around the globe, triggering the blossoming of an entire industry.

This rapid development eventually brought another major technological milestone: the invention of the transis-tor. Considered one of the greatest findings of the 20th cen-tury, the transistor was initially designed to lay the

foundation for the progress in computers and communica-tions. However, as a by-product, it has also enabled the transformation of dc voltages, sparking a power electronics revolution. Now, some 50 years after its onset, power elec-tronics is firmly established as an integral part of modern industry, which strongly underpins the new tendencies in power systems, one of which is the return of dc in big style.

The Future of Integrated Power Distribution Systems: Compliance with Smart Grid ObjectivesIt is a common belief that energy, control, and communi-cations technologies have reached the level of maturity, which is sufficient to put forward a new power utility shift known as the smart grid. The concept of the smart grid was originally envisioned to stimulate the improvement of electric power networks in accordance with certain goals, such as:

TOWER COURTESY OF STOCK.XCHNG/DADITO.

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providing power quality for 21st-century needsoperating resiliently against physical and cyber-attacksaccommodating all generation and storage optionsenabling new products, services, and marketsoptimizing assets and operating efficiently.

The concrete measures that should be taken to accom-plish these objectives have been the subject of intensified research over the past decade. This article explores the strategy that deals with all of them at the same time: a fundamental turnaround at the grassroots levels of low-voltage distribution systems, from ac to dc architectures. In that sense, a particular dc subsystem connected to a supreme ac distribution through dedicated dc–ac convert-er automatically implies power quality independence from utility mains. Furthermore, it gives a natural inter-face for modern electronic loads as well as for most RESs and energy-storage systems (ESSs) like batteries. The pos-sibility of islanded operation that makes the system fully resistant to major blackouts in the main grid is much more simple to design on dc because of the lack of syn-chronization problems and reactive power flows. More-over, with proper selection of nominal operating voltage, its efficiency will generally be higher than its ac

counterpart. With these facts in mind, we envision that these kinds of dc subsystems will constitute the core of future distribution networks and that they will be gradual-ly adopted in applications such as dc homes, hybrid elec-tric vehicle (HEV) charging stations, and commercial and industrial facilities.

A next-generation distribution system that is in line with the aforementioned discussion is depicted in Figure 1. It shows a number of dc-powered subsystems connected to a single synchronous ac system that includes appliances in which dc has already been used for years, such as telecommunication systems, data cen-ters, and dc renewable generation facilities. However, it is the extension of dc to future appliances and to those that were traditionally operating on ac backbone that will make a true difference. For instance, an HEV charging sta-tion formed around a common dc link has the ability of providing much faster recharging service to connected vehicles than presently available ac chargers. Moreover, since the grid connection may be realized by means of a dedicated dc–ac converter, the grid support and power exchange control at the associated point of common cou-pling (PCC) are straightforward. The substitution of tradi-tional ac architectures in favor of dc for the case of future

Figure 1. A next-generation distribution system.

–48 VdcRemote Telecom Station

ac TransmissionSystem

VFD IndustrialMachinery

LED StreetLighting

GridInverter

DistributionSystem

Substation

380 Vdc

pHEV Charging Station

Flywheel

Grid-Tied BidirectionalInverter

Grid RectifierGrid Rectifier

Bidirectionalac–dc Converters

+–

+ – + –+ –

380 Vdc380 Vdc 380 Vdc

dc–dcConverters

Multistageac–dc

Converters

Commercial Building

Data CenterPowered Home

+–

dc RenewableEnergy Park

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households and commercial buildings is expected to remarkably enhance their energy efficiencies since the major share of their consumption is formed by devices that require a dc link in the interface point or in one of the conversion stages. In this regard, appliances such as light-emitting diode (LED) lighting, consumer electronics, and variable-frequency drive (VFD) machines (refrigera-tors, heaters, air conditioners, washing machines, etc.) may contribute to overall efficiency improvement by omitting one or several dc/ac conversion stage(s). Another example for the legitimate use of dc architecture is an electrical power supply of a typical industrial factory facility where a potential for improving the propulsion efficiency stems from a possibility to run a group of VFDmotors from the common dc link.

Today, residential dc architectures operating at 380 V are in the development stage and are only a few steps away from real-world implementation. Indeed, recent studies have roughly estimated their cost effectiveness, indicating up to 30% efficiency gain in comparison with traditional low-voltage ac. Electrical distributions of some of the applications mentioned here are addressed in more detail in the following sections, which are sequenced in line with their growing nominal voltage.

Low-Power Consumer ElectronicsThe battery is a life vein of consumer electronic devices such as MP3 players, cell phones, tablets, digital cameras, laptop computers, and others. Their entire electrical sys-tems consist of a number of dc–dc converter stages that are connected to battery terminals. These converters transform the voltage to levels appropriate for fundamen-tal loads such as displays, processors, cameras, wireless modules, and other application adapted consumption (see Figure 2 for the electrical layout of a modern smartphone).

Today, lithium-ion polymer (Li-Po) battery cells are a common choice for consumer electronics because of their particularly high energy density and a convenient property that allows for a high degree of flexibility in the hardware design. However, unlike batteries from the previous gener-ations, a significant shortening of the lifetime or even haz-ardous conditions may occur if lithium-based batteries are exposed to mistreatments such as high temperature or

overcharge/discharge operation. Therefore, a battery man-agement system (BMS) whose main function is recharge control, state of charge (SOC), and state-of-health monitor-ing has become a constituent part of modern gadgets. In relation to the required storage capacity, it is generally pos-sible to achieve a sufficient storage capacity for smart-phones by using a single 3.7-V Li-Po battery cell, whereas two to three paralleled cells are needed for tablets and dig-ital cameras. On the other hand, it is a common practice to assemble series-parallel cell arrangements for supplying more-demanding devices such as high-performance lap-tops. For these kinds of packs, commercial BMSs often come with an integrated equalization circuit, which is nec-essary for balancing the charge among the respective cells.

By referring back to Figure 2, one may observe that the dc–ac converter is the ultimate conversion step toward the grid. With the aim of increased energy efficiency, this con-version stage may be avoided by using only a single stage dc–dc, given that there are readily accessible dc sockets

Figure 2. The typical electrical layout of a smartphone.

Wi-FiModule

LCDPanel

TouchScreenControl Camera

dc−dc

dc−dc

dc−dc

dc−dc

3.7–20-Vdc Bus

BatteryPack

Optional CellCharge

Equalization(for Series CellConnections)Adapter

WallSocket,ac Grid

Charge Control

ac−dc dc−dc

The battery is a life vein of consumer electronic devices such as MP3 players, cell phones, tablets, digital cameras, laptop computers, and others.

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from dedicated dc power architecture. One example of such an architecture, i.e., the typical telecommunication power supply system, is presented in the next section.

Telecommunication IndustryThe −48 V telecommunication power supply station is likely the best-known example of a full-scale dc distribu-tion. A standard measure of reliability in this kind of sys-tem is five nines (99.999%), whereas for comparison, the usual requirement for the ac bulk power systems is three nines (99.9%). There is a big difference in the permissible downtime between the two, i.e., 5 min and 9 h per year, respectively. The reason why such a high reliability may be achieved in dc systems is the possibility for a direct con-nection of the central battery stack to the common bus. This kind of strategy is, as in the case of consumer elec-tronics, also popular in the telecom industry.

To have high-quality signal coverage over a large area, telecom companies are putting more telecom stations into operation. Those that are built on remote locations normally operate in islanded mode since they stand either too far from the ac utility mains or have a con-sumption that is too low for performing cost-effective grid expansion. In that sense, the replacement of conventional diesel generators that require regular maintenance and

refueling with RESs as the main energy sources emerges as an increasingly popular solution for modern installa-tions. The battery stack then has a dual role:

1) Backup power and stabilization: The capacity of the battery is usually high enough to provide long-term backup power and to ensure stability.

2) Smoothing the common bus voltage: Voltage tran-sients in the common bus that arise from fluctuating RES production and load profile are largely sup-pressed by the battery polarization dynamics. It is worth mentioning that another dc storage technology, i.e., the electrochemical double-layer capacitor, is also often deployed for this short-term power-leveling pur-pose since it has an exceptionally high power density.

The typical electrical layout of a remote telecom dc distri-bution system based on RESs is shown in Figure 3. One may note that all components except secondary batteries are connected to the main bus through power electronic inter-faces. Therefore, the required voltage levels for electronic loads are achieved by processing the battery voltage through dedicated point-of-load converters. On the other hand, RESs are connected through either single or double converter interfaces, depending on the type of the source. Neverthe-less, their last conversion stage is ordinarily based on a dc–dc converter with an integrated bus-signaling control

POL Converters dc−dc

dc−dc dc−dc dc−dc

ac−dcac−dc

dc−dc dc−dc ac−dc

Plug-in Load Sockets

Voltage MeasurementVoltage MeasurementVoltage Measurement

LocalControl

LocalControl

LocalControl

Flywheel

PV ArraySmall Wind

Turbine

SecondaryBattery

Current

Measurement

Current

Measurement

Current

Measurement

Figure 3. The electrical layout of a remote telecom dc distribution system.

A distributed resolution of the aforementioned control strategy gained a lot of popularity in industry since it enables the plug-and-play feature for additional sources.

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scheme, which determines the appropriate operating mode, depending on the battery voltage (dc sources such as photo-voltaic panels and fuel cells can be connected through single dc–dc converter stage, whereas, in the case of ac sources such as small wind turbines, an intermediate dc link needs to be formed using an additional ac–dc converter). In gener-al, there are two relevant modes in that sense: constant power mode, which implies operation under MPPT algo-rithms, and voltage-regulation mode where part of the avail-able energy from RESs is dumped to regulate the charging of the battery.

A distributed resolution of the aforementioned control strategy gained a lot of popularity in industry since it enables the plug-and-play feature for additional sources. For this reason, but also because of the inherent stability of these kinds of systems, the construction of customized dc renewable energy parks for telecom stations was made possible in an ad hoc manner, by a simple buildup of the system using commercially available modules. Neverthe-less, this kind of approach may be considered useful only for small-scale electrical power supplies that do not require precise control over the common bus voltage and are not anticipated for substantial future expansions.

Vehicular Technology: HEVs and Fast DC Charging StationsThe concept of the electric car finds its roots at the end of 19th century, when the first vehicles were developed largely relying on dc motor technology that was invented by Thomas Davenport in 1834. The accompanying industrial buzz result-ed in several successful applications, such as electric-grid-powered trolley systems for public transportation and coal mining. On the other hand, motors in vehicles that required more freedom of movement, such as taxis and passenger cars, were powered by electrochemical batteries. The electric vehicles (EVs) of that time had a number of advantages over their gas-oline- and steam-powered rivals, such as significantly quicker start time and no issues associated with vibration, smell, and noise. However, the development of intercity road infrastructure in the United States in the early 20th century highlighted the problem of their limited range, while the discovery of vast deposits of oil greatly reduced the driving costs of gasoline-powered cars, which soon completely took over the market.

Nevertheless, auxiliary 6 Vdc elec-trical systems remained a vital part

of road vehicles that supplied power for electrical starters. The voltage was eventually increased to 14 V to support newer and stronger engines with high-performance start-ers, and it has been kept as the industry standard to date. Apart from ignition, the usage of electrical distribution eventually spread also to power other appliances such as lighting, instrumentation, and electric motor drives. How-ever, the propulsion of these vehicles remained based exclusively on internal combustion engines (ICEs) until recent times.

A strong interest in EVs has been awakened again in the last few decades when concerns related to reduction of fossil fuel reserves and greenhouse gas emissions became the main driving factor. Much academic and industrial effort has been directed toward the develop-ment of a more-electric vehicle concept, giving birth to three main groups of vehicular technologies: EVs, HEVs, and fuel cell vehicles. The difference between them lies in the manner of power generation for vehicle propul-sion. The only source of power for EVs is an electro-chemical battery, while HEVs and fuel cell vehicles are driven by a combination of a battery and ICE or hydro-gen fuel cell, respectively. The battery is still the major limiting factor for wider use of EVs because the power and energy density in even the best batteries are not predicted to be competitive with those of liquid fuels anytime soon. On the other hand, the technology of

ac−dc dc−dc

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nal Loads

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High-Voltage StorageSystem

AirConditioning

Steering System

ElectricMachine 1

InternalCombustion

Engine

PlanetaryGear

Propulsion System

Unit

ElectricMachine 2

Figure 4. The electrical layout of an HEV.

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hydrogen fuel cell vehicles has still not matured enough, and although it offers good efficiency and practically zero emissions, the challenges related to hydrogen pro-duction and its storage within the vehicle keep restrain-ing its market penetration.

Therefore, HEVs that use batteries only for power leveling by maximizing the fuel economy of the associated ICE and using concepts such as regenerative braking, throttle actua-tion, and power steering, among others, have emerged as the best alternative to conventional vehicles. The electrical distribution of HEVs is conceptually similar to those that characterize consumer electronic devices and is shown in Figure 4. It can be seen that the output terminals of the car battery are extended to form the main electrical bus that has all the other electronic and conventional loads directly connected to it.

Since it is very likely that the electrical consumption in modern cars will reach several tens of kW in the near future, an increase of the distribution voltage is inevitable for having high power-distribution efficiency and restrain-ing the wiring weight. In that sense, higher nominal volt-ages are used in the popular HEV models, i.e., 201.6 V in the Toyota Prius or 355.2 V in the Chevrolet Volt. By deploy-ing power electronic converters, buses with other voltages can be realized, including the classical 14-V bus, which may serve for electrical supply of standard loads such as

window lifters, consumer electronic chargers, or ventila-tion systems.

Another important prerequisite for the rapid increase in the number of plug-in HEVs on the roads is the construction of advanced EV charging infrastructure. Ahighly desirable feature of EV charging stations is the ability to provide a recharging procedure that is as similar as pos-sible to conventional petrol stations, as seen from the per-spective of the vehicle user. The main obstacle in achieving this capability is the limitation of power extraction from conventional ac plugs of up to 10 kW, which makes the recharging process very slow and, hence, unattractive for public locations. As a solution to this problem, fast charging directly from the station’s dc link has emerged as a viable alternative. However, since it implies power extraction of up to 50 kW, there is a legitimate concern about the adverse impact of large fleets of charging stations on utility mains. Therefore, from our standpoint, it will be mandatory to use some kind of dedicated ESS, at least for short-term power-leveling purposes. A diagram of an EV fast charging station formed around a common dc link that uses a flywheel ESSfor the power-balancing task is shown in Figure 5. A fly-wheel is selected here since it provides very high power density and incomparably longer cycle-life than electro-chemical batteries and hence suits this kind of application much better, despite a higher initial cost.

HEV

DSOCommands

Local GridControl

Grid ac−dc

dc−dc

dc−ac

FlywheelConverter

Flywheel

ElectricMachine

ia, b, c

va, b, c

va, b, c vdcvdc

vBATiBAT

Fast-Charge

Controller

FlywheelControl

GridConverter

dcLink

ω

ia, b, c

Figure 5. An EV fast-charging station can use a flywheel ESS for power balancing.

The controllability of a singular dc bus voltage also results in the controllability of tie-line current flows toward other dc buses.

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Enhancement of Conventional dc Power Distribution ArchitecturesThe main factor contributing to the high reliability and robustness of telecom systems, consumer electronics, and HEVs, i.e., the direct connection of the battery to the com-mon bus, entails several major drawbacks that come more into play in cases when more expandable and flexi-ble dc systems are required. The most prominent prob-lems include mandatory rigid design of a battery pack, decentralized charging that causes circulating currents, and inability to directly control voltage of the common bus. In this regard, it is the connection of battery stack to a common bus via dedicated dc–dc converter what distin-guishes fully flexible systems from the applications addressed in previous sections. This simple yet effective topological change not only allows for complete control over the battery recharging and common bus voltage but also greatly facilitates the system’s extensibility. However, even though the battery can now have a dedicated charg-er that cancels out the circulating current effect, it cannot control the common bus and its own voltage at the same time; hence, other converters need to take care over the common bus voltage regulation during the regulated charging process. Moreover, the effective capacity of the battery is no longer seen at the main terminals, as it is now replaced by the several orders of magnitude lower capacitance given only by the output filters of dc–dc con-verters. Therefore, the control design of bus-regulating converters now becomes a much more challenging prob-lem from a stability point of view. Additionally, a

communication infrastructure between converters is often adopted to coordinate and synchronize their actions in realizing functionalities such as secondary or supervi-sory control, as depicted in Figure 6.

The controllability of a singular dc bus voltage also results in the controllability of tie-line current flows toward other dc buses. Consequently, by adapting the volt-ages of respective buses, it becomes possible to control complex dc power distribution architectures. Functionally, such a structure can then be identified as a microgrid (MG), a concept that attracted considerable attention in the academic community over the past decade. The following section looks back at the origin of the MG and explores the possibilities of tailoring the results from that research field to advanced dc power distribution architectures.

Changing the Energy Paradigm: Distributed Generation and MicrogridsSince the very beginning of the introduction of distributed generation, coordination among various distributed gen-erators (DGs) was recognized as a key prerequisite not only for the full exploitation of their potential benefits, but also for avoiding negative impacts on utility. In that sense, a MG concept emerged as one of possible resolutions for efficient integration of a growing number of DGs scattered throughout the network. It is basically a small grid that gathers local loads and DGs, and it may operate in both grid-connected and islanded modes. Being an indepen-dent entity, which optimally coordinates local DGs and loads, MG was envisioned to greatly reduce the number of

Figure 6. A communication infrastructure coordinates converters.

CommunicationFlow

Communication Bus

Power Flow

Loads

Common dc Bus

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dc−dc

dc−dc

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ts

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y Controlvisor

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Distributed Generation

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nodes under the jurisdiction of distribution system opera-tors and to simplify the top-level-communication infra-structure. This is so because the internal coordination of groups of final consumers and small DGs consolidated within the intelligent MGs could be done independently from the distribution system, and the operator may only consider power exchange with the MG at the PCC.

Early MG efforts were largely focused on ac so as to line up with the existing power system infrastruc-ture. To that end, significant efforts focusing on improvement of current sharing, power quality, stability, ener-gy management, and smooth mode transitions have been undertaken to perfect and standardize the operation of inverter-based ac MGs. The topic has further expanded, even to the level of a hierarchical control classifi-cation. Hence, ac MGs began to be perceived as full-scale distribution systems compatible with the main utility. However, the initial motivation has led to a somewhat misleading judgment that the stan-dardization of MG topology and control should be carried out literally following the guidelines imposed by the large ac power systems. This is because of fundamental differ-ences between today’s technology and that at the turn of 20th century, the time when solid-state power converters did not yet exist. Indeed, the outcome of the famous Bat-tle of the Currents, which decided the global direction of power system evolution in favor of ac architecture, could have been different if they did exist. Now, inspired by new trends in electricity production and consumption as well as remarkable technological improvements in power elec-tronics, the same ac versus dc debate is taking place again. However, this time, it appears that the odds are on the side of dc, at least on the low-voltage level. Indeed, merging local dc devices into fully controllable and flexi-ble dc MGs arises as an attractive possibility for this para-digm shift.

DC Microgrids: Full-Scale Electricity Power Distribution Systems Adjusted to Modern TrendsAdvanced low-voltage dc distribution systems for house-hold and commercial appliances have been under consid-eration for quite some time in both academia and industry. Recent comparative analyses between perfor-mances of traditional ac systems and their dc counter-parts have raised a question about the most appropriate dc voltage level, which is to be adopted as a future stan-dard. However, as different types of modern consumer electronic appliances are operated on distinctive voltage levels, it is generally agreed that future dc systems should not be formed around one standardized bus, but of

multiple buses with different voltages. In that sense, 380 V is used as a rule for the high-voltage bus since it is known to match the industry standard for consumer electronics with the power factor correction circuit at the input. More-over, this voltage offers the best efficiency gains in com-parison to ac and is hence predicted to serve as the

principal distribution bus that supplies high demanding loads such as HEV chargers, washing machines, rotating ESSs, etc. A number of lower-voltage buses (48, 24, or 12 V) that power less-demanding loads such as electronic devices and LED lighting and ventila-tion are foreseen to be built upon it using dedicated power electronic interfaces. The structure that com-prises a single high-voltage bus and a number of low-voltage buses is depicted in Figure 7.

Nevertheless, when one considers a number of mutually interconnected

dc subsystems, which is preferably done on high-voltage buses (i.e., 380 V), each one of them needs to have flexible control over its internal voltage. This property may be achieved by sources whose converters are designed for voltage support, i.e., voltage–source converters (VSCs). If VSCs are programmed in a nonstiff manner, a number of sources may control the bus simultaneously. This voltage-regulating strategy is commonly referred to as the voltage droop (VD) and is used for primary control of dc buses MGs. The corresponding control law may be expressed as

,v v R id oref,MGdg = - (1)

where vdg and vref,MG are the common bus and reference voltage, respectively, io is the output current, whereas Rd is the virtual resistance, which defines the steady-state slope. As soon as it is ensured that at least one converter operates in voltage-regulating mode, other kinds of units may be connected to the same bus. In that sense, it is desirable that the RESs exploit as much renewable energy as possible and, hence, their converters are run by the respective MPPT algorithms in normal operating mode. This means that for given environmental conditions (sun and wind), the RES will follow the reference imposed by the algorithm, which is typically executed several orders of magnitude slower than inner loop controllers. Therefore, the RES can be considered a constant power source in a dynamic sense. This point is depicted in Figure 8, where one may see the operational principle of three converters connected to one common bus, with two converters being operated in VD mode (with different slopes) and one con-verter in MPPT mode.

However, if the voltage of the bus is regulated exclu-sively by the law stated in (1), its deviation from the refer-ence value is unavoidable. This feature does not represent

Tie-line current between two MGs can be regulatedby imposing the appropriate voltage drop between their buses.

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a significant problem in autonomous applications with a single bus, but in case of multibus dc systems, voltage deviations will be projected to uncontrolled tie-line cur-rent flows. To have full control over the MG, a higher con-trol level that is able to assign the correct voltage references to every bus with respect to the required cur-rent exchanges between them needs to be installed on top of the primary level.

Multi-dc Microgrid ClustersA structure that incorporates both control levels, normally referred to as primary and secondary control, is depicted

in Figure 9. It should be noted that exclusively 380-V volt-age buses are designed to participate in inter-MG current exchange, and, therefore, only they are represented in the figure. The tie-line current between two MGs can be regu-lated by imposing the appropriate voltage drop between their buses. This voltage drop can be calculated by a sec-ondary current flow controller, which will generate posi-tive or negative value (depending whether the current is regulated to enter or exit the bus) and consequently cause an increase or decrease of the respective common bus voltage. The extent to which units contribute can be actively regulated with participation factors. Apart from

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WashingMachine

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LED Lights

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Figure 7. Cascaded converters in a multibus dc microgrid.

Figure 8. Three converters connected to a common bus: two operate in VD mode, and one operates in MPPT mode.

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Vref, MG

io, VD 1

iOP1 iOP2 iOP3

io, VD 2 io, MPPT

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enforced voltage drop, droop coefficient settings and load variations also have an influence on steady-state voltage, which may then in total considerably deviate from the nominal value. For that purpose, a secondary voltage regu-lator can be deployed in parallel with current flow control-ler to restore the deviation. Naturally, not every bus can be operated at the nominal value, but the best that can be done is to restore the average voltage of all buses. There-fore, as depicted in Figure 9, two signals will form the outer voltage reference designated for primary control loop, i.e.,

vtd and .vsd

It can be noted that the secondary control in Figure 9 is designed in decentralized fashion so that every MG has a dedicated secondary controllers that are able to exchange information with its neighbors others using communica-tion infrastructure, which is normally referred to as the networked control system (NCS). Such an NCS may be realized by means of static averaging calculation or using dynamic consensus algorithms. Both of the aforemen-tioned variations are active areas of research.

Another control layer, referred to as the supervisory control or energy management system, may be incorpo-rated as well. Its functionalities are much more flexible and normally comprise decision-making mechanisms that aim to enhance the operational efficiency or to gov-ern the MG through different operational modes. One of the roles under the jurisdiction of supervisory control is to determine required current exchanges between different MGs depending on internal parameters such as SOCs of online ESS systems and/or energy available from RES.

ConclusionToday, the world has to deal with a scenario where various electronic loads have started to dominate the overall con-sumption profile. HEVs are emerging as a worthy oppo-nent to conventional vehicles, and there is no end in sight for the rising share of RESs in total electricity production. Since dc electricity is an integral part of a large portion of these modern technologies, there is a need for a reevalua-tion of the electrical distribution paradigm that was thought to be resolved in favor of ac at the turn of 20th century. In that sense, the introduction of dedicated low-voltage dc electrical distribution systems that are able to bring the new technologies together and interface them with ac utility in a more efficient and reliable manner is gradually becoming a reality.

This article examined the electrical distributions of sever-al modern dc-based industrial appliances and outlined the need for the modification of existing dc architectures to enhance their controllability and flexibility. A roadmap for this shift was proposed through the application of dc MG technology, where several control levels have been exam-ined. In line with that, a layout of a multibus dc MG with an associated hierarchical control structure that is able to regu-late the current flows between different buses with respect to nominal voltage levels has been presented.

For Further ReadingP. Fairley. (2013, May 21). Edison’s revenge: The rise of dc power. MIT Technol. Rev. [Online]. Available: http://www.technologyreview.com/news/427504/edisons-revenge-the-rise-of-dc-power/

M. Liserre, T. Sauter, and J. Y. Hung, “Future energy sys-tems: integrating renewable energy sources into the smart power grid through industrial electronics,” IEEE Ind. Elec-tron. Mag., vol. 4, no. 1, pp. 18–37, Mar. 2010.

S. Massoud Amin and B. F. Wollenberg, “Toward a smart grid: Power delivery for the 21st century,” IEEE Power Ener-gy Mag., vol. 3, no. 5, pp. 34–41, 2005.

H. Farhangi, “The path of the smart grid,” IEEE Power Energy Mag., vol. 8, no. 1, pp. 18–28, 2010.

B. T. Patterson, “DC, come home: DC microgrids and the birth of the ‘Enernet’,” IEEE Power Energy Mag., vol. 10, no. 6, pp. 60–69, 2012.

G. AlLee and W. Tschudi, “Edison Redux: 380 Vdc brings reliability and efficiency to sustainable data centers,” IEEE Power Energy Mag., vol. 10, no. 6, pp. 50–59, 2012.

D. Boroyevich, I. Cvetkovic, D. Dong, R. Burgos, F. Wang, and F. Lee, “Future electronic power distribution systems a contemplative view,” in 2010 12th Int. Conf. Optimization of Electrical and Electronic Equipment, 2010, pp. 1369–1380.

R. H. Lasseter, “MicroGrids,” in 2002 IEEE Power Engi-neering Society Winter Meeting Conf. Proc. (Cat. No. 02CH37309), vol. 1, pp. 305–308.

F. Katiraei, M. R. Iravani, and P. W. Lehn, “Micro-grid autonomous operation during and subsequent to island-ing process,” IEEE Trans. Power Delivery, vol. 20, no. 1, pp. 248–257, Jan. 2005.

J. M. Guerrero, J. C. Vasquez, J. Matas, L. G. de Vicuna, and M. Castilla, “Hierarchical control of droop-controlled ac and dc microgrids—A general approach toward standard-ization,” IEEE Trans. Ind. Electron., vol. 58, no. 1, pp. 158–172, Jan. 2011.

H. Kakigano, Y. Miura, and T. Ise, “Low-voltage bipolar-type DC microgrid for super high quality distribution,” IEEE Trans. Power Electron., vol. 25, no. 12, pp. 3066–3075, Dec. 2010.

T. Dragicevic, J. Guerrero, J. Vasquez, and D. Skrlec, “Supervisory control of an adaptive-droop regulated DCmicrogrid with battery management capability,” IEEE Trans. Power Electronics, vol. 29, no. 2, pp. 695–706, 2014.

BiographiesTomislav Dragicevic ([email protected]) is a postdoctoral researcher at Aalborg University, Denmark.

Juan C. Vasquez ([email protected]) is an assistant profes-sor at Aalborg University, Denmark.

Josep M. Guerrero ([email protected]) is a full professor at Aalborg University, Denmark.

Davor Škrlec ([email protected]) is a full professor at the Faculty of Electrical Engineering and Computing, Uni-versity of Zagreb, Croatia.

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2325-5987/14/$31.00©2014 IEEE

ISTRIBUTED ENERGY RESOURCES (DERs) OFFER ON-SITEgeneration at consumption points, which are expected to change the conventional concept of central power gener-ation. DER integration reduces transmission losses and enhances the operation reliability of distribution sys-

tems. However, distribution systems are traditionally designed as pas-sive networks in which large DER penetrations representing bidirectional power flows and topology-dependent fault currents could affect protection devices, cause danger to the maintenance personnel, and result in uncontrollable under-/overvoltage and frequency. IEEEStandard 1547 requires DER units to stop energizing the distribution system when the system is de-energized due to faults.

Microgrids are introduced to address the issues with the economics and the resilience of power delivery systems. A microgrid is a small elec-tric power system, which is connected to the utility grid through the point of common coupling (PCC), and uses on-site DERs for supplying all or some portions of local demands. When connected to the utility grid, microgrid loads are supplied by both the utility grid and on-site generation. From the utility grid side, a microgrid is seen as an aggregated controllable load. A key feature of the microgrid operation includes its seamless islanding from the utility grid and ability to be self-controlled in island mode. Once a fault affects a distribution network, local microgrids can enhance the power system reliability by switching to island mode as local DER units continue to supply the microgrid loads.



By Liang Che, Mohammad E. Khodayar, and Mohammad Shahidehpour

DOG © CAN STOCK PHOTO/3DCLIPARTSDE. MICROGRID COURTESY OF MOHAMMAD SHAHIDEHPOUR.

Protection practices of a functional microgrid system.

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Despite the numerous advantages of using microgrids, there are technical challenges regarding the control and protection of microgrids. One of the prominent challenges in microgrid operations is the design of a proper protec-tion scheme for microgrids. The integration of DERs and novel topologies embedded in microgrids would challenge the characteristics of protection schemes in microgrids as compared with those of conventional distribution sys-tems. The conventional protection strategies in distribu-tion systems rely on the radial topology of distribution networks with the supply located at one end. In this con-figuration, the fault current is provided by the utility grid with protective device (PD) settings adjusted accordingly to localize the impact of faults. PDs are coordinated based

on unidirectional power flows from the feeder toward loads in radial distribution networks, in which fault cur-rents are lower as fault locations get farther from feeders. However, these unidirectional characteristics change in microgrids. DER units located in microgrids can increase fault currents, change fault current flow paths, result in bidirectional power flows, and affect PD operations. The inclusion of DER units with power electronic interfaces, such as converters, would limit fault currents and desen-sitize PDs to faults, especially in island mode. The large difference between fault currents in grid-connected and island modes presents new challenges in microgrid fault protections. Moreover, the microgrid topology can be looped, meshed, or mixed networks, which could result in

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more complex fault current paths and affect protection strategies in microgrids.

In this article, protection system challenges in microgrids are discussed and protection practices in the context of a functional microgrid system at the Illinois Institute of Technology (IIT) are presented. We address the structure and design of the IIT microgrid and analyze technical approaches for protecting the IIT microgrid in grid-connected and island modes.

Challenges in Microgrid Protection SystemsConventional protection schemes for radial distribution networks cannot be applied to microgrids without major modifications. Such modifications would require address-ing the impact of DER integration, microgrid topology, and fault current levels in grid-connected and island modes. In this section, the challenges and possible solutions to microgrid protection are discussed.

ChallengesThe integration of DER units would impose major challenges in microgrid protection schemes. The conventional distribu-tion system protection is designed for radial distribution net-works that include feeders at one end with high fault currents. In radial distribution networks, fault currents always flow downstream, i.e., from utility feeders toward fault locations. As a single source of power generation, utility feeders provide high fault currents, which trigger PDs along feeder paths. However, traditional protection schemes face the following fundamental challenges in microgrids.

Fault Current-Level ModificationsFault currents depend on microgrid operation modes. In grid-connected mode, utilities contribute to microgrid fault currents while, in islanded mode, microgrids’ potential fault currents are lower. The fault current injection capabil-ity of DERs with power electronic interfaces is limited to twice their rated currents, and lower fault currents would not trip overcurrent (OC) relays. In traditional distribution

networks, fault currents decrease as feeder impedances increase when fault points shift downward along feeder paths; however, microgrid DERs contribute to fault cur-rents along feeder paths. DER units, especially generators with rotating prime movers, such as synchronous or induction generators, would have higher contributions to fault currents when compared with DERs with power elec-tronic interfaces. As fault current paths could be different in grid-connected and island modes, the two operation modes would require different relay settings. As a result, fixed settings for microgrid relays may become impractical as the dynamic behavior of DERs may also affect the coor-dinated settings of relays.

Impact of DERs on the Operation of Protective DevicesDER units have plug-and-play characteristics in microgrids, which may require modifications to traditional relay set-tings. In such cases, DER locations and fault currents would determine precise relay settings. The impact of DERintegration on PD operations is summarized in the follow-ing two categories:

Malfunction of PDs due to downstream faults: In a downstream fault, shown in Figure 1(a), utility grid and DER unit currents (Ig and ,IDER respectively) con-tribute to the total fault current. If IDER is large enough, Ig will be reduced because of a higher voltage contrib-uted by IDER at PCC. Thus, PD1 may not trip because of a lower fault current even though feeder 1 experienc-es a higher fault current.Sympathetic tripping: In Figure 1(b), PD3 should trip to clear the fault. However, if the DER unit contribution to the fault current is large, PD2 may trip in response to high current ,IDER which would disconnect feeder 2 from the utility grid.

Impact of Microgrid Topology on the Coordination of Protective DevicesThe looped or meshed networks in microgrids will affect fault current magnitudes and directions. For example, the fault current in a loop is divided between two parallel paths. Hence, PDs on the upstream feeder may have cur-rents that are twice as large as that in each fault path within a loop. Accordingly, looped or meshed structures in microgrids could impact the PD coordination.

Possible Solutions for Relay Coordination

Balancing DER Technologies for OC ProtectionA possible solution to overcome low contributions of DERunits to fault currents in microgrids is to balance DER unit contributions with those of other generation technologies by introducing generating units with higher fault currents to increase total fault currents in microgrids to proper lev-els that could be detected by OC protection systems. Syn-chronous generators, including permanent magnet

UtilityGrid

UtilityGrid

MissingOperation

SympatheticTrippingIg Ig

IDER IDER

DERDER

Feeder 1 Feeder 1 Feeder 2

PD1 PD1

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PD3

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Figure 1. The impact of DER units on relay operation. (a) The malfunction of PDs due to downstream faults and (b) the sympathetic tripping of PD.

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synchronous generators (PMSGs), and fly wheels are suit-able choices for increasing fault currents in microgrids.

Differential Protection SchemesDifferential protection schemes are based on coupled dif-ferential directional relays that can accurately locate and isolate faults without affecting other components in distri-bution systems. Differential protection schemes, which incorporate traditional protection technologies, are suited for microgrid protections in both grid-connected and island modes. Differential protection schemes are either central-ized (monitored and coordinated by central controllers) or localized (based on local communications among relays). In centralized schemes, central controllers monitor the microgrid network topology and operation settings of PDs and send tripping commands to PDs once faults are detect-ed. Centralized schemes provide more accurate results with rather unacceptable time delays for performing the compu-tations required by the central controllers. Localized schemes, which are more readily adopted for industry applications, allow for direct communication among relays with the fastest response to faults.

Adaptive Protection SchemesThe difference between fault currents in grid-connected and island modes would necessitate adaptive protection

schemes in microgrids. Adaptive schemes would include two sets of relay settings, one for grid-connected and the other for island mode. Relays would select proper settings when microgrids switch their operation modes. In island mode, the time-OC (TOC) characteristic curve of relays will be shifted to instantaneous and/or definite-time OC set-tings to adapt to lower fault currents. Moreover, adaptive protection schemes would automatically adjust the relay settings according to the network operating state. For example, a voltage restraint OC protection scheme would reduce the time dials (tripping delays) of relays in cases of large voltage depressions.

Protection Schemes Based on Other Parameter MeasurementsVoltage- or harmonic-based detection techniques are con-sidered as alternatives once low fault currents render tra-ditional OC protection schemes impractical in island mode. The voltage-based protection schemes would locate faults by detecting the “d-q” components of voltage distur-bances based on the Park transformation. However, the voltage-based detection schemes may not provide accu-rate fault detections, and undesirable time delays would be introduced by additional computation and filtering. Thus, this protection scheme is usually used in combina-tion with other fault-detection and protection schemes.

Utility Grid12.47 kV

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Figure 2. The IIT microgrid protection system.

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IIT Microgrid Topology and ComponentsIIT owns and operates its campus underground distribution network. Figure 2 shows the topology of the 4.16-kV microgrid, which is fed through two substations. The north substation (NS) and south substation (SS) are connected through a cable to facilitate seamless operation in case of a failure in one of the utility feeders within the IIT substa-tions. The IIT microgrid features a high-reliability distribu-tion system (HRDS) with phasor measurement units to enhance reliable operation of the campus microgrid. Seven distribution loops are implemented by integrating HRDSVista switches, which connect DERs [gas turbines, solar photovoltaic (PV), wind generation, and battery storage] with load entities (building loads and charging stations). The IIT microgrid is equipped with building automation technologies (building controllers, subbuilding controllers, and controllable loads) for energy efficiency and demand response throughout the microgrid.

Vista-E in Figure 2 is a three-way switch in loop 1. Two ways, which are denoted as loop-ways of a Vista switch (Vis-ta-E-1 and Vista-E-2), are equipped with loop PDs. The third way (Vista-E-3), denoted as a load-way, is equipped with a load-way PD, which connects the loads or DER units to the microgrid distribution network. The individual loops are con-nected to the substations via a pair of loop-feeder PDs (A and B in Figure 2). The substation is supplied by the 12.47-kV/4.16-kV delta-wye transformer via substation PDs. The natural gas turbine synchronous generator is connected to the SSthrough generator PDs, and the NS and SS are connected by a cross-tie cable.

Adaptive Protection Schemes in the IIT Microgrid

Hierarchical Protection Scheme for the MicrogridThe hierarchical protection scheme of the IIT microgrid is shown in Figure 3. The scheme is based on localized dif-ferential protections in seven loops and four coordinated protection levels, which are implemented by communica-tion-assisted digital directional relays and HRDS switches. The fundamentals of the effective protection scheme at the IIT microgrid are categorized in the following sections.

Balancing the DER Technologies to Contribute Sufficient Fault Currents in Island ModeIn the IIT microgrid, the synchronous generator can pro-vide sufficient fault currents in island mode. Two cases are simulated in power system computer-aided design (PSCAD) to verify fault current contributions of the syn-chronous generator. The first case considers island mode, in which the synchronous generator operates in conjunc-tion with other DERs, while in the second case, the syn-chronous generator operates in parallel with the utility grid to serve the 8 MW of campus load. In each case, a sin-gle-phase-to-ground fault is applied on different sections of the loops. The fault currents associated with fault loca-tions are listed in Table 1. Since the peak load supplied by a single loop is fewer than 3 MW, the maximum current in normal operation that passes through the cables within each loop is fewer than 0.25 kA when both loop-feeder breakers “A” and “B” are closed (see Figure 2). Once a loop-feeder breaker opens, the maximum current in normal

Microgrid Protection Principle

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Figure 3. The hierarchical protection principle of the IIT microgrid.

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operation flowing through the cables in each loop is fewer than 0.5 kA. Thus, the fault current magnitude in island mode (case 1 in Table 1) is adequate to trigger OC PDs. Moreover, loops 1–3 are directly connected to NS while loops 4–7 are connected to the SS, so the utility grid con-tributes more to fault currents through NS for faults locat-ed in loops 1–3 than those located in loops 4–7 as shown in Table 1. Similar-ly, the utility grid would provide higher currents through the SS to faults located in loops 4–7 than those locat-ed in loops 1–3.

Localized Differential Protection Scheme Implemented by Communication-Assisted Directional OC RelaysThe differential protection scheme can be centralized or localized. The IITmicrogrid uses the localized differential protection scheme as the centralized control suffers from time delays. The Vista switches installed within the loops are equipped with communication-assisted directional OC relays. The two relays at each end of a loop section are equipped with optical fiber communication, which facilitates fast (2 ms) and highly reliable communication capability between them.

Adaptive Relay Settings for Grid-Connected and Island ModesAs the fault current level shown in Table 1 reduced in island mode, the communication-assisted OC relays in the IIT microgrid can change the settings upon receiving the islanding signal from the master controller (MC). The relays switch to instantaneous/definite-time OC protec-tion scheme, considering the fault current levels in island mode, to ensure a fast response to lower fault currents.

Loop Structure to Facilitate Hierarchical Protection and Increase Service ReliabilityThe loop structure provides an uninterrupted electricity sup-ply when one section of the loop is isolated because of a fault. The IIT microgrid features a hierarchical protection structure to enhance the protection reliability. The loop PDs in Figure 2 not only clear the faults within the loop without any interruption to loads but also provide backup protection to the load-way PDs in case a load-way fault occurs. If the load-way and loop-level pro-tection fails to clear the faults within a loop, the entire loop is isolated quickly by respec-tive loop-feeder relays; thus, an uninter-rupted and reliable supply to other healthy loops is ensured. The hierarchical protec-tion strategy at the IIT microgrid is present-ed in the “Protection Strategy” section.

Protection StrategyIn Figure 3, the microgrid protection is divided into four levels: the load-way level, loop level, loop-feeder level, and microgrid level. The protection devices and operation rules in each level are summarized in Table 2. The detailed protection strategy of each level will be discussed next in

this section.

Load-Way ProtectionThe green blocks in Figure 2 denote load-way directional OC digital relays, which clear load-way faults. Figure 4 shows a section of loop 1 with Vista switches B, C, and D. In this figure, the black dashed arrow indicates the posi-tive flow direction on each loop PD. The red, bold arrow denotes the fault current direction. In this figure, the load-way protection and its backup protection are shown. In Figure 4(a), once a fault at the load-way of Vista switch C is cleared by the load-way PD

(C3), the campus building connected to the Vista switch Cwill be isolated. If the breaker at C3 fails, relay C3 will immediately send transfer trip signals to C1 and C2, which are mounted on the same Vista switch. Figure 4(b) shows the pair of loop PDs in Vista C (C1 and C2), which provide backup protections for C3. Should this backup protection operate, the buildings connected to Vista C will be isolated. The load-way PDs can be programmed up to four shots of automatic reclosing. The load-shedding and other control schemes could also be implemented on the load-way pro-tection level based on under/overvoltage and under/over-frequency functions of these relays.

Loop ProtectionThe communication-assisted digital directional relays (blue blocks) in Figure 2 are implemented on the loop-way of Vista switches to provide differential protections at loop levels. Figure 5 shows the same section shown in Figure 4 to present the loop protection schemes when faults occur in a loop section between Vista switches C and D. In this figure, there is a communication channel between cou-pled relays on both sides of each cable segment (C1 and

TABLE 1. The Fault Currents (rms) at the IIT Microgrid.

Fault Location

Case 1 :Islanded Mode

Case 2 :Grid-Connected Mode

PCC at NS PCC at SS

Loops 1–3 3 kAa ~ 4 kAb 12 kAa ~ 15 kAb 8 kAa ~ 9 kAb

Loops 4–7 8 kAa~ 9 kAb 12 kAa~ 15 kAb

aFault current is lower when the fault is close to the middle point of the loop.bFault current is higher when the fault is close to the loop feeder. (All currents are calculated for single-phase to ground fault.)

Microgrids are introduced to address the issues with the economics and the resilienceof power delivery systems.

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D2) for facilitating the permissive overreaching transfer trip (POTT) protection scheme.

In Figure 5(a), when a fault occurs in a segment within a loop, relays within the loop will sense the fault current. The relays sensing the positive directional fault current (D2, C1, and B1) will send permissive signals to their cou-pled relays (C1, D2, and C2), respectively. In this case, only the coupled relays D2 and C1 will clear the fault because each would sense a positive fault current and receive permissive signals. The tripping crite-rion is because both coupled relays detect positive directional fault cur-rent, which indicates that the fault has occurred within the loop section located between them. Figure 5(a) shows that once D2 and C1 cleared the fault, the loop is converted into two parallel feeders and the loop structure is changed to a radial net-work without any load interruptions.

The backup protection operates if a POTT scheme fails (e.g., breaker at C1 fails). In Figure 5(b), once the breaker failure is detected, C1 will send a transfer trip signal to C2 to open the breaker at C2. Here, an outage will occur in buildings fed by Vista switch C while other load points in the same loop will not be affected. Directional

relays eliminate traditional coordination time intervals for primary protections and facilitate an accurate fault-locating scheme within a loop. The load-way and loop relays are high-speed digital relays with an operating time of fewer than 1 cycle (exclusive of the relay’s time delay and the breaker operating time). Thus, very high-speed and accu-rate protections are implemented at the load-way and loop protection levels of the IIT microgrid.

Loop-Feeder ProtectionTable 2 shows that the loop-feeder pro-tection is the upper level of the loop protection, which acts as a backup pro-tection for the entire loop. When a fault in the load-way or loop results in the failure of load-way and loop pro-tection schemes (e.g., loss of commu-nication between PDs or any PDfailure), the loop on outage will be iso-lated by the backup protection provid-ed by loop-feeder PDs. Loop-feeder relays (purple blocks in Figure 2) are nondirectional OC relays, which are set to be slower than load-way and loop relays and faster than substation relays. The proposed setting prevents

nuisance tripping and ensures that faulted loops are iso-lated before substation relays get to operate.

TABLE 2. The Protection Devices and Operation Rules at Each Protection Level.

Protection Level Protection Devices and Operation Rules in Grid-Connected and Island Modes

Load-wayprotection

DOCa digital relay with adaptive relay setting (responding to lower fault current in island mode):—Operates only in load-way faults (DOC and autoreclosing).

Loopprotection

DOCa digital relay with adaptive relay setting:—Operates in loop faults [primary and backup permissive overreach transfer trip (POTT) schemes]—Backup protection for load-way protection.

Loop-feederprotection

OCb relay:—Operates to isolate the faulted loop only when the load-way and loop protections have failed within the loop.

Microgrid-levelprotection

OCb relay and PCC switch:

In grid-connected mode:—Unintentional islanding operation due to external fault or disturbancebased on the signal from the MC—OCb relay (backup protection for the entire microgrid)—Intentional islanding operation based on the islanding command from the MC.

In island mode:—Resynchronization initiated by a command from the MC.

aDOC: directional OC.bOC: nondirectional OC.

A key feature of the microgrid operation includes its seamless islanding from the utility grid and ability to be self-controlled in island mode.

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Microgrid-Level ProtectionThe microgrid-level protection includes PDs for substa-tions and synchronous generators, which are equipped with nondirectional OC relays for backup protection. When the microgrid is in grid-connected mode, the OCrelay and the PCC switch located at the substation can operate in one of the following scenarios:

Unintentional islanding as a result of external disturbanc-es: This operation is to protect the IIT microgrid against utility network outages as shown in Figure 6. In the case of external outages, the utility PD (PD1 in Figure 16) would trip to isolate the fault, leading to an uninten-tional islanding of the IIT microgrid. Once any utility-side voltage and frequency deviations are detected, the microgrid MC will send a command to open the PCCswitch and isolate the microgrid.

Figure 5. The (a) loop POTT and (b) backup scheme.

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Figure 4. The (a) load-way and (b) backup protection.

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32

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32

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2 13

2

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32 1

32

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332

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FailedTripped

BackupTripped

Outage

(a) (b)

POTT

External Fault orDisturbance on Utility

Microgrid

Signalfrom MC

Substation Relayand PCC Switch

Utility PD

Figure 6. The unintentional islanding of the microgrid due to a utility disturbance.

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Nondirectional OC relay: If the primary protection fails to clear a microgrid fault or the PCC switch does not respond to the MC’s command to isolate a utility fault, the PCC switch will ultimately open in response to the substation OC relay. This relay should have a suffi-cient time-delay for the operation of all protection schemes in the load-way, loop, and loop-feeder levels.Intentional islanding and resynchronization initiated by the MC: This operation is controlled by the MC for intentional islanding of the microgrid and does not apply to any faults.

In the IIT, two synchronous generators are directly con-nected to the SS. In island mode, a synchronous generator should remain connected, at least for a short period, to provide sufficient fault currents for PD operations at other protection levels; hence, the OC relay of synchronous generator has a longer time delay than that of the substa-tion protection.

DER SwitchesFigure 7 shows that renewable energy resources (PV and wind) are connected via a controlled DER switch to the load-way PD of Vista switches. In this figure, once the relay E3 detects the microgrid isolation, it will send a transfer trip signal to the DER switch to open. This function prevents an uncontrollable under-/overvoltage or frequen-cy according to IEEE Standard 1547, which requires DERunits to be disconnected when the microgrid is de-energized. Unlike renewable energy resources, the battery storage supplies the campus load when there is a loop fault. If a campus building or loop connected to the battery storage is isolated, the MC will send signals to dis-charge the battery storage in the building or loop. The duration of battery storage discharge is dependent on the available energy at the isolation instant.

Protection Coordination in the IIT Microgrid

Coordination Based on Operation Curves of RelaysFigure 8 shows the TOC curves of relays in grid-connected and island modes. In this figure, load and loop curves denote the TOC curves for load-way and loop relays, which clear the load-way and loop faults, respectively. The feeder and substation curves denote the TOC curve for the nondi-rectional OC relays at the loop-feeders and substation. Based on the adaptive protection scheme discussed in the “Hierarchical Protection Scheme for the Microgrid” section, once the microgrid changes its operation to island mode, the MC would send a signal to the load-way and loop relays to switch to the instantaneous/definite-time OC scheme as shown in Figure 8(b). This enables the load-way and loop relays to respond to lower fault currents in the island mode.

Coordination Considering Special Cases in LoopsSince the fault on a closed-loop IIT microgrid system will always be fed through two paths from substations, the relay coordination for a looped distribution network dif-fers from that of a radial network. To evaluate the protec-tion coordination in a loop, two extreme cases are investigated in loop 1, as shown in Figure 9.

1) Equidistance loop fault: The equidistance loop faults occur half-way between the loop-feeder breakers (e.g., at point 1 in Figure 9). In this case, as the fault current is split equally between the two paths in the loop (I a

fault1

and ),I bfault1 the loop and loop-feeder relays will detect

approximately 50% of the total fault current and the substation relays will detect the entire fault current.

Vista-ELoop PD

Loop 1

Load-Way PD

DERSwitchPV

Eng. 1

Transfer Trip

1 2

3

DERSwitchPV

T

Figure 7. The DER switches control.

0.1 1 100.01

0.1

1

10

100

Current (kA)

LoadLoop

Feeder

Substation

Grid-Connected Mode

0.1 1 10Current (kA)

(a) (b)

Tim

e (s

)

0.01

0.1

10

1

100

Tim

e (s

)

Load

Loop

Feeder

Substation

Island Mode

Figure 8. The TOC characteristics of relays in (a) grid-connected and (b) island mode.

Load-Way PDLoop PDLoop-Feeder PD (OC Relay)

B A I 2a

I 1a

I 2bF1F2

FaultFault

I 1bFault Fault

2

Vista-D Vista-C Vista-BVis

ta-E

Vis

ta-A2

2

3

3

1

1 23

1 2

2

3

3

11

12

1

Figure 9. The equidistance and weak-infeed faults in loop 1.

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Therefore, the loop and loop-feeder relays must clear 50% of the fault current when coordinated with the substation relay.

2) Weak-infeed loop fault: The weak-infeed loop faults occur immediately downstream of the loop-feeder breakers along the loop (e.g., at point 2 in Figure 9). In this case, the substation relay, loop-feeder relay A, and loop relay F1 will sense nearly the entire fault current ( ),I a2

fault while loop-feeder relay B and other loop relays will sense only a small portion of the fault current ( ) .I b2

fault In this extreme case, the loop-level POTT scheme, provided by coupled loop relays A1 and F1, may fail because of the low fault current flowing through A1 and the loop-feeder relay A will trip to provide the backup protection (nondirectional OC protection). Once the loop-feeder relay A has tripped, loop-feeder relay B will detect the fault current and trip subsequently to isolate the entire loop. This procedure for clearing the fault would take twice as much time as that of the loop-feed-er-level protection. The substation relay always detects the fault current. However, it is important to make sure that the loop-feeder-level time delays are less than half of that of the substation relays. This procedure is shown in a simulation in the “Adaptive Protection Schemes in the IIT Microgrid” section.

Simulation Results for Microgrid ProtectionThe IIT microgrid is modeled in Figure 2, and single-phase to ground faults are applied in loop 1. All faults are bolted (low-impedance) faults. Here, OC (directional and nondirectional) protection schemes are only considered. Figures 10–16 show the instantaneous voltage and current curves. Table 3 shows the typical operating times for the key protection devices in

the IIT microgrid. In this section, the following cases are pre-sented to simulate the protection schemes discussed in the “Adaptive Protection Schemes in the IIT Microgrid” and “Pro-tection Coordination in the IIT Microgrid” sections.

Case A: Protection in grid-connected mode ■ A1: load-way fault ■ A2: loop fault.

Case B: Protection in island mode ■ B1: load-way fault ■ B2: loop fault.

Case C: Protection in weak-infeed loop fault.

Case A: Protection in Grid-Connected Mode

A1: Load-Way FaultThis case shows how the protection schemes clear a load-way fault in grid-connected mode. Here, the IIT microgrid is connected to the utility grid through the NS, and the syn-chronous generators are disconnected according to the ter-tiary control signal provided by the MC. A single-phase to ground fault occurs at t = 1 s on the load-way at Vista C in

Figure 10. The simulation results when the synchronous generator is disconnected in Case A1. (a) The fault is cleared by the load-way PD. (b) The load-way PD has failed to clear the fault, which was cleared by the backup protection provided by loop PDs.

v_vista-C

i_fault

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i_fault

i_relay-C1

i_relay-C2

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30

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(kA

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x 0.90 1.00 1.10 1.20 1.30x

(a) (b)

TABLE 3. The Operating Time of Key Protection Devices Applied at the IIT Microgrid.

Cycles Seconds

Operating time of load-way and loop relays

Dropout time of load-way and loop relays

Operating time of medium-voltage circuit breakers

<1

1

3

0.01

0.017

0.05

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D2 Tripped;C1 Failed

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)

4.0

–4.0

(kV

)(k

A)

(kA

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20100

–10–20

(kA

)

x

(b)

Figure 12. The simulation results when the synchronous generator is disconnected in case A2. (a) The fault is cleared by the POTT scheme. (b) The fault is isolated by the backup loop PDs once the POTT scheme has failed.

Fault IsApplied

v_vista-C

i_fault

i_grid

i_gen

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2010

–10–20

2010

–10–20

0

0

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and C2

30

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2010

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2010

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0

2010

–10–20

(kA

)

(kA

)(k

A)

x

(a)

2.90 3.00 3.10 3.20 3.30x

(b)

Figure 11. The simulation results when P 4=SG MW in case A1. (a) The fault is cleared by the load-way PD. (b) The load-way PD failed to clear the fault, which was cleared by the backup protection provided by loop PDs.

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loop 1 (see Figure 2). Figure 10 shows the instantaneous simulation results for the faulted phase. Here, v_vista-C is the voltage at Vista C, and i_fault, i_relay-C1 and i_relay-C2 are the fault current and relay C1 and relay C2 currents. In Figure 10(a), the fault is cleared by the load-way PD installed at Vista C. In this figure, the fault current of the load-way of Vista C is about 13 kA (rms), which triggers the load-way relay to clear the fault in less than 0.1 s. This time includes the time-OC delay and operating times of the relay and breaker. In Figure 10(b), it is assumed that the load-way PD has failed to clear the fault and the fault is cleared by the backup protection provid-ed by the two loop PDs at Vista C. In this figure, the fault clearing time is about 0.16 s, which is the total operating time of the primary and backup protections. Figure 10(b) shows the current for the two loop PDs (C1 and C2). Both scenarios result in building outages at Vista C;

however, the duration of the fault is much shorter when the fault is cleared by the load-way PD.

Figure 11 shows the results when the same fault has occurred at t = 3 s and the synchronous generator sup-plied 4 MW of the campus load according to the tertiary control sig-nal. The synchronous generator will also contribute to the fault current. Here, i_grid and i_gen are the cur-rents of the utility grid and the syn-chronous generator. Figure 11(a) and (b) shows the scenarios in which the faults are cleared by load-way PDand the backup loop PDs. In these figures, the utility grid contributes about 12 kA (rms), and the synchro-nous generator contributes 3 kA (rms) to the total fault current.

A2: Loop FaultThis case shows how the POTTscheme and its backup protection

Fault IsApplied

v_vista-C

v_vista-D

i_fault

i_relay-C1

i_relay-D2

i_grid

4.0

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0.0

30

0

–30

20100

–10–20

2.90 3.00 3.10 3.20 3.30

Fault IsApplied


Fault IsIsolatedby Backup(D2-C2)

Fault Is FedThroughVista C


(kV

)

4.0

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)(k

A)

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(kA

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20100

–10–20

(kA

)

i_gen20100

–10–20

(kA

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x

(a)

v_vista-C

v_vista-D

i_fault

i_relay-C1

i_relay-D2

i_grid

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2.90 3.00 3.10 3.20 3.30

(kV

)

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A)

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–10–20

(kA

)

20100

–10–20

(kA

)

i_gen20100

–10–20

(kA

)

x

(b)

Figure 13. The simulation results when P 4=SG MW in case A2. (a) The fault is cleared by the POTT scheme. (b) The fault is isolated by the backup loop PDs once the POTT scheme has failed.

Differentialprotection schemes are based on coupled differential directional relays that can accurately locate and isolate faults without affecting other components in distribution systems.

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Fault IsApplied

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i_relay-D2

4.0

–4.0

2.90 3.00 3.10 3.20 3.30

4.0

–4.0

i_gen

(b)

Figure 15. The simulation results in case B2. (a) The fault is cleared by the POTT scheme. (b) The fault is isolated by the backup loop PDs once the POTT scheme has failed.

Fault IsApplied

v_vista-C

i_fault

4.0

–4.0

10.05.0

–5.0–10.0

0.0

0.0

Fault IsApplied


Fault IsClearedby C1and C2

(kV

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A)

i_gen10.05.0

–5.0–10.0

0.0(kA

)

2.90 3.00 3.10 3.20 3.30x

(a)

v_vista-C

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i_relay-C1

i_relay-C2

4.0

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2.90 3.00 3.10 3.20 3.30

(kV

)

10.05.0

–5.00.0

–10.0

10.05.0

–5.00.0

–10.0

10.05.0

–5.00.0

–10.0

10.05.0

–5.00.0

(kA

)(k

A)

(kA

)(k

A)

i_gen

x

(b)

Figure 14. The simulation results in case B1. (a) The fault is cleared by the load-way PD. (b) The load-way PD failed to clear the fault, which is cleared by the backup protection provided by loop PDs.

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scheme clear a loop fault in grid-connected mode. Here, we assume that the IIT microgrid is connected to the utili-ty through the NS and that the synchronous generator is disconnected according to the tertiary control signal. A single-phase to ground fault occurs at t = 1 s in the loop section between Vista C and Vista D (see Figure 2). Figure 12(a) shows that the fault is cleared by the POTT scheme of coupled PDs within this section. Since the fault location is close to the middle of the loop, both D2 and C1 detect about 7 kA (rms) fault current, so the fault is cleared in fewer than 0.1 s without any interruption to the electricity supply of the campus buildings. Figure 12(b) shows that once the POTT scheme fails, the back protection scheme isolates the fault. In this figure, D2 has operated success-fully; however, C1 has failed and its backup PD (C2) has been triggered to clear the fault. In Figure 12(b), only one side of the loop (Vista C) supplies the fault current between t = 1.09 s and t = 1.17 s; therefore, during this period, the current flowing through relay D2 is reduced to zero while the current in relay C1 is increased, and the total fault current is reduced from 14 kA (rms) to 12 kA (rms). At 1.17 s, the fault is isolated by D2 and C2, and there is an outage in the building connected to the Vista C. In Figure 13, we assume the same fault occurs at t = 3 s with the synchronous generator supplying 4 MW of campus load according to the tertiary control sig-nal. In this case, the synchronous generator will also contribute to the fault current. Figure 13(a) and (b) shows the fault being cleared by the POTT scheme and its backup protec-tion, respectively. In these figures, the utility grid contributes about 12 kA (rms) and the synchronous generator contributes 3 kA (rms) to the total fault current.

Case B: Protection in Island ModeHere, the island mode protection is discussed. In this case, since the fault current level is reduced, the MCsends signals to the load-way and loop PDs to change their relay settings to island mode.

B1: Load-Way FaultThis case shows how the protection scheme clears a load-way fault in island mode. A single-phase to ground fault occurs at t = 3 s on the load-way at Vista C in loop 1 (see Figure 2), and the fault current is mainly provided by synchronous generator. In Figure 14(a), the fault is cleared by the load-way PD installed at Vista C. The fault current on the load-way of Vista C is about 3.2 kA (rms) as shown in this figure, and the load-way relay clears the fault in less than 0.1 s. This time delay includes the instantaneous/definite time delay of relay and the

breaker operating time. In Figure 14(b), it is assumed that the load-way PD has failed to clear the fault and the fault is cleared by the backup protection provided by the two loop PDs at Vista C. In this figure, the fault is cleared by the backup protection after about 0.16 s, which is the total operating time of the primary and backup protections. Both scenarios result in building outages connected to Vista C. Compared to Case A1, the

fault current in Figure 14 is signifi-cantly reduced in the island mode.

B2: Loop FaultThis case shows how the POTT and its backup protection schemes clear a loop fault in the island mode. A single-phase to ground fault occurs at t = 3 s on the loop section between Vista C and Vista D (see Figure 2), and the fault current is mainly provided by the synchronous generator. In Figure 15(a), the fault is cleared by the POTT scheme of coupled PDs (C1 and D2) in this loop section. Since the fault location is close to the middle of the loop, both D2 and C1 detected about 2 kA (rms) fault current and the fault is cleared in fewer than

0.1 s without any supply interruption to the campus build-ings. Figure 15(b) shows the case in which the fault is isolated by the backup loop PDs once the POTT scheme has failed. In this figure, breaker D2 successfully operated while C1 failed. The backup breaker at C2 is triggered to isolate the fault about 0.18 s after the fault is applied. As shown in Figure 15(b), between 3.09 s and 3.18 s, only one side of the loop (Vista C) still supplies the fault current, so during this period, the current passing through relay D2 reduces to zero while the current passes through C1 increases, and the total fault current is reduced from about 4 kA (rms) to 3.1 kA (rms). In Figure 15(b), there is an outage in the loads connected to Vista C as it is isolated from the loop. Compared to Case A2, the fault current is significantly reduced in island mode.

Figure 16. The simulation result in case C (weak-infeed loop fault).

Fault IsApplied

LowCurrent

ThroughLoop

PD A1

Fault IsIsolatedbyFeedersA and B

Feeder ATripped

Feeder BTripped

i_fault

i_feederA

i_feederB

30

30

30

–30

–30

–30x

0.80 1.20 1.60 2.00 2.40

(kA

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A)

(kA

)

The difference between fault currents in grid-connected and island modes would necessitate adaptive protection schemes in microgrids.

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Case C: Protection in Weak-Infeed Loop FaultIn this case, we assume that the microgrid operates in grid-connected mode and a single-phase-to-ground fault occurs at t = 1 s on loop 1 immedi-ately after loop-feeder A (see Figure 9). The total fault current and fault cur-rents through loop-feeders A and B are shown as i_fault, i_feederA, and i_feederBin Figure 16, The loop POTT protection scheme failed because of low-fault cur-rent sensed by loop PD A1. This small fault current is shown by i_feederB from 1 s to about 1.6 s as marked in Figure 16. As a backup pro-tection for loop 1, the nondirectional OC relay at loop-feeder A trips at 1.6 s after 0.6 s delay. This time delay includes the relay and breaker operating time and time-OC delay of relay A. The entire fault current flows through loop-feeder B in 1.6–2.2 s, which triggers the nondirection-al relay at loop-feeder B after 0.6 s delay at 2.2 s. The total fault current is lower in 1.6–2.2 s compared to 1–1.6 s, because of the higher loop impedance in the latter period.

ConclusionIt is shown that the hierarchical protection strategy based on the communication-assisted directional OC relays and the localized differential scheme would provide efficient protec-tion schemes for the IIT microgrid in both grid-connected and island modes. The communication-assisted relays adopt adaptive settings for their operation to respond to the higher fault currents in grid-connected mode and lower fault currents in island mode. The synchronous generator in the microgrid provides sufficient fault current for the implemen-tation of the OC-based protection strategy. The simulation results for grid-connected and island modes demonstrated the effectiveness of the proposed protection scheme.

AcknowledgmentsThis project was partially supported by the U.S. Depart-ment of Energy under grant DE-FC26-08NT02875.

For Further ReadingM. Shahidehpour, M. E. Khodayar, and M. Barati, “Campus microgrid: High reliability for active distribution systems,” in Proc. IEEE Power Energy Society General Meeting, July 2012, pp. 1–2.

M. Shahidehpour and M. E. Kho-dayar, “Cutting campus energy costs with hierarchical control: The eco-nomical and reliable operation of a microgrid,” IEEE Electrification Mag., vol. 1, no. 1, pp. 40–56, Sept. 2013.

M. E. Khodayar, M. Barati, and M. Shahidehpour, “Integration of high reliability distribution system in microgrid operation,” IEEE Trans. Smart Grid, vol. 3, no. 4, pp. 1977–2006, Dec. 2012.

Perfect power prototype at Illi-nois Institute of Technology. [Online]. Available: http://www.iitmicrogrid.net

A. Flueck and Z. Li, “Destination: Perfection,” IEEE Power Energy Mag., vol. 6, no. 6, pp. 36–47, Nov. 2008.

T. Horan, J. K. Niemira, and J. F. Clair. (2010). Detailed functional specification and analytical studies results for high reliability distribution system (HRDS) of Illinois Insti-tute of Technology, S&C Electric Company, Project No. 3568 and 3953. [Online]. Available: http://www.sandc.com

G. Tsai. (2011). Perfect power system—Design of the SCADA system for the high reliability distribution system at Illinois Institute of Technology, S&C Electric Company. [Online]. Available: http://www.ieeechicago.org/LinkClick.aspx?fileticket=NDa3t6rGHig%3D&tabid=1559

SEL-351 optimize protection, automation, and breaker control. [Online]. Available: https://www.selinc.com/workarea/downloadasset.aspx?id=5527

IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems, IEEE Standard 1547–2003, pp. 7, 2003.

Biographies Liang Che ([email protected]) is with the Electrical and Computer Engineering Department, Illinois Institute of Technology, Chicago.

Mohammad E. Khodayar ([email protected]) is with Department of Electrical Engineering, Southern Methodist University, Dallas, Texas.

Mohammad Shahidehpour ([email protected]) is with the Electrical and Computer Engineering Department, Illinois Institute of Technology, Chicago.

The IIT microgrid uses the localized differentialprotection scheme as the centralized control suffers from time delays.

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http://www.iitmicrogrid.net

http://www.sandc.com

http://www.ieeechicago.org/LinkClick.aspx?fileticket=NDa3t6rGHig%3D&tabid=1559

https://www.selinc.com/workarea/downloadasset.aspx?id=5527








By Aris Dimeas, Stefan Drenkard, Nikos Hatziargyriou, Stamatis Karnouskos, Koen Kok, Jan Ringelstein, and Anke Weidlich

2325-5987/14/$31.00©2014IEEE IEEE Electr i f icat ion Magazine / MARCH 2014 81

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RIVATE HOUSEHOLDS CONSTITUTE A CONSIDERABLE SHARE OFEurope’s electricity consumption. The current electricity distribution sys-tem treats them as effectively passive individual units. In the future, how-ever, users of the electricity grid will be involved more actively in the grid operation and can become part of intelligent networked collaborations.

They can then contribute the demand and supply flexibility that they dispose of and, as a result, help to better integrate renewable energy in-feed into the distribution grids.

To achieve energy efficiency and sustainability, a novel smart grid information and commu-nication technologies (ICTs) architecture based on smart houses intelligently interacting with


Developing an interactive

network.

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smart grids is needed. Along these lines, the European Com-mission cofunded the research project SmartHouse/Smart-Grid (SH/SG) (see www.smarthouse-smartgrid.eu), a consortium of leading parties in ICT for energy, has adopted an innovative approach. The ICT architecture developed by the consortium introduces a holistic concept and technology for smart houses as they are situated and intelligently man-aged within their broader environment (see Figure 1). The approach treats smart homes and buildings as proactive cus-tomers (prosumers) that negotiate and collaborate as an intelligent network in close interaction with their external environment. Context is king here: the smart home and building environment includes a diversity of other units: neighboring local energy consumers (other smart houses), the local energy grid, associated available power and service trading markets, as well as local producers [local environ-mentally friendly energy resources such as solar and (micro) combined heat and power (CHP)].

The architecture is based on a mixture of innovations from recent R&D projects in the forefront of European smart grids research. These innovations include:

in-house energy management based on user feed-back, real-time tariffs, intelligent control of appliances, and provision of (technical and commercial) services to grid operators and energy suppliers

aggregation software architecture based on agent technology for service delivery by clusters of smart houses to wholesale market parties and grid operatorsusage of service-oriented architecture (SOA) and strong bidirectional coupling with the enterprise sys-tems for system-level coordination goals and han-dling of real-time tariff metering data, etc.

The project capitalizes on several smart grid concepts developed at different research institutes:

The bidirectional energy management interface (BEMI) was developed at the Fraunhofer Institute for Wind Energy and Energy System Technology (IWES), Germany.The multiagent intelligent control (MAGIC) system was developed at the Power System Laboratory of the National Technical University of Athens, Greece.PowerMatcher was developed at the Energy Research Center of The Netherlands (ECN). [The PowerMatcher team at ECN was recently taken over by The Nether-lands Organization for Applied Scientific Research (TNO).]

These three technologies were further developed within the project, and synergies between the approach-es were identified. They all share one control paradigm, which can be summarized as:

Transaction Platform

MarketplaceAuctions

Optimization Service

Buy and Sell

Legacy Providers

BusinessIntelligence

AlternativeEnergy

Providers

Smart Meters

Future Service-BasedEnergy Infrastructure

Internet

Internet

Internet Internet

Home AppliancesManagement

Figure 1. The service-based ecosystem based on smart houses and smart grids.

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http://www.smarthouse-smartgrid.eu






TABLE 1. SH/SG Business Cases.

Number Name Brief Description

1 Aggregation of houses as intelligently net-worked collaborations

When smart houses are able to communicate, interact, and negotiate with both customers and energy devices in the local grid, the electricity system can be operated more efficiently because consumption can be better adapted to the available energy supply, even when the proportion of variable renewable generation is high. A commer-cial aggregator could exercise the task of jointly coordinating the energy use of the smart houses or commercial consumers that have a contract with him (either via direct control of one or several participating devices or through providing incentives to the participating devices so that they will behave in the desired way with a high probability but not with certainty).

2 Real-time imbalance reduction of a retail portfolio

This business case is rooted in the balancing mechanism as applied in Europe and defined by the European Network of Transmission System Operators for Electric-ity (ENTSO-E) Scheduling System. It focuses on the balancing actions by a balance responsible party (BRP) during the balancing settlement period. The key idea of this business case is the utilization of real-time flexibility of end-user customers to balance the BRP portfolio instead of using traditional power plants. For each control zone, the BRP aggregates all of its contracted flexible distributed generation (DG) and responsive loads in a virtual power plant (VPP). The BRP uses the VPP for its real-time balancing actions.

3 Offering (secondary) reserve capacity to the transmission system operator (TSO)

This business case is rooted in the ancillary services as initiated by TSOs throughout the world. In this business case, the BRP should be able to offer its flexible demand and supply on the reserve market. To enable BRPs to offer flexible demand and supply on the reserve market, their bids have to fit into the above market structure. The key idea of this business case is the utilization of real-time flexibility of end users (prosumers) in balancing a control zone. For each control zone, market parties aggregate these flexible DG and responsive loads in a VPP. The TSO contracts in real time part of these flexible loads for its real-time balancing actions.

4 Distribution system con-gestion management

This business case aims at deferral of grid reinforcements and enhancement of network utilization. The need clearly arises in areas with a large amount of DG near one location. Noncoordinated control of (new) electric devices (e.g., heat pumps and electric cars) may lead to a sharp rise in needed capacity on lines and transform-ers. By coordination of these devices, there can be allocated timeslots for operation that are spread out over time. Furthermore, coordination can increase the simul-taneousness of local supply and demand in case local generation is integrated. Congestion management as a service can be used to better match own generation and consumption for prosumers; also, distribution system operators (DSOs) may be interested in improving the quality of supply in areas with restricted capacity in lines and transformers.

5 Variable tariff-based load and generation shifting

In well-functioning and liquid markets, the expectations of all market participants about the generation and consumption situation of the next day are well reflected in day-ahead power exchange prices. If these wholesale prices are passed over to the end users, these have an incentive to shift loads from high-price times to times of lower prices. The key idea of the business case is, thus, to provide the customer with a variable price profile on the day before power delivery. At the customer’s premise, an energy management system should receive the price signal and determine the optimal timing for the energy consumption (or generation, for prosumers) of those appliances that can be shifted in time or that have a storage characteristic. The main value driver from the customers’ perspectives is to receive a tariff and a technology that reduces their energy bills. The value driver from the retailers’ perspectives is the opportunity to reduce his procurement.

6 Energy usage monitoring and optimization ser-vices for end consumers

Awareness of one’s energy use can stimulate behavioral changes toward energy savings. Personalized and well-targeted advice on how to save energy can help further exploit the savings potential. This business case, therefore, suggests providing customers with detailed and comprehensible information about their own energy con-sumption. The additional value to the customer provided by the described information services can either be remunerated through additional fees or through enhanced customer loyalty. A combination of both is also conceivable.

(Continued)

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TABLE 1. SH/SG Business Cases (Continued).

Number Name Brief Description

7 Distribution grid cell islanding in case of higher system instability

The key idea of this business case is to allow the operation of a grid cell in island mode in case of higher system instability in a market environment. This business case considers that the islanding procedure is performed automatically. Technically, it involves monitoring and forecasting the available DG and loads and creating a load shedding schedule based on to the criticality of the consumption loads and on the customer’s willingness to pay for running the appliance during island mode. During an event, decisions are taken how many and which loads must be shed to maintain island mode steadily. Grid cell islanding is of value to the DSO. Islanding helps him to quickly restore system stability within his grid area.

8 Black-start support from smart houses

The key idea of this business case is to support the black-start operation of the main grid. It considers that after a blackout, the local grid is also out of operation and the main goal is to start up quickly in island mode and then to reconnect with the upstream network to provide energy to the system. Black-start support is of value both to the DSO and the consumer. Flexible demand helps the DSO restore system stability.

9 Integration of forecast-ing techniques and tools for convenient participa-tion in a common energy market platform

The volatility of the production level of distributed energy resources (DERs) makes forecasting a necessary tool for market participation. The actor with the lowest fore-casting error will have the most efficient market participation. This business case pro-vides benefit for both the consumer and the aggregator. The aggregator has the ability to participate accurately in the wholesale market and gain by reducing the uncertain-ties. The consumer benefits from lower prices. However, it requires the participation of the consumers since an accurate forecast requires online monitoring of the DERs and not simply reading from the smart meter. The business case comprises the data collection, which is the most critical part that may lead to a correct forecast. The second part is the data evaluation and processing, e.g., for extracting a wind power prediction valid for a certain region.

TABLE 2. An Overview of the SH/SG Technologies.

PowerMatcher BEMI MAGIC

Basic concepts

■ Decentralized decision making about consumption and production

■ Decision making based on central-ized market equilibrium of all bids

■ Real-time mapping of demand and supply

■ Automated control of production and consumption units

■ Scalable architecture


■ Decision making based on central-ized tariff decision

■ Mapping demand to available supply■ Automated control of consumption

units■ User information for manual control

of consumption behavior


■ Decision making based on central-ized negotiation of requests

■ Mapping of demand and supply■ Automated control of production and

consumption units

Methodology

■ Market-based concept for demand and supply management

■ General equilibrium theory■ Market is distributed in a tree

structure■ Participants: devices, concentrators,

objective agents, and auctioneer■ Device agents submit bids/demand

and supply functions■ Auctioneer determines prices■ Round-based marketplace

■ BEMI enables decentralized decisions based on tariff information

■ Decision consists of local information about devices and central informa-tion about variable prices

■ Pool-BEMI sends price profiles■ “Avalanching” can be avoided by giv-

ing different price profiles to different customer groups

■ Day-ahead announcement of price profiles

■ Multi-agent system (MAS) based using Java Agent Development Frame-work (JADE) (negotiation based)

■ Grid announces selling price/buying price

■ Microgrid tries to agree on “better” prices

■ Maximum of internal benefit■ Auction algorithm such as the sym-

metric assignment problem■ Agents also may use reinforcement

learning (Adapted MAS Q-Learning)■ Number of involved agents differs

with the action to take

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The concept of the project is to combine central-ized and decentralized control approaches with the following philosophy: Let the end-customer decide as much as possible within his or her private grid. Therefore, offer the end customer the online tools with appropriate boundary conditions and incen-tives to optimize his or her energy interface to the outside world according to actual (dynamic) prices and energy efficiency considerations that reflect the real-time needs of the public grid. To this end, pro-vide centralized information but allow for decen-tralized decisions.

Business CasesThe technological developments in the SH/SG project have been based on nine business cases that describe how smart grid approaches could be applied by single stakeholders in the electricity supply business. As shown in Figure 1, not all business cases are applicable to all stakeholders, but each stakeholder can apply more than one business case. Table 1 summarizes the nine business cases.

The Overall ArchitectureThe SH/SG architecture has to account for the heterogene-ity of concepts adapted and tested within the project. One major overarching paradigm that has to be reflected is the distributed control paradigm. Following this, there needs to be some distributed decision making at the house level, which is facilitated through an appropriate in-house archi-tecture in combination with global coordination. The latter, in turn, facilitates a business case of some involved enter-prise. Table 2 summarizes the main characteristics of the three technologies employed in the project: PowerMatcher, BEMI, and MAGIC.

There are some important commonalities between these technologies. As already depicted in Table 2, it can be recog-nized that the common idea of the SH/SG implementation follows a unified approach: PowerMatcher, BEMI, and MAGICmanage demand and supply on the basis of a centralized optimization tool that works with decentralized decision making. This is highly important for the acceptability of these technologies since each participant keeps full control over his devices but has incentives to align the device opera-tion with the global status of the overall system.

Each of the three technologies is based on the concept of mapping the demand to the producible or produced energy. It is possible to adjust the amount of energy to be consumed by deploying features like automatically switching on and off consuming devices or indirectly influencing the consumer’s behavior via price incentives. These features are part of all three trials (which are based on three different technology approaches), and the auto-mated switching of the controllable devices in the house-holds plays a significant part. The control of the shiftable production of energy is in a similar way possible by means

of automated on and off switching features for CHP pro-ducers, as an example.

Each of the concepts includes a centralized negotiation or calculation mechanism that tries to map the producible energy to the consumable energy for all actors (smart houses and production sites) within the smart grid. Exter-nal production sites producing and providing a certain amount of energy can be included in the negotiation pro-cess as a fixed and uncontrollable amount of energy. Therefore, the architecture of all three setups contains a central coordination mechanism.

The way the three coordination mechanisms are designed is similar from a high-level perspective, but differs in the details. Each tool either collects information or fore-casts the desired amount of energy to be consumed or produced from all participating smart houses and produc-tion sites. Each tool is able to understand not only the desired energy amounts but also some indicators about the conditions energy will be consumed or produced, namely, price incentives to shift demand. Based on all offers and requests, the tool analyses how the equilibrium can be reached under the given conditions.

One major difference between the negotiation proce-dures is the time cycle of the negotiations and, therefore, the consideration of unforeseeable changes. PowerMatcher and the MAGIC system work in (near) real time. The advan-tage is that for unforeseeable demand or production requests, a short reaction time can be expected to map the complementary production or demand requests. The BEMItechnology, in contrast, works on a time scale of a day, where day-ahead production and consumption patterns are considered to define the price levels that are used as decision-guiding signals.

The field trials described in next few sections aim to investigate the appropriate time scale of equilibrium cal-culations. The near real-time negotiation demands a high degree of scalability and performance requirements. The PowerMatcher tool performs real-time negotiation using a multilevel approach realized by the use of agents, cluster-ing several smart houses or concentrator levels stepwise. For a small number of smart houses, the concept of real time could scale easily, but for a higher number of smart houses, the concept has yet to be proven.

Decentralized decisions about consumption and pro-duction decisions are decentralized, i.e., the control of switching on or off of a certain producing or consuming device is always done within the smart house itself. Even when for the smart houses a central control is established, the decision remains within the house. Of course, the decision is guided by a centrally determined and provided signal (e.g., virtual price signal or a real-time tariff/price structure or direct control signals).

Because of the difference between the technologies employed, SH/SG does not have a common architecture in the classical notion, but an amalgamation of heteroge-neous approaches that are glued together by an SOA, as

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shown in Figure 3. This is compatible with the future smart grid vision as it is not expected that a single archi-tecture will prevail but several heterogeneous approaches will be applied. All of them will exchange information at a higher level via common standardized approaches, such as those enabled by Web services.

Field Trials

Win-Win Situations: Trial in Manheim

Trial Setup and ObjectivesThe main objective of the trial in Manheim is to test the automated response of household devices and the cus-tomers’ behavior on variable electricity prices within a real utility environment. Participants are located in Mannheim’s ecologically oriented suburbs of Wallstadt and Feudenheim with a large number of customers act-ing as consumers and photovoltaic (PV)-based electricity generators, i.e., prosumers. Part of the solution proposed by the field trial in Manheim is to integrate a demand-side energy management system as an active part of the grid by offering incentives to use electric devices at speci-fied times. This energy management system should be flexible so that it can be extended by control functions for electricity generators, e.g., micro-CHP in combination with thermal storage devices to allow electricity genera-tion when needed, while also supplying heat or warm water when requested. Therefore, decentralised energy management in households for balancing local consump-tion and local supply of electricity is investigated in 100 households.

The core of the energy management system used is a newly developed device called the “Energy Butler.” Together with a broadband power line modem and peripheral additional modules (e.g., smart meter, data storage/data aggregator, and switchboxes), the Energy Butler serves to optimize selected household appliances

based on a tariff profile received one day ahead via a broadband power line used for communication with the DSO. Automatically switched devices include dishwashers, wash-ing machines, refrigerators, freezers, and clothes dryers (with a maximum of two devices switched per custom-er). In addition, other devices could be started or stopped by the custom-er any time according to price incen-tives by a simple click on the Web interface. Consumer interaction with the Energy Butler and the communi-cation among all elements of the smart house is presented in Figure 4.

The energy management system tested in this field trial uses two main

units together with supporting additional equipment:1) a smart meter to measure the electricity consumption

digitally2) the Energy Butler together with switchboxes to start/stop

connected household devices and primary equipment.In addition to these units, the energy management sys-

tem comprises supporting technical infrastructure involv-ing many rather complex processes and equipment within a single household. To keep high customer satisfaction and considering interaction between various stakeholders—between the customer and the local Utility at Mannheim, Germany, Mannheimer Versorgungs- und Verkehrsgesell-schaft Energie AG (MVV) Energie between MVV and the equipment developer, hardware manufacturer and other third parties involved—a failure management system was introduced. The field trial installations were conducted in several phases, starting with a small group of households in the first phase and with further replication to a larger num-ber of the customers in the subsequent phase. The two main phases were:

elaboration and installation of the smart meters according to suitability and price and their testing afterwardstesting and checking the functioning of the newly developed hardware and software for the Energy Butler energy management system, including briefing, train-ing, customer care, and installation teams, as well as implementation of a new billing procedure.

Four preferred tariffs were introduced for weekends and working days with two different profiles for each of them. Each tariff profile used for the field trial had two price levels: low and high tariff with a minimum duration of one hour. The tariff profiles were static, which means that the same sequence (high and low tariff) applied for every working day and every weekend day and holiday, respectively.

The field trial measurements were implemented in three phases adding step-by-step tariff incentives and

WholesaleMarket

EnergyRetailer

DGOperator

Consumer/Prosumer

DSO

TSOLarge Power

Producer

Energy Trade

BalancingEnergy

CommoditySubsystem

TechnicalSubsystem

PhysicalEnergy Flow

BC 2, 3, 4BC 1, 5, 9

BC 6, 7, 8

Figure 2. Mapping the business cases to the market participants.

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Energy Butler devices from October 2010 to August 2011, with further ongoing data acquisition and documentation:

The first phase with new energy management/vari-able tariffs started in October 2010. The customers received a first variable tariff on a monthly basis and access to the MVV metering portal. The custom-ers could shift their loads according to this variable tariff manually.The second phase started in December 2010. Since the Energy Butler was still not available to all customers, a new tariff model was introduced to get a better statis-tical basis for the evaluation of the load shift potential. In parallel, the Energy Butler was installed and tested, first at up to ten selected friendly customers followed by the installation of the other 90 Energy Butler devic-es with all peripheral devices (e.g., switchboxes, gate-way/modems, and temperature sensors) starting in spring 2011. This included constant software improve-ments and installation of the most recent software updates on the Energy Butler via remote access.

The third phase started in May 2011 and lasted until August 2011 when activating the Energy Butler soft-ware allowing the customer to use it not only for manual but also for automated load shift.

Key Findings and Lessons LearnedQuantitative assessment of the load shift potential requires comparison between the load curve when variable tariffs (electricity prices) are applied and the normal reference case with fixed tariffs. Since it is impossible to measure concurrently the load curve with the two options for any customer, it was decided to use as the reference case modi-fied standard load profiles considering seasonal effects.

A representative load shift together with the applied, as obtained for February 2011, is shown in Figure 5. There are several effects that need to be considered with respect to the load shift. Besides the seasonal and price effects, changes in consumer awareness, saturation, or habitual effects can be important when tariffs are constant for sev-eral months.

Centralized

SendingSignals/Prices,ReceivingPreferences/Bids

Decentralized

ReceivingSignals/Prices,DeliveringPreferences/Bids

External Services Smart Retailer/Service Provider

Meter DataAnalysis

Smart Grid ProductDevelopment

HEM SignalOptimization

Energy Feedbackfor Customers

Rating andBilling

Aggregation Level

Smart HouseHEM UserInterface

ConsumptionMonitor Interface

ConcentratorHome Gateway

Devices and DeviceControl

Smart Meter

HEMConcentrator

Metering DataConcentrator

DSLPLC, BPLCGSMIP

ZigBeePLC,Z-WaveIP

LoadForecasting

RES GenerationForecasting

PriceForecasting

RES: Renewable Energy Sources

HEM: Home Energy Management

GSM: Global System for Mobile Communications

PLC: Power Line Communication

BPLC: Broadband Power Line Communication

Figure 3. The architecture of loose coupling via services.

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Customer feedback showed that during the test, the majority of the participants used devices at times conve-nient for them. The most commonly used flexible appli-ances were dishwashers, washing machines, and clothes dryers. Two thirds of the customers indicated that they changed their electricity consumption behavior during the field test. The participants also indicated that they had adapted their electricity consumption to the tariffs and it was estimated that they could save about €5 per month compared to flat tariffs. Participants also reported that they were motivated to reduce consumption by acknowl-edgment of their contribution to climate protection. In summary, two conclusions can be drawn, as assessed by the participating consumers: 1) power consumption was reduced in absolute terms and 2) the power consumption of white goods (e.g., household devices) has been shifted to off-peak hours.

Finally, a unique feature of the field trial in Manheim is that it involves many profit-oriented stakeholders. An important lesson learned is that the emergence of these stakeholders, who were once single vertically integrated utilities, greatly increased mediation issues when imple-menting smart grids. Within the project context, this is resolved by project management and common consor-tium decisions. However, if considering implementation of smart grids in today’s unbundled market, such a

consortium would have to be replaced by a trusted cross-partner organization for mediation between con-flicting partner interests, which otherwise would hinder technical implementation. For example, giving the cus-tomer a tariff bonus to motivate a load shift for better utilization of the DSO’s grid resources may be an advan-tage for the DSO, but it is unattractive for the energy pro-vider as of today. This is due to the introduction of variable tariffs that raise costs for establishing new bill-ing procedures but do not yield direct income. However, without technical services provided by the DSO and energy provider, the smart grid cannot prevail, which is a disadvantage for both.

Support in Critical Grid Operation: Trial in Meltemi

Trial Setup and ObjectivesThe aim of the field trial in Meltemi is to demonstrate the ability of a decentralized system to handle critical sit-uations, such as the transition to island mode or black start. Furthermore, it aims to demonstrate the capability of decentralized resources to provide ancillary services, i.e., load shedding to alleviate network congestions. Melt-emi offers seaside camping near the Athens coast, con-sisting of 170 cottages used mostly for summer holidays. Because of the small size of each cottage, its electrical

Display for Monitoringand Control

Energy Butler

Energy ManagementNetwork

Energy Management GatewayRouter

Multitariff Metering

Micro-CHP

Meter Gateway

Intelligent Devicesand Systems

www

Figure 4. The smart house as envisioned in the Mannheim trial.

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consumption is lower than an ordinary house in Greece. However, the ecological awareness of its habitants and the electrical structure [all houses are connected to the same medium voltage/low voltage (MV/LV) transformer] of the settlement make it ideal for use as a test bed for functions related to emergency and critical grid situa-tions. The installation of distributed generation (DGs), including a 40-kVA diesel generator, 4.5-kW PV panels, and small residential wind turbines, can partially sup-port the Meltemi campground in a microgrid operation.

The MAGIC system installed allows the DGs and the household to negotiate to decide the next sequence of actions. This system is a Java-based software that imple-ments intelligent agents. A critical component of the MAGIC system is the intelligent load controller (Figure 6) based on an embedded processor that runs Linux and can be used to monitor the status of a power line providing voltage, current, and frequency measurements. The con-troller is expandable with several serial ports and a uni-versal serial bus port and has the ability not only to control but also to monitor several appliances. It is designed for indoor installation and is equipped with a display to present messages directly to the consumer. In addition, the consumers are informed online about the status of the system as well as their consumption and energy costs. This information is also available through a Web portal. This information is critical since consumers accept them only when they visualize the potential for energy savings cost benefits.

Measurements and ResultsCongestion management is based on the monitoring of the transformer that feeds the camping site. The idea is that when the transformer is close to its critical level of overloading, the DSO requests that the aggregator proceed with load shedding.

The MAGIC system deals with this request in two steps. During the first step, the agents monitor the system and provide to the other agents and the aggregator infor-mation about its status, i.e., production, consumption, and voltage measurements. The system provides a list of loads that can be shed, as well as the units that are capable of providing extra energy.

The second step concerns the time period just before the transformer overload. The system predicts the over-load using its forecasting functions and proceeds with intelligent load shedding. Advanced load-shedding algo-rithms are used ensuring that loads of the consumers are curtailed in a fair way.

To evaluate this function, a simple algorithm that simply reacts to the various disturbances was consid-ered. The difference between the two approaches is shown in Figure 7. During the disturbance, the simple algorithm reacts when the system detects the overload. This stimulates load shedding at the MV substation. On the other hand, the MAGIC system has the ability to pre-dict the incoming event and act faster. It has been dis-covered that 15 min early warning is enough time to cope with the disturbance.

Electric Load Shift Within the Field Trial

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Figure 5. The load shift in the field test achieved by variable tariffs (February 2011).

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The islanding/black start support scenario also has two main steps: the first step takes place before the event that may occur, and the second step is the steady island-ed operation. During the first step, the system monitors both the available DG units and the loads, and forecasts the consumption and the available power and energy in the next hours. A load-shedding schedule is derived based on the criticality of the loads expressed by the cus-tomers’ willingness to pay for their service during the island mode period.

In the first few minutes after the event, the DSO (simu-lated agent) allows operation of critical loads depending also on the local power availability. When balance and sta-bility have been ensured, MAGIC assumes on its own the energy management, i.e., generation and consumption, within the islanded network. The transition to the island mode is done automatically without interference from the end users or the aggregator.

It should be noted that if the disturbance happens dur-ing the middle of the day, there is sufficient energy and

critical loads can be supplied by the PVs. The MAGIC sys-tem interferes only when the consumption increases sig-nificantly. For example, on 2 August, a cloud reduced the PV production, as shown in Figure 8. If this event hap-pened during the islanded mode, the MAGIC system would limit the consumption of the controllable devices. The general conclusion is that effective monitoring (knowledge) and device control improves quality of ser-vice to the consumers.

Key Findings and Lessons Learned from the Trial in MeltemiThe primary lesson learned from the Meltemi trial is the importance of enhanced SOA capabilities. Large-scale implementation requires cooperation with enterprise information systems and, consequently, an adaptation of the negotiation algorithms. Another important issue is the importance of the legal framework and the level of market deregulation. All of the scenarios implemented in the field trial assume the implementation of flexible tariffs and the ability of the aggregator/Energy Service Company (ESCo) to make arrangements with the consumers/ DG owners.

Finally, the facilities provided by the intelligent load controller are crucial. The availability of an indoor display is significant since it allows the inhabitants to actively participate in shaping their energy profiles. Communica-tion with the users has revealed that information about level of consumption and costs increases their awareness regarding energy savings and, as a consequence, solutions like the one proposed by SH/SG project are easier accept-able. The existence of a Web portal is also significant, although it was not widely used in the Meltemi trial because of the limited access to Internet by the residents of the holiday campground.

Mass Scalability: Trial in HoogkerkThe field trial in Hoogkerk aims to demonstrate the mass-scale perspective of automated aggregated control of end-user systems for energy efficiency, combined with testing the information exchange with enterprise systems using data traffic at mass-application strengths. The scale of mass-application is set at 1 million households.

Detection Thatan IncidentHappened

Detection Thatan Incident Is

Ready to Happen

Action Action

Overload Overload

LoadIncrease

(a) (b)

Figure 6. The MAGIC load controller. (Photo courtesy of NTUA.)

Figure 7. The operation of the (a) simple versus (b) advanced algorithm.

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One subgoal of the trial was to demonstrate that the performance of automated control of 1 million house-holds is adequate with respect to the business case on Real-time Portfolio Imbalance Reduction. This business gives a BRP the ability to control the flexible demand and supply of household appliances to improve its overall demand and supply balance within a settlement period. Since this settlement period varies in Europe from 15 to 30 min, the control actions at the BRP enterprise level should preferably be in the order of 5 min or fewer. In this way, a BRP will have at least three moments during a set-tlement period to exert its control.

A further subgoal was to demonstrate the ability of the system to handle variable tariff-based metering data from the smart meter through the smart grid infrastructure to the enterprise system for billing and rating. This business cases assumes real-time tariffs, which implies that prices can change at any moment in time. Billing is based on integrated volumes and prices over fixed periods, i.e., 15 min. Therefore, the metering interface should be able to handle both the real-time varying tariffs on the usage side and the integration into periodic volumes and prices on the meter reading side.

The field trial in Hoogkerk is built around the Power-Matcher technology. The PowerMatcher is designed to be scalable and applicable on a large scale. The objectives have proven this in two ways:

Performance of control: To control a cluster of house-holds for a business case, the control signals should reach the households and the devices fast enough to support the business case.Performance of metering and billing: Variable pricing leads to large amounts of detailed measuring data, which has to be processed by the enterprise system.

A main challenge for the trial was to reach 1 million households. Because of the large numbers involved, it is impossible to include 1 million real households in the trial. Therefore, a large part of the trial was based on simu-lated entities. For the same reason, it is not feasible to sim-ulate every single household as a separate entity. The setup of the trial is shown in Figure 9. It shows the hierar-chical structure of the PowerMatcher technology with two levels of concentrators between the enterprise system and the smart house gateways. The metering data are commu-nicated through the same layered structure.

In Figure 9, several components can be distinguished. On the left side are the real-world components in the test (encircled in red). Concentrator 1.1 is dedicated to the control of the real smart houses that are part of Pow-erMatching City, an existing test field in Hoogkerk in the north of The Netherlands. Concentrator 1.2 is connected to 100 actual smart meters; this part is dedicated to delivering metering data without implementing Power-Matcher control. Concentrator 2.1 connects concentra-tors 1.1–1.100 to the enterprise system located in Karlsruhe, Germany.

A simulation was set up running 1 million virtual households on the SH/SG side of the setup. This system was connected to the PowerMatching city field test to measure latency of the communication of the control sig-nal coming from the enterprise and reaching the lower level device agents in the smart houses, both real and simulated. To connect to the PowerMatching City field test, some adjustments have been made, which added artificial delays to the latency. To accommodate for software discrepancies, two objective agents and several Web ser-vices were used to enforce the SH/SG price on the Power-Matching City cluster (Figure 10). Bids and prices signals were recorded with the corresponding time at each level of the simulation to measure the latency.

The results of the latency test can be seen in Table 3. The influence from an objective agent on the SH/SG side of the simulation reaches a real device in fewer than 5 min (on average 4 min), thus meeting the desired target. How-ever, there was a large amount of artificial latency, which influenced this result and could require 1 min to reach the agents. This artificial latency was caused by the polling and measurement tactics enforced on the PowerMatching City cluster. Further, an additional auctioneer, Web services, and objective agents are required to complete this test.

On the metering side, it was discovered that a lot of time is spent on internal processing of the meter reading assessment process (e.g., validation, sanity checks, and storage) inside the application server itself. For example, the total request/response time for one connection, for a single meter reading submission to the metering server, was approximately four times longer than the time required to insert the metering data into the database. This difference was the first sign that the application server load should be balanced over multiple nodes. As such, further performance enhancements should focus on reducing the request processing time, e.g., a meter data concentrator to collect meter readings could be used and submit them in bulk to the main server. This way, the request processing time per meter reading can

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Figure 8. The measurements at the Meltemi PVs.

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be reduced, yielding higher efficiency. However, even more aggressive performance-related strategies might provide better results, such as usage of in-memory data-bases or strategic (on-demand or periodic) committing to the database.

Key Findings and Lessons LearnedArtificial latency in the PowerMatcher communication will impact the latency between an objective agent and device agent is well within the settlement period of the BRP. Therefore, it was proven that there is potential to

Figure 10. The latency test.

SmartHouse

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Figure 9. An overview of the components in the Hoogkerk field trial.

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balance control via demand-side man-agement at a household level. Further-more, there is also the potential for balancing ancillary services for the TSOusing this same method.

The SH/SG project made the assump-tion that there will be no common archi-tecture penetrating all layers of the envisioned smart grid. It is proven that this is a viable approach and the interme-diate communication and data exchange layers are appropriately wrapped. To this end, we must once more underline the importance of stan-dardization of smart meters, smart services, and energy management systems toward energy-related services and toward data models depicting the energy data acquired.

On the metering side, it turned out that there was no tool available for asset management of the smart meters used in the trial. As the measurement data are accumulat-ed values, it was not a big problem when values were miss-ing or duplicated. Once in a while, the meshed radio-frequency network delivered duplicate data, i.e., with the same origin, value, and timestamp. The application should be robust enough to handle this situation. Duplicate meter reading is a nonmalicious error; however, it high-lights the need to check data for compliance to specific for-mats and also to perform logical checks. Although the focus of the project was not on security, in a real-world deploy-ment, this would be of paramount importance. At this instance, it would be quite possible to inject erroneous metering data in an attempt to destabilize the system, lower its performance, or even reduce the monthly bill.

ConclusionThe infrastructure that will exist in the future smart house is expected to be highly heterogeneous. However, it seems that at some level, all devices—either by them-selves or via gateways—will be able to communicate over the Internet protocol and participate in bidirectional col-laboration with other devices and enterprise services. Similarly, multiple concepts for monitoring and control-ling the smart houses and the smart grid will emerge, with different optimization and control algorithms. It is therefore imperative not to focus on a single one-size-fits-all approach but rather to prove that an amalgamation of existing approaches should be developed. The SH/SG proj-ect can be seen as a first step to developing mechanisms for gluing different monitoring and control approaches as well as empowering the next-generation enterprise services and applications. This is done by using Web ser-vices and open standards, as applied by the PowerMatch-er, BEMI, and MAGIC systems.

Innovative technologies and concepts will emerge as we move toward a more dynamic, service-based, market-driven infrastructure, where energy efficiency and savings can be facilitated by interactive distribution networks. A

new generation of fully interactive ICT infrastructure has to be developed to support the optimal exploitation of the changing, complex business processes and to enable effi-cient functioning of the deregulated energy market for the benefit of consumers and businesses.

AcknowledgmentsWe would like to thank the European Commission for their support and the partners of the Smart Grid projects SH/SG, Integral (www.integral-eu.com), Modellstadt Mannheim (www.modellstadt-mannheim.de), and NOBEL(www.ict-nobel.eu) for the fruitful discussions.

For Further ReadingSmartHouse/SmartGrid. [Online]. Available: http://www.smarthouse-smartgrid.eu/

SmartGrids European Technology Platform. (2010, Apr.). Smartgrids: Strategic deployment document for Europe’s electricity networks of the future,. [Online]. Available: http://www.smartgrids.eu/documents/SmartGrids_SDD_FINAL_APRIL2010.pdf

BiographiesAris Dimeas ([email protected]) is a researcher at the National Technical University of Athens, Greece.

Stefan Drenkard ([email protected]) is a senior engineer at Gopa-intec, Germany.

Nikos Hatziargyriou ([email protected]) is a pro-fessor at the National Technical University of Athens. For six years, he was deputy CEO of the Public Power Corpora-tion of Greece.

Stamatis Karnouskos ([email protected]) is a research expert at SAP in Karlsruhe, Germany.

Koen Kok ([email protected]) is a researcher at The Nether-lands Organization for Applied Scientific Research (TNO), The Netherlands.

Jan Ringelstein ([email protected]) is a researcher at the Fraunhofer, Institute for Wind Energy and Energy System Technology, Germany.

Anke Weidlich ([email protected]) is a professor at the Hochschule Offenburg, Germany.

TABLE 3. The Latency Test Results for Controllability.

NodeMeasured

PerformanceNet

PerformanceArtificial Latency

Virtual network

Enterprise 0 s — —

Concentrator level 2 70 s 10 s (30 + 30) s

Real network

Concentrator level 3 142 s 22 s (30 + 30) s

Home gateway 205 s 25 s (60) s

Device 240 s 30 s (30) s

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D A T E S A H E A D


2014

14–17 APRILT&D 2014: IEEE PES Transmission & Distribution Conference & Exposition, Chicago, Illinois, USA. Contact Tommy Mayne, e-mail: [email protected], www.ieeet-d.org

20–23 MAYISGT Asia 2014: IEEE PES Innovative Smart Grid Technolo-gies Asia, Kuala Lumpur, Malaysia. Contact Titik Khawa Abudl Rahman, e-mail: [email protected], http://ieee-isgt-asia-2014.com/

15–18 JUNEITEC 2014: IEEE Transportation Electrification Conference and Expo, Dearborn, Michigan, USA. Contact Mahesh Krish-namurthy, e-mail: [email protected], http://itec-conf.com

27–31 JULYGM 2014: IEEE PES General Meeting, National Harbor, Maryland, (Washington, D.C. Metro Area) USA. Contact Paula Traynor, e-mail: [email protected], http://www.pes-gm.org/2014/

31 AUGUST–3 SEPTEMBERITEC Asia-Pacific 2014: IEEE Transportation Electrification Conference and Expo, Asia-Pacific, Beijing, China. Contact Xuhui Wen, e-mail: [email protected], http://www.itec2014.com

12–15 OCTOBERISGT Europe 2014: IEEE PES Innovative Smart Grid Technolo-gies Europe, Istanbul, Turkey. Contact Prof. Dr. Omer Usta, e-mail: [email protected]

2015

10–13 MAYIEMDC 2015: IEEE International Electric Machines and Drives Conference, Coeur d’Alene, Idaho, USA. Contact Her-bert Hess, e-mail: [email protected]

26–30 JULYGM 2015: IEEE PES General Meeting, Denver, Colorado, USA. Contact Paula Traynor, e-mail: [email protected]


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N E W S F E E D

Around the Society

HE IEEE TECHNICAL Activities Board, during its fall meeting in New Jersey in

November 2013, approved the IEEEPower & Energy Society (PES) proposal to establish a new open-access publi-cation called IEEE Power & Energy Tech-nology Systems Journal. The first issue of this quarterly periodical is expected to come out in the fall of 2014.

This journal will contain practice-ori-ented articles focus-ing on the develop-ment, planning, design, construction, maintenance, instal-lation, and operation of equipment, struc-tures, materials, and power systems for the safe, sustainable, economic, and reli-able conversion, gen-eration, transmis-sion, distribution, storage, and usage of electric energy, including its measure-ment and control.

IEEE PES membership consists of more than 70% of industry profes-sionals, many of whom come from electric utilities, consulting compa-nies, and small- and medium-sized enterprises. This journal is expected

to attract technical papers addressing the latest information and systems written by industry practitioners, academics, and public sector employ-ees, among others.

Reder Honored with Emberson AwardCongratulations to PES Past President Wanda K. Reder. Reder is the recipient

of the 2014 IEEE Richard M. Emberson Award for distinguished service to the development, viability, advance-ment, and pursuit of the technical objec-tives of the IEEE, spon-sored by the IEEETechnical Activities Board: “for leadership in the IEEE Smart Grid program and in the continued growth of the Power & Energy

Society, including the creation of its Scholarship Fund.”

IEEE PES Scholarship Plus InitiativeThe PES Scholarship Plus Initiative (IEEE PES S+) is a scholarship and career experience program that was created in response to the looming workforce shortfall in the power and energy industry. The goal is to increase the number of well-qualified, entry-level engineers in the United States and

Canada. Since 2011, the IEEE PES has distributed more than 549 scholarships to 364 students from 137 universities within the United States and Canada.

Applications are being accepted for the 2014–2015 academic year for IEEE PES S+. Under this program, recipients can graduate with recogni-tion as an IEEE PES scholar, receive up to US$7,000 in multiyear scholar-ships, and gain career experience. The application period is 1 March to 30 June 2014.

Additionally, the top IEEE PES scholar from each IEEE region will be selected as the IEEE PES John W. Estey Outstanding Scholar. These individu-als will each receive an additional US$5,000 for school expenses (tuition, books, and student fees), IEEE and IEEE PES Student Member-ship for 12 months, and a travel hon-orarium of up to US$1,000 to attend the IEEE 2015 PES General Meeting.

Thanks to our current donors, the initiative has raised more than US$5.2 million. Individuals and organizations are encouraged to give back to the industry and “pay it forward” by donat-ing to the initiative. Your donation will educate and inspire the next genera-tion of power and energy engineers.

To learn more about IEEE PES S+, visit the IEEE PES Scholarship Plus Web site: http://www.ee-scholarship.org/.

T


The PES Scholarship

Plus Initiative (IEEE

PES S+) is a scholarship

and career experience

program that was

created in response to

the looming workforce

shortfall in the power

and energy industry.

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V I E W P O I N T

and distribution more cost effective for the vast majority of electricity con-sumers. However, and this is critical, disruptive technologies are making microgrids a cost-effective way for a larger portion of electricity customers to save money on their electricity use and increase their power reliability.

Before we dive into this idea in greater detail, it is crucial that we define what we mean when we use the word “microgrid.” It is just as important for us to also understand the value microgrids deliver to cus-tomers. These values will set the basis for looking at how microgrids could be perceived as a threat to utilities.

What Is a Microgrid, and What Is Its Value?Depending on who you talk to, there are dozens of interpretations as to what qualifies as a microgrid, which causes confusion in our industry. Some require renewable resources to be part of the mix, some are super reliable distribution systems, and some are just big loads with lots of diesel generation. To provide clarity and consistency, we will lean toward

the U.S. Department of Energy’s defi-nition and consider a system a microgrid if its electrical system meets all four of the following criteria:

1) It must be a group of interconnected loads: A microgrid must have more than one interconnected load.■ What counts: An industrial

campus with multiple facilities that are interconnected by the same distribution system.

■ What doesn’t count: A single building with a backup diesel generator is not considered a microgrid, as there is only one load to support.

2) It contains distributed generation (DG) resources: A microgrid must have at least one source of local generation tied to the local power system. For our discussion herein, ES systems will be considered DG. To be clear, ES is typically not con-sidered DG as it can be both a source of generation and a load, but we have grouped them togeth-er for this discussion.■ What counts: A campus with

rooftop solar and a large die-sel generator.

■ What doesn’t count: A campus that buys renewable energy credits but has no local source of generation.

3) A clearly defined electrical boundary:Microgrids must have a clearly defined boundary between their grid and any other power system.■ What counts: A military base

that owns and operates its own distribution system with two utility substations feeding the base.

■ What doesn’t count: A major city with multiple loads and multi-ple points of interconnection.

4) Islanding: The final, and maybe most debated, differentiator for our version of the microgrid is the ability to connect and disconnect from the grid without dropping any of the supported load. This is commonly called islanding. We will make an exception for two things here. The first is for remote microgrids that are never con-nected to a centralized grid and are, therefore, permanent islands. The second is the need to pick up every load within the microgrid. Demand response and load shed-ding are necessary components of an economical microgrid.■ What counts: A university cam-

pus that has the necessary controls to manually, or auto-matically, disconnect their sys-tem from the local utility.

■ What doesn’t count: A group of high-rise residential build-ings that have diesel genera-tors but no method by which they can isolate themselves from the grid.

It is important to understand what constitutes a microgrid, but it is equally important to understand the value a microgrid provides to customers. All of the value boils down to improving the efficiency and/or reliability of a customer’s local power system. We often use Figure 1

Peak Load

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Figure 1. The value of a microgrid. (Image courtesy of S&C Electric Company.)

(continued from page 104)

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to represent the convergence of val-ues a microgrid can offer.

Although simplistic, Figure 1 shows how a microgrid provides value to a customer. We start with a customer who has a peak average load as well as a mission-critical load. The mission-critical load is essential and needs the highest level of reli-ability. Since there is a difference between the customer’s peak load and their mission-critical load, we can assume that this grid meets our first criteria of a microgrid by having multiple interconnected loads.

Efficiency Through Demand ReductionsThe bottom left corner of Figure 1 shows a customer with no DG. This customer relies completely on the util-ity to support his or her load. The load supported by the utility is shown in gray. This is the vast majority of elec-tricity users today. As we move to the right in Figure 1, we can see the first benefit of a microgrid: to improve effi-ciency. Efficiency uses customers’ own sources of generation to reduce their overall load and, in turn, reduce their electric bills. As you can see, the DG cannot meet the customer’s mission-critical load, let alone his or her peak load. But it does help save real dollars by reducing his or her electric bills, which is shown in the green shaded areas. The fact that the customer has a source of DG also meets our second criteria for qualification as a microgrid.

Mission-Critical ReliabilityAs the customer connects additional DG resources, we see their demand on the utility continue to reduce. More importantly, at value point 2 in the figure, the customer’s DG is now capable of supporting his or her most critical loads, which we will call the mission-critical load. The second major value of the microgrid is the reliability improvements that are achieved when customers generate enough power locally to support part, or all, of their load.

This ability is crucial in the fourth criteria of a microgrid, islanding. In the event that utility power is lost, a microgrid must be able to support at least its critical loads with its available DG. At value point 2 in Figure 1, we can see that if the utility source (the gray part) goes away, the customer has enough on-site DG to keep the mission-critical loads running. This improves the overall reliability of his or her power system if utility power is lost and also allows the customer to reduce his or her demand when connected to the grid even if utility power is available.

This brings up an important con-cept in microgrids, which is time. There is a reason we do not show time in this figure. As we have visited and built microgrids around the world, one of the often missed concepts is the difference between power and energy. Microgrids are often analyzed in terms of power, looking at the loads and available DG in terms of kilowatts or megawatts. Most people see it as a logic equation:

IF (Average Power Demand ÷ DG Power) > 0Then Microgrid.

This equation is great when you want to talk about the efficiency improvements a microgrid can pro-vide. As the result of the equation gets closer to one, the customers become less reliant on the utility, in turn reducing their demand costs. Between one and zero, customers can generate more power than they use, a concept we will cover a little later.

The challenge is that this equation focuses only on the efficiency of the system and does not factor in how long the DG used in the equation will last, which is called its energy. You can have entire buildings with megawatts of load supported for a few seconds by an uninterruptable power system. These systems use dozens, hundreds, and sometimes rooms full of batteries to support critical loads for short peri-ods of time in the event that utility power is lost or there are power

quality issues that could affect the load. Would you consider this a microgrid? Would a building with roof-top solar panels alone be considered a microgrid? Most microgrid customers would say no, as these systems would not support the reliability of the loads for any usable period of time.

Every microgrid customer we have met wants to improve both the effi-ciency and the reliability of his or her power system. They want the DG they invest in to reduce their electricity demand and support at least a portion of their load for an effective period of time. Depending on the customer, the typical expectation starts around 6 h and can extend to days, weeks, or even months. Therefore, we often use the equation below, which focuses on energy, not power, as the determining factor for a microgrid.

IF 0 < (Average Customer MWh ÷ DG MWh) < 1Then Microgrid That Will Last.

With this equation, as the number gets closer to zero, the overall reliabili-ty of the microgrid improves because the DG resources can support the cus-tomers’ peak load for longer periods of time. The farther the result is above one, the less likely the microgrid can support the customer’s average load for any significant period of time. Table 1 illustrates some examples.

Any value shaded red would be able to keep the customer operating for fewer than 1 h and probably only be useful for temporary outages or power quality issues. When the total DG energy equals that total energy of the consumer, it means the customer is supported for 1 h, which is colored yellow because this is typically not long enough to satisfy any reliability improvement needs. Where we start to get a microgrid that can last for a reasonable amount of time is in the green areas.

Total ReliabilityAs we move to the right in Figure 1, we start to reach a tipping point. Between

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V I E W P O I N T

points 2 and 3 we have enough on-site DG to provide power to our system’s average load. As DG continues to be added or turned on, we exceed the peak load of our system and find ourselves in a situation where the microgrid can generate more power than our system would ever demand. In terms of reliabil-ity, we reach a point where, if we lose our primary source, we have the means to keep our entire system running for as long as our DG sources allow.

An important concept with the value of reliability and efficiency in a microgrid is load shedding. In Figure 1, you can see a third line that is below our average load and closer to our mis-sion-critical load. One tool that makes a microgrid vastly more adaptable is a control system that allows the inter-connected loads to shed their nones-sential loads. This can be as simple as physical plant personnel manually cut-ting power to a nonessential building or it could be as advanced as a central-ized master control that automatically turns off individual circuits among the microgrid’s interconnected loads.

In Figure 1, we show this concept with our theoretical customer having the means to shed load to a new reduced load level. By doing this, cus-tomers can keep just a bit more than their mission-critical loads operating using the DG already in use. This abili-ty transitions us to the fourth value of a microgrid.

Grid SupportColored in yellow on the final portion of Figure 1, we show DG increasing to

a point where it exceeds the peak load of the customer’s system. At point four, we have more generation capaci-ty than our system demands. This excess capacity can be used to sup-port the local grid. For example, imag-ine a microgrid at a military base. At a typical base, a majority of the person-nel who work at the base live nearby in the surrounding communities. If a major weather event interrupts sourc-es of generation typically feeding these communities, and the base is set up like our microgrid in Figure 1, the base could use its excess DG to support other loads outside its system with permission and coordination with the local utility. In a nonemer-gency situation, the base could sell its excess generation to the local utility, essentially becoming a source of both load and generation.

With load-shedding capability, a microgrid can broaden its ability to support the grid. In Figure 1, there is enough DG to support the customer’s peak load, but there may be situations where it is more economical or neces-sary to reduce the customer’s load and provide additional support for the local grid. This is the exact situation that occurred at the University of Cali-fornia San Diego (UCSD). The UCSD campus has a variety of DG sources including a fuel cell, combined heat and power system, solar panels, and ES. When wildfires took out transmis-sion lines, the local utility asked UCSD if they could use its DG to stabilize the grid. UCSD was happy to help and reduced its load through load

shedding protocols that were already in place to provide the maximum support it could by exporting its now excess DG capacity. This effort helped keep the grid from collapsing.

Microgrid CostsWe hope this overview helps you see why there is such momentum building behind microgrids. Large and small customers hold tremendous potential to save money by implementing microgrids of their own. We can dollar-ize the two benefits for consumers:

1) By using microgrids to become more efficient, customers can directly save money by reducing their power demand (cost savings).

2) By using microgrids to become more reliable, customers can indirectly save money by reduc-ing the frequency and duration of outages (cost avoidance).

If we look for ways that microgrids could threaten utilities, the most obvious culprit is the ability for cus-tomers to reduce their demand. For instance, if a large customer decides to invest in DG, that would, in turn, reduce the customer’s energy demand and thereby reduce revenues for the utility. However, it is much more complicated than that. We illus-trate this through the microgrid cost evaluation tool shown in Table 2. This is the same tool we use with our cus-tomers to evaluate what their real-ized cost savings would be for using DG to offset their electricity demand and improve their reliability.

The argument for microgrids dis-placing utilities is that customers can own and operate their own grids cheap-er and more reliably than what their local utility can. We have highlighted four portions of the economic analysis shown in Table 2 that highlight why microgrids are not going to disrupt utili-ties in the near future. When you run the numbers, you find out quickly that the utility still delivers the same value that led to its creation in the first place. The rumors of their demise are extremely premature.

TABLE 1. Distributed Generation (MWh).

0.25 MWh 1 MWh 24 MWh 50 MWh

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0.25 MWh 1 0.25 0.010 0.005

1 MWh 4 1 0.04 0.02

24 MWh 96 24 1 0.48

50 MWh 200 50 2.08 1

75 MWh 300 75 3.13 1.50

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The Electrical RateOne of the major factors in determin-ing the potential cost savings through efficiency is the customer’s electrical rate. Electric rates vary sig-nificantly across the world for any number of reasons. Regardless, they play the largest part in deciding whether reducing demand through the use of DG is economical. For example, in Illinois, the average retail price of electricity for an industrial customer is about US$0.8/kWh. In Hawaii, that price is more than four times the rate in Illinois at about US$0.33/kWh. The average rate in the United States is about US$0.13/kWh.

When we plug in some hypotheti-cal numbers and dollarize the effect of the rates, it becomes clearer why using

the DG in a microgrid as the primary source of power rather than the utility is often not economical. If we assume that the customer uses 240,000 annual kWh, our equation works out to the values shown in Table 3.

Between the United States aver-age and Hawaii, there is a difference of US$48,000 a year. This is a big dif-ference, which is why we see areas with higher electricity rates, such as islands, making microgrids work for them. The fact is that, for most cus-tomers, the utility rate is more eco-nomical than running DG when you factor in the additional costs.

In addition to electricity rates, most large customers pay a demand charge, which covers the utility’s opera-tion and maintenance costs for the

infrastructure needed to support their loads. These demand charges are typi-cally negotiated and require the cus-tomer to meet a certain power factor. Most importantly, demand charges can include peak demand charges. Wheth-er through peak demand charges or time-of-use rates, the economics behind microgrids become more appealing when you consider the pos-sibility of reducing your demand dur-ing peak periods, which is called peak shaving. If rates are higher, say around the Hawaii level, in the middle of the day, customers can save even more money by reducing their load.

Some would argue that it is the reduction of these peak demand charges that can threaten utilities. The truth is that there is a joint

TABLE 2. The S&C Microgrid Cost Evaluation Tool.

Unit

Customer’s annual energy use kWh

X Customer’s electrical rate US$/kWh

+ Annual demand charges US$

= Total annual electricity costs US$

X Percentage reduction in electricity demand realized through use of a microgrid %

1 = Total annual savings from microgrid US$

– Direct costs for DG US$

+ Direct costs for islanding infrastructure US$

*One time expense= total direct costs for microgrid US$

– Number of hours DG is expected to operate annually Hours

X Number of watts used in 1 h of operation kWh

X Cost of fuel source for DG US$/kW

2 = Total variable cost for microgrid operation

– Annual operation costs US$

+ Annual maintenance costs US$

3 = Total recurring costs for microgrid operation

+ Cost of outage for 1 h US$

X Standard average interruption duration indices SAIDI

X Standard average interruption frequency indices SAIFI

4 = Total cost of reliability improvements US$

= TOTAL COST SAVINGS FROM MICROGRID US$

Note: U.S. dollars are used as an example. It could be the currency of any country.

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benefit here that helps the customer save money and really helps the utili-ty defer capital costs. If customers can reduce their load during peak periods, the cost of losing that potential reve-nue from the customer is minuscule compared to the savings utilities real-ize by not having to purchase peaking generation or invest in spinning reserve. Thus, the ability for custom-ers to use the DG in their microgrids to reduce their peak loading actually helps utilities in the long term.

Cost of FuelWe have already calculated the energy savings operating a DG can have, but these savings are defrayed by both fixed and variable costs. Fuel is a vari-able cost and a major factor that chips away at the economics of microgrids. The range for the cost of fuel varies based on where you are, what fuel source you are using, and the efficiency of your DG resources. Without calculat-ing it, we want to highlight this number because it feeds into the total variable cost of operating a microgrids DG.

Let us take two extremes, solar power and diesel generation, and look at the differences the cost of fuel can play in whether it is economical to use on-site DG instead of utility sourc-es. With solar, there is US$0 in variable fuel costs to operate that source of generation. Therefore, solar power does not subtract anything from our savings from operating it, although it

may produce smaller savings than the diesel would provide because of vary-ing levels of efficiency.

On the other hand, diesel has vari-able costs that vary depending where you are in the world. In the United States, one barrel of diesel fuel costs about US$125. If we assume that a microgrid has two 150-kW diesel gen-erators operating on full load, they would consume 21.8 gal/h of fuel. This would consume about 2.8 barrels of oil per day and cost the microgrid owner US$350 per day, or about US$127,750 annually, to peak shave. This does not take into account restrictions on emissions that may cause additional costs in taxes or require the microgrid to run the gen-erator below peak load.

These are extremes, but the ener-gy mix within a microgrid and the fuel used to support it are critical fac-tors that typically deter customers from using anything that has high consumption costs.

Operation and Maintenance CostsNext time you look at your electric bill, you will see an additional cost added to your energy use that covers the utilities’ costs to operate and maintain the infrastructure neces-sary to provide electricity to your home. A microgrid is no different. Outside of the direct costs for the implementation of DG and controls

capable of islanding, there are recurring annual costs for cus-tomers to operate and main-tain their microgrid.

These costs vary greatly but draw out an important reason why microgrids are not harming utilities: econo-mies of scale. The typical investor-owned utility has a median of 400,000 customers with an average of 34 custom-ers per mile. To deliver power to these customers, utilities have invested in an infra-structure that requires con-

tinued operation and maintenance. Over the past 100 years, utilities have become experts at this and have entire asset management groups devoted to maintaining their infrastructure. Because of the scale of the typical utility’s system, econ-omies of scale fall into place with utilities able to leverage their size to lower the costs of equipment, per-sonnel, and other resources needed to maintain their system.

When you look at a microgrid, the costs for ongoing operation and main-tenance fall to the customer. These costs take away from the annual cost savings of operating a microgrid. Worse yet, if a customer decides to forgo maintenance of their microgrid, the wear and tear of operation can take its toll on the equipment, causing it to fail and negating any benefits.

What Is the Cost of Reliability?We have looked at how to calculate the savings customers can realize by using their microgrid to become more efficient and offset the power they demand from the utility. To balance that equation, we have accounted for the annualized cost of the system as well as its operation and maintenance.

As you may recall, one of the qualifying criteria for a microgrid is the ability to island itself from the grid. The U.S. electric grid is 99.9% reliable, but reliability numbers differ among states, regions, and countries.

TABLE 3. Comparison of Electrical Rates in the United States to Total Electricity Costs.

Customer annual energy use 240,000 kWh

X Customer’s electrical rate (Illinois average) 0.08 US$/kWh

= Total annual electricity costs in Illinois 19,200 US$


X Customer’s electrical rate (Hawaii average) 0.33 US$/kWh

= Total annual electricity costs in Hawaii 79,200 US$


X Customer’s electrical rate (United States average) 0.13 US$/kWh

= Total annual electricity costs in the United States 31,200 US$

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This may seem like a high level of reliability, but if you measure that against the number of hours in a year, it means that the average U.S. customer experiences just under 9 h without power per year.

What costs does a customer avoid by eliminating that outage? Like all good engineering answers, it depends on the customer, their operations, and their values. Recently, the U.S. Depart-ment of Energy and Lawrence Berkley National Labs released their interrup-tion cost estimate (ICE) calculator, which has collected data from thou-sands of U.S. customers to dollarize their costs for a power outage. They estimate that outages cost U.S. custom-ers about US$80 billion per year, and the majority of those losses come from medium to large businesses. Figure 2 shows data pulled from the ICE calcu-lator for the State of Mississippi. Based on their data, the average medium to large commercial/industrial customer uses 5,100 MWh/year.

On average, these customers start off with a loss of US$5,000 when an outage occurs. As the duration of the outage grows, you can see that the cost for the customer increases steadily. In this situation, a 2-h interruption in power costs the average commercial and industrial (C&I) customer in Mis-sissippi about US$17,000.

These curves can change drastical-ly by customer. For example, if the servers that host the electronic trans-actions on the New York Stock Exchange were to lose power, the costs could be astronomical. At the other extreme, a local strip mall that loses power for 2 h would lose reve-nues and still have to pay employees, but these costs would not be large in relative terms.

ConclusionIf the grid is 99.9% reliable, then the purpose of a microgrid is twofold. During the 0.1% of the time that the grid is unavailable, customers want to have the means to continue their operations. This can range from

supporting only their mission-critical operations to supporting their entire peak load and beyond. Either way, customers want to improve their power reliability by islanding them-selves from the grid and using their own DG. By reducing the frequency and duration of outages, microgrid users can eliminate the costs they incur in the event of an outage.

During the 99.9% of the time the utility grid is working, microgrid cus-tomers want to use the idle DG they have to economically reduce their electricity demand. This reduces their power consumption and saves customers money by reducing their electric bills.

Utilities stand to benefit more than they lose from the increased adoption of microgrids. Certainly from an effi-ciency standpoint, utilities could lose some of their revenue through reduced demand from microgrid cus-tomers. However, what utilities gain is customers who can reduce their peak load. Clearly stated, customers can help the utility reduce the stress on the grid at crucial times and poten-tially reduce the cost to the utility of maintaining or adding additional peak demand standby costs.

From a reliability standpoint, utili-ties also do not have anything to lose by fostering the increased use of microgrids. In fact, since microgrids can serve as both a source of load and generation for the utility, the

on-site DG used to support microgrid customers when the power goes out can be used to support the utility’s grid when the need arises. It also allows the utility to restore other parts of its grid while remaining secure in the knowledge that the microgrids are supporting continued operations within their boundaries.

We have not met one person at a utility who sees microgrids as a threat. Of course, there are technical challeng-es that need to be considered when it comes to the islanding and reconnect-ing portion, as is the case with any dis-ruptive technology. For instance, a major utility concern is making sure that they know what sources of load and generation are on their system so that the men and women who operate and maintain the grid are safe. Every utility we talk to wants to work with, not against, customers in its imple-mentation of microgrids. In some cases, the utility wants to experiment with owning microgrids.

We have never met microgrid cus-tomers, other than in rural/remote microgrids, who want to operate completely independent from the grid. They think of the utility as their lifeline, the system that will support them 99.9% of the time. They just want to reduce their dependence on that lifeline and be prepared if that lifeline is no longer there.

Microgrids are not coming; they are already here. From the innovations

0

5,000

10,000

15,000

20,000

0 10 20 30 40 50 60 70 80 90 100 110 120

Use

r C

ost P

er E

vent

(U

S$)

Minutes of Interruption

5,100 MWh/Year (Mississippi)

Figure 2. Costs of the average medium/large C&I customer in Mississippi.

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that created Pearl Street to the trans-formations that drive today’s grid, microgrids are here to stay and rep-resent a new business model for both consumers and utilities. How-ever, the past is littered with old business models, such as pay phones, and those companies that survived adapted to the disruptive technology and changed their busi-ness models appropriately, such as AT&T and Verizon. Therefore, utili-ties and customers need to continue to work together to find ways to adapt the old grid models to the new smarter grid realities.

BiographiesDavid B. Chiesa ([email protected]) earned his B.S. degree in engineering from the United States

Military Academy and his M.B.A. from the University of Maryland. He is the director of commercial and industrial business development for S&C Electric Company. He has more than 20 years of experience turning project ideas into reality for the power and energy industry. In his current role, he oversees the strate-gic approach to the C&I market, which includes working with cus-tomers to evaluate, plan, and imple-ment microgrids. He is a certified Master Black Belt in the Six Sigma quality program and a Member of the IEEE, the American Council on Renewable Energy, the American Wind Energy Association, the Ameri-can Legion, Veterans of Foreign Wars, and the Association for Iron and Steel Technology.

Spencer K. Zirkelbach ([email protected]) earned his B.A. degree in marketing from Illinois State University. He is the marketing specialist for S&C Electric Company’s Power Systems Solutions division. In this role, he guides the communica-tions and research for multiple mar-kets including microgrids, wind, solar, ES, data centers, smart grids, and communication system deployments. He has coauthored 12 articles covering the subjects of microgrids, renewable energy, ES, and dynamic islanding. He is actively involved in industry associ-ations such the IEEE Power & Energy Society, the American Wind Energy Association, the Solar Energy Power Association, the Electricity Storage Association, and the Business Market-ing Association.

Charting the Course toa New Energy FutureJust a stone’s throw from our nation’s capital, the PES General Meeting will attract thousands of professionals from every segment of the electric power and energy industries. It will feature a comprehensive technical program, including super sessions, panel sessions, tutorials, technical committee meetings and standards activities. Plus, enjoy a lineup of excellent technical tours, a student program, companion activities and much more.

About National HarborLocated on 300 acres of prime real estate along the scenic Potomac River in Washington, D.C., National Harbor is the new gateway to the National Capital Region. This spectacular urban-waterfront community offers stunning views of downtown Washington, D.C. and Old Town Alexandria, and is just a 15-minute drive–or water taxi ride–to the heart of the nation’s capital.

2014IEEE PESGENERALMEETINGJuly 27–31, 2014National Harbor, MD

For More Information and to Register Today visitpes-gm.org/2014

Registration is NOW OPENGaylord National Resort and Convention Center

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V I E W P O I N T


By David B. Chiesa and Spencer K. Zirkelbach

Microgrids Help More Than They Hurt

HERE DID THE MYTH THATmicrogrids are going to be the end of utilities start? We

use the word myth specifically. A myth is a work of fiction, a story that no one can explain or trace back to a fact. We have seen the myth that microgrids are a threat to utilities grow more common in conversations at confer-ences, in publications, and on social media. We can make assumptions about how the myth was started. Microgrids are becoming a popular idea, with analysts forecasting billions of dollars in revenue potential over the next five years. Major weather events that knock out service for millions of customers are sparking discussions on the reliability and quality delivered by the electricity utilities. New tech-nologies such as energy storage (ES), fuel cells, renewable generation, and grid automation are making the idea that customers can own, control, and operate their own power system(s) a growing reality.

But microgrids are not a future concept; they are already here. They are utilized in hospitals when utility power is lost but the lights and life-saving equipment in the emergency room must stay on. They have been in the northwest territories of Cana-da for decades, where oil is abundant but electrical utilities are scarce,

forcing companies to run their own power grids to support the plants and community infrastructure that make their businesses possible. They make sure that the data centers that run the servers that host the financial transactions of the world’s economic markets never ever lose power.

In fact, our entire power infrastruc-ture began as a series of microgrids. The story of the first microgrid reach-es back to 1882 when Thomas Edison built the Pearl Street generating sta-tion in New York City. Pearl Street was the first commercial power station, and it supported the loads of lower Manhattan with local generation. With no support from any other gen-eration sources, Pearl Street was an islanded grid conveniently located on an island. As the demand for electrici-ty grew, Edison added additional sources of generation, eventually con-necting these small grids throughout New York to one another.

In the late 1800s, as the demand for electricity grew, companies were creat-ed to invest in the infrastructure and generation needed to bring power to everyone. This was ignited by the invention of the electric meter, which allowed these companies to accurately bill customers for the actual cost of energy instead of, for example, basing their bill on the number of lamps that were being powered. Over the next 100 years, these early electric utility companies expanded their systems

with larger sources of generation, and the grid as we know it was born.

This historical review is important because it provides the backdrop of history against which we can view the myth of microgrids destabilizing utili-ties. If all electrical usage started out as microgrids and early small systems had to generate and distribute their own electricity, why was it necessary for utility companies to be formed in the first place? The answer is cost. It was, and still is, vastly more economi-cal to generate power in mass than for consumers, large or small, to gen-erate it on their own. Sure, there will always be instances where the eco-nomics behind buying, operating, and maintaining an independent grid makes sense. But these are few and far between when compared to the group of electrical consumers as a whole. It costs consumers far less to pay an entity, whether publicly traded or not, to deliver electricity than it would if every consumer chose to gen-erate his or her own power. But there is more than economics at stake. If every electricity consumer decided to generate his or her own power 24/7, 365 days a year, the environmental impact would be astronomical as well.

The simple truth is that economies of scale will always make the tradi-tional centralized utility-based meth-od of power generation, transmission,

W

Digital Object Identifier 10.1109/MELE.2013.2297182Date of publication: 18 March 2014 (continued on page 96)

2325-5987/14/$31.00©2014IEEE

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Published quarterly starting in September 2013, each issue will provide:

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IEEE Electrification Magazine provides timely insights into the challenges and solutions of electrifying the diverse transportation sector—making this periodical a must-read for anyone responsible for evaluating and purchasing the numerous related products and services offered in this burgeoning market.

The publication features myriad industries, from semiconductors to software, renewable energy to energy storage, and power electronics to communication networks. You will find that Electrification is an invaluable means for reaching the most important players in this space.

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