energy management systems in microgrid operations

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Energy Management Systems inMicrogrid Operations

Microgrids are a promising technology that can increase

the reliability and economics of energy supply to endconsumers. Microgrid development is shifting fromprototype demonstration and pilot projects to full-scalecommercial deployment. Microgrid energy managementsystems are critical components that can help microgridscome to fruition.

Wencong Su and Jianhui Wang

I. Introduction

Economic and environmental

incentives, as well as advances in

technology, are reshaping the

traditional view of power

systems. The majority of the

current U.S. power grid

infrastructure was built in the1930s. The aging and

overburdened power grid has

experienced five massive

blackouts in the past 40 years

(Farmer and Allen, 2006). To

address these challenges,

microgrids have emerged as a

relatively new and promising

solution to restructuring the

current energy infrastructure and

ensuring the reliability of energy

supply.

A. Definition of microgrid

and energy management

system (EMS)

Technically speaking, amicrogrid is a low-voltage

distribution network that is

located downstream of a

distribution substation

through a point of common

coupling (PCC). Microgrids

consist of a variety of components

including distributed generators

(DGs), distributed energy storage

Wencong Su works as a researcher for Argonne National Laboratory, a U.S.

Department of Energy Laboratory in Argonne, Illinois. He has also worked as

a research and development engineerintern at ABB’s U.S. Corporate ResearchCenter. He is currently working toward a

Ph.D. degree in the Department of Electrical and Computer Engineering at

North Carolina State University. Hisspecialties and research interests include

Smart Grid, microgrid, renewableenergy, grid integration of plug-in

electric vehicles, computationalintelligence, and power system modeling

and simulation.

Jianhui Wang is an energy systemengineerat Argonne NationalLaboratory.

He is also an affiliate professor of the

Department of Industrial and SystemsEngineering at Auburn University. He is

the chair of the IEEE Power & EnergySociety (PES) Power System Operation

Methods Subcommittee and co-chair of an IEEE task force on integrating wind andsolar power into power system operations. He has authored/co-authored more than100 journal and conference publications.

He is an editor of the IEEE Transactionson Smart Grid, and an editorial board

member of Applied Energy. He is also a

guest editor of a special issue of the IEEEPower and Energy Magazine onElectrification of Transportation, which

won an APEX Grand Award, a guesteditor of a special issue of Applied

Energy on Smart Grids, RenewableEnergy Integration, and Climate Change

Mitigation – Future Electric EnergySystems, and is a guest editor of four

special issues of the IEEE Transactionson Smart Grid on communication

systems, demand response, storage, and forecasting. He is the technical program

chair of the IEEE Innovative Smart GridTechnologies conference 2012.

This work was supported by the U.S.Department of Energy, Basic Energy

Sciences, Office of Science, undercontract No. DE-AC02-06CH11357.

October 2012, Vol. 25, Issue 8 1040-6190/$–see front matter# 2012 Elsevier Inc. All rights reserved., http://dx.doi.org/10.1016/j.tej.2012.09.010 4

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(DES), and controllable loads. The

unique characteristics and

dynamics of a microgrid’s

components present a unique

challenge with regard to grid

control and operation.

Depending on the characteristicsand penetration of distributed

energy resources (DERs) and DES

nodes within a particular

microgrid, the desired energy

management scheme can be

significantly different from a

conventional power system. A

typical microgrid runs in two

operational modes (Asmus, 2010;

Lasseter, 2002): in aninterconnected mode linked to the

main grid through the

distribution substation

transformer and in an islanded

(autonomous) mode when it is

isolated from the main grid

during a blackout or brownout.

In the islanded mode, the

microgrid remains operational

and functional as an autonomous

entity. In a conventional

power distribution system, the

islanding process is prohibited

for practical operation, due tosafety concerns and hardware

limitations. Nowadays,advanced

power electronic devices (i.e.,

solid-state transformers)

consolidate the two-way

communication, switching

functions, protective relaying,

metering, digital data processing,

two-way power flow, and high

computational capability. Theinterconnection switch that a

microgrid has is compatible with

islanding and resynchronization

under a variety of operating

conditions.

A microgrid EMS is controlsoftware that can optimally

allocate the power output among

the DG units, economically serve

the load, and automatically

enable the system

resynchronization response to the

operating transition between

interconnected and islandedmodes based on the real-time

operating conditions of microgrid

components and the system

status. Figure 1 shows a typical

control hierarchy of a microgrid.

In general, a sophisticated

microgrid EMS has to operate and

coordinate a variety of DGs, DESs,

and loads in order to provide

high-quality, reliable, sustainable,and environmentally friendly

energy in a cost-effective way.

T he most common microgridcomponents and thecorresponding control/

management schemes are

discussed as follows.

[

Figure 1: Control Hierarchy in Microgrid

1040-6190/$–see front matter # 2012 Elsevier Inc. All rights reserved., http://dx.doi.org/10.1016/j.tej.2012.09.010 The Electricity Journal



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B. Microgrid components

Althoughthereisnotauniversal

definition of what constitutes a

microgrid, it can be generally

stated that a microgrid is

composed of several major

components which normally do

not exist in traditional power

systems. High penetration of these

components increases the

complexity of the microgrid EMS.Table 1 summarizes the major

components associated with

microgrid EMSs and their

functionalities.

1. Distributed generator

It is usually defined as a small-

scale (e.g., kilowatts) electric

power generator which is

directly connected to thedistribution system at or near the

load feeder. In contrast,

conventional power plants

supply electricity through high-

voltage transmission lines with a

capacity of hundreds of

megawatts. Since DGs are

normally onsite or close to the

end-users, some types of DGs

(e.g., micro gas turbine), or more

broadly speaking combined heatand power (CHP) plants, can

simultaneously generate both

electric power and usable heat,

which can be a great benefit of

installing a microgrid. CHP

plants will likely be at the heart of

microgrid economics (Lasseter

et al., 2002). Traditional large

generators are at best 35 percent

efficient with a significant loss of primary energy. A CHP system

can potentially reaches an

efficiency of up to 80 percent to 85

percent. Without CHP systems,

microgrids may be less efficient

than the traditional power grid.

Moreover, since the waste heat

emitted from U.S. power plants

accounts for approximately 28

percent of the energy-relatedcarbon emissions of the country

(Marnay et al., 2008), the U.S.

Department of Energy (DOE) sets

up an aggressive goal of having

CHP plants comprise 20 percent

of U.S. generation capacity by the

year 2030 (Shipley et al., 2008).

The United States would see a

5,300 trillion British thermal unit

(Btu) annual energy

consumption reduction, an 848million metric ton (MMT) annual

CO2 reduction, and a 231 MMT

annual carbon reduction (DOE,

2012).

Some types of non-fuel-based

DGs (e.g., wind turbines,

photovoltaic [PV] panels) are non-

dispatchable, and their output

depends on uncertain and

variable energy sources. Fuel- based DGs (e.g., micro gas

turbines, diesel generators) can be

dispatched according to their

operating cost. An effective

microgrid EMS needs to

determine the optimal energy

scheduling of all DGs depending

on fuel costs, heat/energy

requirements, and customer

preferences. It is worthmentioning that the heat and

electricity demand may not

occur at the same time, which

places an additional constraint on

the microgrid’s control algorithm.

D ue to the nature of variousDGs, advanced powerelectronic devices are applied to

smoothly convert energy of

Table 1: Microgrid Components Controlled by Energy Management System.

Components Examples Functionalities

DG Reciprocating internal combustion engines with

generators, fuel cells, microturbines, small-scale wind

turbines, and photovoltaic arrays

Generate electricity and useful heat to local users and

utilize a variety of energy resources.

DES Battery banks, flywheels, super-capacitors, compressed

air energy storage

Store excess energy at off-peak time and operate as an

additional generator at peak time.

Controllable load Heating, ventilation, and air conditioning (HVAC) system,

plug-in hybrid electric vehicle (PHEV), plug-in electric

vehicle (PEV), and commercial and residential buildings

Dispatch the load to minimize the disturbance to power

grids and maximize customer preference.

Critical load School, hospital Serve as base load.

Need power quality support for critical loads.

PCC Static switch Switch between islanded and interconnected modes.




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variable frequency into the grid-

compatible alternating current

(AC) or direct current (DC) power.

The local regulator embedded in a

DG is mainly responsible for

voltage/frequency control and

real/reactive power control inorder to ensure DGs can be

integrated into the microgrid. In

addition, optimal energy

management for microgrids witha

significant DG penetration

requires the monitoring control of

DGs through free information

flow. It is critical to maintain the

compatibility of communication

technologies and provide thenecessary interoperability among

the diverse DGs. The International

Electrotechnical Commission

(IEC) 61850-7-420

Communications Standard for

Distributed Energy Resources

(DERs) has been widely used

(Cleveland, 2008) to address this

issue. It is an international

standard that defines thecommunication and control

interfaces for all DER devices, in

particular when DERs are

interconnected with the electric

utility grid.

2. Distributed energy storage

DES can make microgrids more

cost-effective by storing energy

when energy from the main grid ischeap or there is excessive

generation from the local DGs.

DES can also be operated as an

additional generator during peak

demand periods. The detailed

operations on DES are performed

by the embedded local regulators

within DES while the microgrid-

level EMS will control when to

dispatch the stored energy and

how much. The overall energy

management objective for DES

varies depending on the microgrid

operational modes. In an islanded

microgrid mode, DES can return

electric energy to minimize thedisturbance on end-users and

maintain the system reliability. In

an interconnected mode, DES is

mainly responsible for

maintaining the stable power

output of DGsandstoringlow-cost

electricity when it is available. In

general, some forms of DES are

coupled with DGs according to

their power/energy density. For

instance, a supercapacitor with

high power density is an excellent

candidate for short-term

balancing. A flywheel also has

high energy density and can

interact with certain types of DGsto provide energy for a prolonged

periodoftime.Inthelongrun,DES

can also provide a reasonable

amount of reserve capacity to main

the reliability of the microgrid.

3. Controllable loads

Controllable loads refer to the

loads that can adjust their own

electric energy usage based on

real-time set points. In a

conventional distribution

system, consumers have little

flexibility to fully participate in

electricity markets. Controllable

loads are usually tied with theconcepts of demand-side

management (DSM) or demand

response (DR). For example, the

load of buildings can be

controlled by adjusting the

HVAC system and temperature

to save energy cost while not

sacrificing the customer’s

comfort level. More and more

buildings equipped with thistype of control can be easily

interfaced with microgrid EMS.

Another controllable load

example is residential/

commercial lighting control,

which has been proven

successful (Dounis and

Caraiscos, 2009). Plug-in hybrid

electric vehicles (PHEVs) and

plug-in electric vehicles (PEVs)can be another special class of

controllable load. Unlike other

controllable loads, these

vehicles can be connected to the

outlets anywhere and at any

time, bringing more spatial and

temporal diversity and

uncertainty to the grid. Also

vehicle-to-grid (V2G)

technologies allow PHEVs/PEVsto feed energy directly back to

the distribution network, which

creates a reverse flow and

complicates EMS operations.

4. Critical load

A typical microgrid consists

of both critical load and

controllable load. In the normal

In a conventionaldistribution

system, consumershave little flexibility

to fully participatein electricity

markets.




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operational mode, the DG and

DES nodes can be utilized to

support as many critical loads as

possible. Once a microgrid is

disconnected from the main

utility grid, not all of the load

within a microgrid can besupplied. In order to improve the

availability and reliability of

power supply for critical loads,

some of non-critical (i.e.,

controllable) load may have

to be disconnected or shed

accordingly.

5. Point of common coupling

PCC is the point at which thepower production, distribution

network, and customer interface

meet. In the most common

configuration, DGs, DESs, and

loads are tied together on their

own feeders,which arethenlinked

to the utility grid at a single PCC.

II. Functionalities ofMicrogrid EMS

A microgrid is a small portion

of a power distribution system

which is tied with the rest of the

distribution system via aninterconnection switch. From the

system point of view, a microgrid

can freely route the energy

among the utility grid, local

renewable energy generators,

controllable loads, and DES

devices, opening up a new

paradigm of ‘‘Internet for

Energy’’ (Huang et al., 2011). The

microgrid EMS is expected tomonitor the operational

conditions and optimally

dispatch power from DERs and

DES nodes to supply the

controllable and critical loads.

Controllable loads can also be

dispatched accordingly to

maintain system reliability and

other critical loads. Figure 2

shows the role of EMS in a

microgrid associated with policy,

electricity market, load/DER

forecast, customers, utility, loads,

DGs, and DES. The microgridEMS receives the load and

energy resource forecasting data,

customer information/

preference, policy, and electricity

market information to determine

the best available controls on

power flow, utility power

purchases, load dispatch, and

DG/DES scheduling.

T here are a number of EMSsoftware programs availablein practice. Table 2 summarizes

an incomplete list of vendors for

microgrid EMS systems. Each

EMS has different features that

can be customized for a specific

microgrid.

[

Figure 2: An Illustrative Microgrid EMS




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Table 2: Major Vendors for Energy Management System.

Vendor Product Feature

Tridium, Inc

(www.tridium.com)

Vykon A comprehensive set of applications that synchronize, manage, and control

major building system functions required in a facility, such as HVAC systems,

energy, lighting, security, fire, safety, and unitary devices.

Encorp (www.encorp.com) Microgrid System

ControllerTM

Microgrid

SecureTM

Virtual

Maintenance

MonitorTM

A controller to remotely connect existing onsite generators with the latest clean-

and-green energy assets, such as PV systems and microturbines, and then

monitor and control the resulting microgrid. The software suite allows the

user to control and aggregate multiple energy systems remotely and provides

the user with site-specific generator metering, monitoring, and control.

Sutron (www.sutron.com) GenCom A wireless remote generator control system, in addition to many other

monitoring and control systems.

Invensys Energy Solutions

(www.ies.invensys.com/ )

Local Area

Power Control

Barber-Colman DYNA

It provides integrated, reliable, cost-effective power delivery system control and

management solutions for onsite power generation.

Wonderware

(www.wonderware.com/ )

Wonderware1 A real-time operation management software. Wonderware software delivers

significant cost reductions associated with designing, building, deploying,

and maintaining secure and standardized applications for manufacturing and

infrastructure operations.

GE

(www.ge-ip.com/products/ )

iPower An open, standards-based supervisory control and data acquisition (SCADA)

solution. Typical application solutions include: substation management

solutions; rural and municipal utility SCADA solutions, and in-plant

distribution solutions.

ABB (www.abb.com) MicroSCADA Pro

Network

Manager

SCADA

Manages the entire distribution network in utility and in industry environment

within the same system. It offers immediate access to real-time information

as well as easy connectivity to other systems. Provides a complete set of

advanced power system application functions, all proven under a wide

variety of field conditions.

Siemens

(www.energy.siemens.com)

Spectrum

PowerTMSpectrum Power offers a comprehensive range of SCADA functions for

requirements in energy generation, transmission/distribution network

operations, energy data management, and extensive communications

options with communication protocols.

Viridity Energy

(www.viridityenergy.com)

VPowerTM Provide the ability to communicate with and control equipment so that

executing the optimal energy strategy is as easy as pushing a button.

Power Analysis

(www.poweranalytics.com/ )

Paladin1

SmartGridTM A software platform designed specifically for the on-line management and

control of next-generation ‘‘hybrid’’ power infrastructure incorporating both

traditional utility power and on-premise power generation (e.g., solar power,

wind turbines, battery storage, etc.).

Green Energy Corp.

(www.greenenergycorp.com)

GreenBus1 GreenBus enables packaged applications such as SCADA, AMI/MDM, OMS,

CIS, IVR, and AVL to share data over a standard application programming

interface (API) and industry standard interfaces like MultiSpeak 1.


http://www.awea.org/learnabout/publications/reports/upload/AWEA_First_Quarter_2012_Market_Report_Public.pdfhttp://www1.eere.energy.gov/manufacturing/distributedenergy/chp_benefits.htmlhttp://energy.gov/sites/prod/files/Microgrid%20Workshop%20Report%20August%202011.pdfhttp://www.epia.org/publications/epiapublications/global-market-outlook-for-photovoltaics-until-2015.htmlhttp://www.smartgrid.epri.com/Demo.aspxhttp://www.smartgrid.com/wp-content/uploads/2011/09/12___Richard.pdfhttp://grouper.ieee.org/groups/scc21/dr_shared/http://www.electricenergyonline.com/%3Fpage=show_article%26mag=63%26article=491http://www.pikeresearch.com/research/microgrid-deployment-tracker-4q11http://www.poweranalytics.com/http://www.greenenergycorp.com/http://dx.doi.org/10.1016/j.tej.2012.09.010http://dx.doi.org/10.1016/j.tej.2012.09.010http://www.greenenergycorp.com/http://www.poweranalytics.com/http://www.pikeresearch.com/research/microgrid-deployment-tracker-4q11http://www.electricenergyonline.com/%3Fpage=show_article%26mag=63%26article=491http://grouper.ieee.org/groups/scc21/dr_shared/http://www.smartgrid.com/wp-content/uploads/2011/09/12___Richard.pdfhttp://www.smartgrid.epri.com/Demo.aspxhttp://www.epia.org/publications/epiapublications/global-market-outlook-for-photovoltaics-until-2015.htmlhttp://energy.gov/sites/prod/files/Microgrid%20Workshop%20Report%20August%202011.pdfhttp://www1.eere.energy.gov/manufacturing/distributedenergy/chp_benefits.htmlhttp://www.awea.org/learnabout/publications/reports/upload/AWEA_First_Quarter_2012_Market_Report_Public.pdf


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III. Microgrid EMSArchitecture and ControlPhilosophy

A. Centralized microgrid

EMS

From the energy management

and control perspective, a

microgrid consists of three

hierarchical levels (Katiraei et al.,

2008): distribution network

operator (DNO) and market

operator (MO); microgrid central

controller (MGCC); and local

controllers (LCs) associated with

each DER/DES/load unit. TheMO is responsible for exchanging

information between the

microgrid and the electricity

market. DNO is a high-level

management system that

aggregates real-time information

and operating commands among

multiple microgrids and utility

grids. MGCC serves as a gateway

between the DNO/MO and LCswithin the microgrid. Ideally, a

microgrid EMS is an information

and control center embedded in

an MGCC.

A n MGCC is engineered fortwo major functions forupstream/downstream

distribution systems,

respectively. Firstly, an MGCC

has a two-way conversationchannel with the DNO and MO to

meet the utility requirements

(e.g., supply of electricity and

provision of ancillary services)

and participate in the energy

market (e.g., bidding). The MGCC

monitors the system operational

conditions, responds to any

disturbance, and switches/

resynchronizes the microgrid

operational modes (i.e.,

interconnected or islanded).

Secondly, the MGCC receives

information and requests from

multiple LGs within a microgrid.

Given the system set point sentfrom the DNO and MO, an MGCC

makes a decision to appropriately

allocate the power output among

DER/DES units according to a

certain objective function (e.g.,

loss or cost minimization, or profitmaximization). Then the MGCC

will send back the control signals

and power scheduling references

to the corresponding DGs. The

entire scheduling process is

subject to certain constraints

including reserve requirements,

renewable generation

uncertainties, and physical

constraints of DG and DES units.

I n a centralized operationregime, an MGCC is expectedto be computationally powerful in

order to process a large amount of

real-time data from all DER/DES

and loads in a timely manner. A

reliable two-way communication

infrastructure also needs to be in

place. The centralized microgrid

EMS design holds a number of

advantages such as easy

implementation, standardized

procedure, and high expansion

cost. However, as the number of

control devices rapidly increases,

high requirements oncommunication network capacity

and computational ability become

a major bottleneck for this type of

centralized design.

B. Real-world examples of

centralized microgrid EMS

In the early adoption of

microgrids, utilities largelyfocused on the system reliability

and security issues, based on the

assumption that microgrids are

less likely to completely replace

the existing grid structures.

Figure 3 illustrates a centralized

control scheme of microgrid EMS

(EPRI, 2011).

The energy supply for a

centralized microgrid design maycome from various sources. For

example, Northern Power

Systems has installed and

operated a customer-designed,

utility-connected microgrid

within the area known as Mad

River in Waitsfield, Vt. (Barnes

et al., 2007). A central controller

monitors the system states and

sends out real-time control signalsto multiple generators through a

reliable, secure, and high-speed

communications network.

In comparison, in some other

examples, a single large-capacity

generator or energy storage unit is

installed onsite. For instance, the

BC Hydro Boston Bar (Kroposki

et al., 2008) project is a microgrid




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that is interconnected to 69 kV

feeders through a 69/25 kV

substation. It allows a 3 MW peak

load and 8.6 MVA of

hydroelectric generation in the

islanded mode. Since there is no

storage device involved in thismicrogrid, the central controller

effectively manages a single large

hydro generator by sending

control signals using a leased

telephone line.

Table 3 lists some ongoing and

existing microgrid projects and

testbeds. As can be seen in the

table, the radical (centralized)

microgrid structure is still apopular design for microgrid

installations.

C. Decentralized microgrid

EMS

In contrast to centralized

control, distributed control in a

decentralized microgrid EMS

constitutes a framework where

each microgrid component is

regulated by one or more local

controllers rather than being

governed by a central master

controller. Every local control

monitors and communicateswith the other local controllers

through the communication

network. The local controllers

have the intelligence to make

operational decisions on their

own, without receiving the

control signals from a ‘‘master’’

control in the centralized EMS.

The local controllers then

exchange the information amongneighbors to reach consensus.

Figure 4 illustrates a

decentralized control scheme in

microgrid operations.

B ecause the local regulatorsonly need to communicatewith neighboring devices, the

amount of information

transferred is much less than

what is needed in the centralized

scheme. The computational

burden is also distributed on local

agents because the local

controllers only need to make a

decision locally. Local controllers

are no longer subject to a MGCCto determine the optimal power

output in such a distributed

system. Hence, this kind of

structure significantly reduces the

computational need and releases

the stress on the communication

network of the entire microgrid

system. But it should be

mentioned that a MGCC and its

associated EMS still play animportant role in even this

decentralized framework. For

example, an EMS in a

decentralized microgrid

exchanges energy price

information with the DNO and

MO and is able to take over the

control of the local regulator from

the system level in the event of

[

Figure 3: Centralized Microgrid EMS




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Table 3: Summary of Microgrid Projects and Testbeds.

Region Microgrid DG DES Load Control

North America British Columbia Boston Bar Hydro N/A Residential Centralized

Boralex, Canada Diesel Generator N/A Residential Centralized

CERTS, US Diesel Generator Battery Static,

Induction Motor

Decentralized

University of

Wisconsin-Madison, US

Diesel Generator, PV N/A Static Centralized

Mad River, Waitsfield,

Vermont

Biodiesel Genset,

Microturbine,

Propane Genset

N/A Industrial,

Commercial

Centralized

Asia Shimizu, Japan Gas turbine Battery,

Supercapacitor

Residential Centralized

Hachinohe, Japan PV, Wind,

Diesel Genset, CHP

Battery Industrial,

Commercial

Centralized

Kyoto Eco-Energy, Japan PV, Wind, Fuel Cell,

Biogas

Battery Residential Centralized

Aichi, Japan PV, Fuel Cell Battery Industrial,

Commercial

Centralized

Sendai, Japan PV, Fuel Cell,

Gas turbine

Battery Residential,

Industrial,

Commercial

Centralized

Hsingchiang, China PV, Diesel Genset Battery Residential,

Commercial

Centralized

Hefei University of

Technology, China

PV, Wind, Diesel

Genset, Hydro

Battery,

Supercapacitor

Static, Motor Centralized

Europe Kythnos, Greece PV, Diesel Genset Battery Residential Centralized

Labein Experimental Centre Wind, PV, Microturbine,

Diesel Genset,

Battery,

Supercapacitor,

Flywheel,

Static Centralized and

Decentralized

CESI, Italy, PV, Wind, CHP,

Diesel Genset

Battery,

Supercapacitor,

Flywheel,

Static Centralized

Lab-scale Testbed, University

of Leuven, Belgium

PV, CHP Battery Static Decentralized

Continuon Holiday Park,Netherlands

PV Battery Residential Centralized

Demotec, Germany PV, Wind, CHP,

Diesel Genset

Battery Residential,

Commercial

Centralized

Am Steinweg, Germany PV, CHP Battery Residential Centralized

Lab-scale testbed,

National Technical

University of Athens,

Greece

PV, Wind Battery Static Centralized

Source : Lidula and Rajapakse (2011) and Barnes et al. (2007).




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serious contingencies and

equipment failure.

D ecentralized control isone potential solutionto many challenging controland energy management

problems in microgrids

(Liu et al., 2007). For instance,

as mentioned, the computational

requirement for the MGCC is

much more limited. Also if the

MGCC fails, the rest of the system

can still survive. It is a modular

system to ensure the plug-and-

play flexibility. However, becausethe local controllers have more

authority in this setting, the

inherent security issues make

decentralized microgrids more

vulnerable to cyber and physical

attacks, which can be more

difficult to detect and

troubleshoot. Smooth operations

are highly dependent on

successful communications

among the local agents and their

neighbors. The desired

communication topology

needs to be carefully investigated.In the legacy power system,

the communication channel is

mostly dedicated to the EMS

(master) and local agents

(slave). The local agents have

little flexibility to exchange

information with their neighbors

through the exiting

communication network. Utilities

are seeking a practical way toupgrade/replace an aging power

grid, which cannot be achieved by

a one-step-at-a-time approach.

The expensive initial upgrading

cost on control and

communication facilities are

another bottleneck of the

decentralized EMS in microgrid

operations.

D. Real-world examples of

decentralized microgrid EMS

and control

Figure 5 illustrates the

schematics of the AEP/CERTS

microgrid (Barnes et al., 2007). TheCERTS microgrid is intended to

act as a single self-contained and

autonomous entity. Under the

peer-to-peer concept, this CERTS

microgrid does not require a

single ‘‘master’’ controller. It

operates in a distributed

(decentralized) fashion. The local

controllers have a certain level of

intelligence in order to respond tothe system dynamics (e.g., voltage

magnitude and frequency) by

using droop control and

proportional–integral (PI) control

loops. However, it is important to

mention that a low-dynamic

central controller may still be

needed in this kind of microgrid

to broadcast the steady-state set

points. The dynamic control isperformed by the local controller/

regulator. An example of a

‘‘pure’’ distributed microgrid

operation can be found in

(Brabandere et al., 2007), as shown

in Figure 6. The primary droop

control is responsible for

maintaining the frequency and

voltage at their set points to

ensure reliable operation evenwhen communication fails. A

gossip-based secondary control is

used to minimize the average of

all voltage and frequency

deviations. Then a gossip-based

economic optimization is

performed to determine the cost-

effective energy scheduling by

finding a unique optimal

[

Figure 4: Decentralized Microgrid EMS




11/16

marginal cost. The entire process

is fully distributed without a

central controller.

A s discussed above, twomicrogrid EMS

architectures are available:

centralized and decentralized.

Each of these two control options

has its advantages and drawbacks.Table 4 shows the comparison

between centralized and

decentralized microgrid EMS.

Centralized control is widely

deployed in various SCADA

systems, as shown in Table 3.

Because the system operator has

direct control over the entirepower system in a centralized

control environment, system-wide

optimization can be achieved in a

timely fashion. However, a

microgrid is a complex and

heterogeneous system with

diverse controllable devices. A

centralized microgrid EMS

requires a reliable, high-speed

communication network betweenthe central controller and local

regulators. In addition, the current

centralized control structure is not

fully compatible with the plug-

and-playfunctionality which is the

key feature of microgrids. The

decentralized control option is

being advocated as well. It is

believed that microgrid operations

rely on the intelligence of localcontrollers/regulators. Microgrid

[

Figure 6: Overview of the Proposed Primary, Secondary and Tertiary ControlSource: Brabandere et al. (2007).

[

Figure 5: Schematics of AEP/CERTS MicrogridSource: Lidula and Rajapakse (2011).




12/16

devices (e.g., DG, DES, and load)

operate autonomously (e.g.,

frequency droop control, Volt-

VAR control) based on local

information only. Without the

information exchange between the

master controller and local

regulators, decentralized control

can greatly reduce the need of

high-bandwidth communication.Since it is fairly immune to a single

point of failure, decentralized

control is a good candidate for

small-scalemicrogrids withhigher

priorities on system reliability.

However, due to the nature of

decentralized control, there is no

direct link to broadcast global

information to each controllable

device (e.g., generator, load, andbattery storage). The local

regulator negotiates with

neighboring local regulators to

reach consensus (e.g., nominal

operating set-points) iteratively

among communication networks,

which causes the additional cost of

time synchronization. It is

challenging to achieve global

optimization in microgrid

operations (e.g., energy/power

dispatch) in form of a ‘‘pure’’

decentralized control.

IV. Challenges andOpportunities for Microgrid EMS

A. Dynamic energy supply

In comparison with the

topology of the bulk power

system, which is relatively static,

a microgrid can have a highly

dynamic topology and a number

of heterogeneous devices. The

ability of microgrid components

to plug-and-play is one salientfeature of the microgrid. Plug-

and-play allows any energy

source or storage device to be

connected with the microgrid,

anywhere and anytime. Since

most DGs and DESs in a

microgrid are locally owned and

operated, consumers can become

independent of the conventional

electricity supplier to a certain

extent. In other words, consumers

can operate their DGs and DESs

optimally to supply their own

load or provide ancillary services

(A/S) to the utility grid,

depending on the electricity and

A/S prices on the utility grid. The

plug-and-play functionality is the

key to equipping the microgridwith such flexibility. Essentially,

microgrids are capable of fast

reconfiguration without

redesigning the energy

management scheme.

C ontrollable loads are alsoplaying a very importantrole in microgrid operations. The

ability to shift or curtail certain

load can help improve thereliability of electricity supply to

the critical load. In addition, the

rapid deployment of electric

vehicles can further contribute to

the magnitude of controllable

loads. Ideally, customers may

charge the vehicles at any time.

But, with central/coordinated

signals from the microgrid EMS,

Table 4: Comparisons between Centralized and Decentralized Microgrid EMS.

Pros Cons

Centralized control Simple to implement. Computational burden.

Easy to maintain. Requires high-bandwidth links.

Relatively low cost. Single point of failure.

Widely used and operated. Not easy to expand.

Wide control over the entire system. Weak plug-and-play functionality.

Decentralized control Easier plug-and-play (easy to expand). Need synchronization.

Low computational cost. May be more time-consuming for local agents to reach consensus.

Avoid single point of failure. Convergence rates may be affected by the communication

network topology.

Suitable for large-scale,

complex, heterogeneous systems.

Upgrading cost on the existing

control and communication facility.

Needs new communication structure.




13/16

electric vehicles also have the

potential to shift the electric

demand for charging from peak

times to off-peak times or provide

A/S to the microgrid or the utility

grid.

M oreover, the dynamicinteractions of variousmicrogrid devices may require acomplete reconfiguration of the

microgrid network topology at

certain times, just as how

reconfiguration can be done in a

distribution system. Installation of

reliable breakers/switches is

needed to implement such actions.

Also the existing algorithms fornetwork configuration are based

on certain kind of heuristics, as the

resulting non-linear optimization

problem is of large scale and it is

difficulttofindanoptimalsolution

in real time.

B. Renewable energy

intermittency

Microgrids can be an

immediate solution to better

utilize renewable energy

resources. The United States had

2,820 MW of cumulative installed

capacity of photovoltaic in 2010,

and that figure almost doubled in

2011 (EPIA, 2012). The U.S. wind

industry installed 52 percent

more MW during the first quarterof 2012 than the first quarter of

2011. During the first quarter of

2012, the U.S. wind industry

installed 1,695 MW across 17

states. This brings cumulative

U.S. wind power capacity

installations to 48,611 MW

through the end of March 2012

(AWEA, 2012). Although a large

portion of renewable energy such

as wind power directly sends

power to the bulk power grid on

the transmission level, distributed

renewable energy sources have

been playing an increasing role in

the distribution systems.Normally, DGs using renewable

energy resource are considered as

non-dispatchable units. From a

long-term operation point of

view, the operational cost of those

renewable energy-based DGs isneglectable. The inherent

intermittency and variability of a

renewable energy resource (e.g.,

wind and solar) has complicated

implications for microgrid

operations (Wang et al., 2011a).

These renewable energy

resources tend to fluctuate

dramatically depending on the

time of day and time of year. Suchvariability and uncertainty need

to be carefully taken into account

in microgrid EMS design.

C. Other uncertainties

With increasing control loads,

the accurate load forecasting is

becoming more and more

challenging. In general, the load

profile varies with time and

season. However, the uniqueness

of microgrid controllable loads

can be present in both temporal

and spatial dimensions. For

example, unlike other traditionalpower loads, PHEVs/PEVs can

be connected to power grids

anywhere and anytime, which

brings more spatial and temporal

diversity and uncertainty (Su

et al., in press). Under the

‘‘primary’’ and ‘‘standard’’

charging level (Level 2), the

hourly charging load of a typical

battery on an electric vehicle, 6.7/7.7 kW, is approximately

equivalent to the average

household power consumption at

peak time. At this level, multiple

charging loads connected to one

feeder at peak time may cause

serious transformer overloading

during a short period of time.

Also, depending on user

preference and interest, thevehicle owner may charge a

PHEV or PEV at any charging

location (e.g., public parking deck

or home garage) and at any time.

Therefore, a well-designed

microgrid EMS has to incorporate

both spatial and temporal scales.

D. Communication

requirements

In general, the communications

network can be categorized as:

wide area network (WAN), field

area network (FAN), and home

area network (HAN). The needed

microgrid communications

network architecture falls in the

categories of FAN and HAN. A




14/16

FAN, which can be either field-

based or customer-based with

different critical requirements

(Wang et al., 2011b), is normally

implemented on the distribution

system. A HAN is usually

implemented for residentialconsumers to enable Smart Grid

functionalities such as DSM and

advanced metering infrastructure

(AMI). A reliable and compatible

communication network is

required to monitor and

effectively manage a variety of

microgrid components (e.g., DG,

DES, and load).

Two-way communication:Unlike most of existing control

and communication systems in

today’s unidirectional power

systems, two-way power flow

and information flow is the

backbone of a microgrid.

Reliability: A successful

microgrid EMS relies heavily on

the communication infrastructure

to send control signals and receivefeedback on device status.

Communication reliability is

affected by a number of possible

failures such as time-out failures,

network failures, and resource

failures (Wang et al., 2011b).

Compatibility: A number of

communication protocols (e.g.,

HomePlug, ZigBee, Cellular

Network, WiFi, and Bluetooth)can be good candidates for

achieving reliable, secure, and

two-way communication. Since

local communication nodes will

talk to each other and

communicate with the microgrid

EMS, the compatibility of various

communication technologies and

protocols is critical.

Network latency: Just as with

any communication network,

network latency may present a

problem to microgrid EMS

implementation.

Time synchronization: From

the control perspective, some of microgrid devices need to be

synchronized in real time to

achieve accurate real-time energy

management.

Cyber security: In addition to

the standard requirements for acommunications network such as

bandwidth and reliability,

security is another critical aspect

in implementing microgrid EMS.

Traditional power grid

communications mainly rely on a

dedicated wired communication

network to support reliable

monitoring and control. In a

microgrid, since more wirelesstechnologies are extensively

deployed, a unique security threat

exists due to the shared and

accessible nature of medium.

Some recent work (Ericsson, 2010)

identified the threats and

vulnerabilities of wireless

technologies and summarized

their security performance.

V. Future Trends ofMicrogrid EMS andControl

Figure 7 illustrates the history

of the power system EMS.

The future research topicsregarding a microgrid EMS can be

summarized as:

Openness: An open

communication peripheral highly

compatible and standardized

microgrid EMS enables utilities to

move from legacy operation

systems to micro-scale energy

management applications in a

highly scalable architecture.There are numerous related

standards (e.g., IEC 61850, DNP3,

C22.12) that have been recently

published or are currently being

reviewed. Since various third-

party end-user software packages

are available in the market, non-

proprietary open

communications protocols are

highly recommended. EMS architecture: The choice

of EMS architecture—centralized

or decentralized—is ultimately a

philosophical question. There are

pros and cons for both

approaches. Such a choice may

not have to be an either/or

proposition. To achieve a cost-

effective microgrid EMS with

better control performance,microgrid operators have to make

a tradeoff between those two

approaches. Those two control

strategies are not mutually

exclusive and they can operate in

harmony. A mix of microgrid

EMS architectures can combine

many of the advantages of

centralized and decentralized




15/16

approaches. A mix of microgrid

EMS architectures would be able

to facilitate the successful rollout

of microgrid deployment in the

near term. Communication gateway: A

communication gateway must be

developed to allow a microgrid to

supply ancillary services to the

main grid. A low-cost, reliable,

standardized communication

gateway should be developed to

meet both the needs of the utility/

independent system operator and

the needs of the microgrid EMS. Reliability and cyber security:

The exchanged information

among microgrid components

might be of interest to cyber

attackers. A robust microgrid

EMS needs to sustain cyber

attacks such as protocol and

routing attacks, installation of

worms/spyware/malware and

denial-of-service (DoS). Requiredcyber security features include

intrusion detection, server

firewalls, access control, and data

encryption.

Human-man interface (HMI):

On-demand microgrid

monitoring and control is

required in a microgrid EMS

design to collect system

information in real time through a

two-way communication

network. The next-generation

monitoring and control functions

should provide system operatorswith useful information rather

than raw data (Zhang et al., 2010).

The HMI should be capable of

visualizing and archiving the

collected data and processing

commands and additional

information, which moves

microgrid operations from being

data-intensive to information-

directed. On the customer side,HMI allows customers to more

actively interact with the

microgrid EMS.

Standards and protocols:

Currently, there is no such a well-

defined universal end-to-end

microgrid communications and

control standard that links all

microgrid devices with

standardized componentcapabilities. The existing IEC

61850 communications and

control standards do not fully

satisfy the need of microgrid

operations. The Institute of

Electrical and Electronics

Engineers (IEEE) has made many

efforts to develop a guideline for

the deployment of microgrids.

According the recently published

DOE microgrid report (DOE,

2011), IEEE 1547.4 was

acknowledged as the benchmark

milestone and baseline standardfor microgrids. IEEE P1547.8

would further support the IEEE

1547 standard to develop a

national standard for microgrids.

The IEEE 2030 Smart Grid

Interoperability Series of

Standards (IEEE Standards

Association, 2012) were also

considered an important standard

with respect to interoperability inmicrogrids. It addresses the

interoperability of energy

technology and information

technology operation with electric

power systems and end-use

applications and loads.

VI. Conclusion

In summary, microgrids are one

promising technology that can

increase the reliability and

economics of energy supply to end

consumers. According to Pike

Research (Pike Research, 2011),

microgrid development is shifting

from prototype demonstration

and pilot projects to full-scale

[

Figure 7: History of General EMSSource: H. Lee Smith (2010) and IBM (2010).




16/16

commercial deployment.

Microgrid energy management

systems are critical components

that can help microgrids come to

fruition.&

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