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36 E L E C T R I C P E R S P E C T I V E S

Electric utilities see new opportunities in the enormous amounts of data they now collect from the smart grid.By Dennis J. Wamsted

DATA D R I V E N

36 E L E C T R I C P E R S P E C T I V E SE L E C T R I C P E R S P E C T I V E S

M A R C H / A P R I L 2 013 37

The numbers are truly staggering.

Southern California Edi-

son’s (SCE’s) SmartConnect

program collects more data

every 12 hours than it previ-

ously did in an entire year. In

total, the utility says, it will pull

in roughly 5.6 billion meter

reads a month from its roughly

4.9-million metered customers,

requiring about 28 gigabytes of

storage daily, or slightly more

than 10 terabytes a year.

In 2012, CenterPoint En-

ergy collected 99 data points

every day from its 2.2 mil-

lion smart meters, compared

to just one data point per

month with its old analog me-

ters. By year’s end, the com-

pany needed 30 terabytes of

storage to accommodate the

217,800,000 data points it was

bringing in every day from the

system.

M A R C H / A P R I L 2 013M A R C H / A P R I L 2 013 37Masterfi le


Dennis Wamsted is an energy business writer in Arlington, VA.

Similarly, data storage needs at PPL Electric Utilities have ballooned in re-cent years. For example, the utility’s meter data management system data-base now holds more than seven tera-bytes of data—much more than the three terabytes in the system’s initial design—and it is still grow-ing.

Utilities have coped well with these skyrocketing storage needs, says Gerald Gray, senior project man-ager for utility enterprise architecture at the Electric Power Research Institute (EPRI), the utility industry’s research and development organization. But storage is not the problem, he adds. The real is-sue is being able to use the data. Here, progress has been much slower.

Gray, who facilitated a utility chief information offi cer workshop on these issues late last year, recalls one par-ticipant saying, “It would be great if we could ask the data a question.” That really is the challenge facing the in-dustry from now on, says Gray: “What information can we get out of these data? Analytics is the thing that’s on everyone’s mind.”

Testing the WaterAnalytics is clearly on Mark Podorsky’s mind at SCE. “I want to do more with the data we are collecting,” says Podor-sky, principal manager of SCE’s Smart-Connect program. “I want to be able to manage the health of the assets on the SCE system. I want to create programs that are valuable for our customers.”

But fi rst, he cautions, the company must develop a system for governing and using all the new data it collects, having just hooked up the last of the company’s roughly 4.9 million smart meters late last year. As he describes it, there are data at rest (historical), data in motion (real-time system informa-tion), structured data from within the utility, unstructured data from custom-ers (such as Facebook postings and Twitter feeds about outages), and data

in doubt (when, for example, there is a discrepancy between fi nancial and engineering information). You must verify all that data, he says, or you may unwittingly be following the “garbage-in, garbage-out” philosophy.

“Doing predictive analytics using bad data gets you nothing,” he says.

As a starter, his shop has been correlating the new meter data with weather statistics and other infor-mation to identify possible theft and line-loss prob-lems on SCE’s system. This is just in the proof-of-con-cept-stage, he says, “but it is a key step for us in us-

ing the data for something other than billing.” It is also essential in the long term, he points out, because without meter readers on the ground the com-pany plans to develop a method of us-ing data to pinpoint theft and similar problems.

Other, perhaps more valuable uses of the data, such as for running pre-dictive maintenance programs (for transformers, substations, and so on),

will have to wait, adds Podorsky. “We are still not to a point in the maturity curve where we are comfortable with the data. We’ll get there, we will, but it is going to take time.”

While Podorsky deals with the data, Doug Kim, director of advanced tech-nology for SCE, is focused on testing the various analytic technologies. “There is a good deal of promise from the meter data,” he says, “and there potentially are a number of disruptive data tech-nologies coming into the market in the near term.” But before these new technologies get on SCE’s system, they will have to pass muster in Kim’s shop. “We do our testing quite deliberately,” he says. “We want to be sure it works.”

And this combination works for SCE. “We are focused on doing it right the fi rst time,” says Podorsky. “That is why we are comfortable taking baby steps.”

CVR Takes HoldDominion also is taking baby steps, having installed just 110,000 smart meters in three pilots across Virginia. But Brandon Stites says the lessons the company is learning will pay big divi-dends when it expands its program. To

“WHAT INFORMATION CAN WE GET

OUT OF THESE DATA? ANALYTICS IS

THE THING THAT’S ON EVERYONE’S

MIND.”

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date, Dominion, which has roughly 2.5 million customers, has concentrated on five core capabilities, explains Stites, director of automated meter in-frastructure and energy conservation at the utility:■ conservation voltage reduction (CVR);■ remote meter reading;■ outage and restoration notifi cation;■ remote connect and disconnect; and■ a dynamic pricing pilot.

“This has been a learning process,” says Stites, adding that the company is pleased with the pilots’ results, partic-ularly regarding CVR. Otherwise known as volt/var optimization (VVO), CVR is an energy-saving technique whereby the utility can reduce the voltage of the power it sends out while ensur-ing that the voltage stays within ac-ceptable operating limits (the range is from 114-126 volts). In the old analog days, utilities had little choice but to send out power at the high end of the allowable voltage range, around 124 volts, to ensure that when the power reached the end of each distribution line it was still within acceptable limits. This wasted energy, and money, but there was no practical alternative.

Now, with the ability to read the volt-age at each meter, utilities have more options. Getting voltage data at the customer level in real time—data that previously had only been available at the substation level—allows utilities to be much smarter in setting voltage. Dominion has been one of the com-panies leading the effort to capitalize on CVR. In its ongoing testing, Stites says, Dominion has posted average energy savings of between 2 and 3 percent, with some circuits closer to 4 percent and others slightly lower. The next step will be to incorporate adaptive al-gorithms into the program to analyze circuit-level volt-age.

Once this is done, Stites says, the company an-ticipates that energy savings of 3-4 percent will be possible, while still providing the needed voltage. Indeed, he says, customers shouldn’t notice a thing—other than a reduction in their utility bills.

For this year, Stites adds, one of his key goals is to upgrade the software

running the CVR program to incorpo-rate demand response (DR). Under the current schedule, he says, “Virginia Power [Dominion’s operating company in Virginia] will be piloting CVR-based demand response this year.”

AEP is another proponent of CVR. “We have a number of volt-var dem-onstration projects under way and we are seeing an average reduction of 3

percent in energy use in those areas,” says Chuck Talley, manager of distribu-tion engineering service for the utility company. “We are convinced that it works.”

In one test, according to a paper by Tom Weaver, man-ager of distribution system planning at AEP, 11 feeders at fi ve substations recorded an average reduction in en-

ergy consumption of 2.9 percent dur-ing a 60-day evaluation period. During 30 days of operation, Weaver added, CVR cut electricity consumption by 251 megawatt-hours on the 11 feeders.

Despite this technical optimism, policy decisions may hold up the broader use of the technology, Talley

GETTING DATA AT THE CUSTOMER

LEVEL IN REAL TIME ALLOWS

UTILITIES TO BE MUCH

SMARTER IN SETTING

VOLTAGE.

M A R C H / A P R I L 2 013M A R C H / A P R I L 2 013 39


says. A key unanswered point at the moment is how state regulators will treat the energy savings. If utilities can’t use the reductions for compliance with statewide energy efficiency goals or as part of their energy effi ciency pro-grams, they will be less inclined to move forward, Talley predicts.

But regulators took a step forward on this issue late last year. At the Na-tional Association of Regulatory Utility Commissioners (NARUC) annual meet-ing, the members adopted a resolution

NARUC’s action is a good fi rst step, says Kelly Warner, executive vice president of Applied Energy Group, a consulting firm. Twenty-eight states have some form of energy effi ciency

requirement for utilities, and the companies by and large have been struggling to meet those statewide goals. CVR offers a viable option for compliance, he says. “It is controllable, can be very cost-effective, and is scal-able. The benefi ts are huge.”

A Commercial ForayWhile those concerns may have slowed CVR’s adoption elsewhere, Dominion’s test-

ing has been so positive that, in 2012, it established a subsidiary, DVI, to mar-ket the technology under the moniker EDGE, for “energy distribution and grid effi ciency.”

“Smart meters enable a multitude of applications,” says Todd Headlee, director of DVI, “but few are as compel-ling now as CVR.”

The beauty of the EDGE software, adds Headlee, is that it is capable of fi nding where the voltage is lowest on

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that encourages public service com-missions and other state and regional regulatory bodies “to certify energy ef-fi ciency and demand reductions asso-ciated with utility grid modernization efforts, including, but not limited to, the deployment of volt/var optimization technologies, as qualified resources in meeting legisla-tive or regulatory energy ef-fi ciency resource standards and/or regulatory expecta-tions and orders to achieve prescribed levels of energy and demand reductions.”

Another issue is how states will treat the recovery of fi xed costs when custom-ers are using less energy; this is an is-sue associated with all utility energy effi ciency programs or initiatives. How much customers pay for a utility’s fi xed costs generally is linked to energy us-age. So removing the disincentive to the utility for helping its customers cut their energy usage is also important.

The NARUC resolution also urges state commissions to ensure that utili-ties “are not fi nancially burdened” as a result of their VVO programs.

THE NARUC RESOLU-

TION URGES STATE COM-MISSIONS TO ENSURE THAT

UTILITIES “ARE NOT

FINANCIALLY BURDENED” AS A RESULT

OF THEIR VVO PROGRAMS.

Big

sto

ck

Reliability improvements

Revenue assurance

Voltage optimization

Energy loss reduction

Demand management

Operational efficiencies

Outage management

How do I realize beyond a meter read?

Future. Ready.SM

befutureready.com/bizcase

business value


a given circuit. The easy answer is that it will be the last meter on the circuit, but this isn’t always true.

DVI announced its fi rst commercial user in December when Central Lin-coln People’s Utility District, Oregon’s

fourth largest utility, signed on to use the software. According to Headlee, DVI

is in fi nal negotiations with another six customers and hopes to land 20 more in 2013.

“This is not a science experiment,” Headlee says. “We see this as a profi t center. We are at the stage where utili-ties are ready. It is a plat-form that we can build on.”

Customers already plan to use EDGE in different ways. Headlee says that one of the companies currently negotiating with DVI likely won’t use the software for CVR but rather will operate it as an on-call DR technique. Instead of running it 24/7, this com-pany will use it only on high demand days to cut load, when it could poten-tially shave 5 percent from peak levels.

One intriguing future application of the technology, Headlee adds, is in a microgrid setting. Once you are behind the meter, so to speak, you can drop the voltage even lower, below the 114-volt limit under which utilities operate, since appliances and the like are all manufactured to run on 110 volts. That

opens the door for even greater energy savings, he notes.

Currently, DVI is discussing this po-tential with Virginia Commonwealth University in Richmond, but talks are still in the early stages. One of the key decisions, says Headlee, will be fi gur-ing out how to market what he calls

micro-CVR. “Do you ap-proach the customer or try to market this through the utility?”

Tip of the IcebergStites says that the EDGE

software is just the begin-ning. Dominion’s pilot work will serve as the infrastruc-

ture for the future, he says. “There is a lot more to come. We are just looking at the tip of the iceberg right now.”

One area that is high on Stites’ list is predictive maintenance. The company has not yet ventured into this arena, he says, but it looks like one with a great deal of possibility.

Stites also seconded Podorsky’s cau-tion about the need for accurate data, pointing out that one of the reasons Dominion is taking such a gradual ap-

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proach is to ensure that the utility has good protocols in place for collecting, using, storing, and safeguarding the data. “We are walking before we run with our 100,000-plus meters,” he says.

One of the decisions Dominion has made that differs from SCE’s and Cen-terPoint Energy’s is that it is not pulling in all the meter data generated in its pilots and storing them. Instead, says Stites, the company is pulling in only information for which it has identifi ed a need. “We extract and store the data when there is a business requirement to do so,” he says.

Analytical RevolutionCenterPoint Energy completed the last of its smart meter installations last summer, finishing a three-and-a half-year process that Kenny Mercado, division senior vice president of grid and market operations, says has com-pletely changed how the company does business. The data has enabled the company to eliminate manual meter reading and the thousands of associ-ated daily truck rolls, helped it more quickly identify and stop potential tam-pering or theft, and greatly enhanced

its ability to respond to and manage system outages. None of that will come as a surprise to anyone in the industry, as utilities with automated metering infrastructure programs nationwide generally have focused on similar, rela-tively easy-to-implement initiatives.

But this is just the beginning, says Mercado. The digital technologies on its system give the company the abil-ity to “see” what is happening in es-sentially real time, he says. “We have more and more visibility onto our grid.” Soon, he continues, the com-

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pany will be able to see a fault on the line as it is oc-curring instead of waiting for a line worker to roll out to the problem area. This will change how we oper-ate the grid, and how we talk to and present data to our customers, he adds.

“We’re not there yet,” says Mercado. “But there is no doubt that data analytics is about to unleash its potential on the industry.”

For CenterPoint Energy, the first foray into this new realm of data ana-lytics will come in the form of a pre-dictive maintenance program for its transformers, which the utility hopes to unveil at least in test mode this sum-mer. The unrelenting heat that settles over Houston during the summer al-ways results in transformer failures as the units never get a chance to cool down. But until now the company could do little but reschedule mainte-nance crews for evening shifts to en-sure they had the ability to install new equipment—but that still meant hours without power for affected customers.

Now, said Gary Hayes, division vice

president and chief in-formation officer, Cen-terPoint Energy will link the 96 meter reads it gets daily from each house with those from other houses on a shared trans-former, incorporating past performance infor-mation, industry speci-fications on transformer

performance, and other meter data to help predict when the transformer re-quires proactive maintenance.

The program is not yet in the fi eld, but Mercado is confi dent. “It will work. It is just a question of time.”

PPL Electric Utilities is also looking to develop its predictive maintenance capabilities, says Mike Godorov, se-nior project manager for the compa-ny’s smart grid programs. PPL Electric Utilities’ goals—to upgrade an aging system and improve reliability—are somewhat different from CenterPoint Energy’s, but the analytical require-ments largely will end up being the same, he says. The company wants to be able to look at the data and see which pieces of equipment need to

be replaced and which can be kept in operation. By doing this, he adds, the company will be able to wisely spend its capital budget through optimizing its investment dollars. The company is also hoping to use the data “to fi gure out whether to upgrade an entire area, or just the worst-performing circuits.”

PPL Electric Utilities is not there yet, though, he cautions. The company has had smart meters installed for the past 10 years, and it is bringing back a host of data into its operations systems, says Godorov. “But we haven’t optimized it yet for distribution operations. We will be working on how to apply the data and then aggregate them to make it useful for distribution operators and others in the company.”

“Analytics is a big, big issue,” he con-cluded.

No More SilosThe rush of data into its system has prompted CenterPoint Energy to re-think how it operates, says Hayes. Previously, virtually all the data in its system were historical; and the com-pany could analyze them and prepare reports. That has all changed. The

PPL ELECTRIC UTILITIES WANTS

TO BE ABLE TO LOOK AT THE

DATA AND SEE WHETHER EQUIP-

MENT NEEDS TO BE REPLACED

OR KEPT IN OPERATION.

44 E L E C T R I C P E R S P E C T I V E SE L E C T R I C P E R S P E C T I V E S

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M A R C H / A P R I L 2 013 45

company now gets reams of daily in-formation—and it had to figure out how to analyze it, albeit still in an after-the-fact report fashion, says Hayes. In addition, the company also needs to fi gure out how to analyze data in real time, as it is streaming into the system.

The company had to change how it approached the data. “What we found,” says Hayes, “is that we needed to slow down for a bit in order to go faster again.” In particular, he said, the company realized that analytics is dif-ferent from reporting, and the skill sets and the types of people involved are different.

That prompted the company to reach across the organization for infor-

mation and skills, con-tinues Mer-cado. The result is that t h e c o m -pany culture

has changed. “Five years ago,” he says, “we were much more in our silos, but not anymore. We depend on experts across the chain within the company.”

While acknowledging that it sounds hokey, Hayes said the operating man-tra at the company stopped being “I’m

in IT” or “I’m in OT” (operations tech-nology) and became, “We are all in CenterPoint Energy technology.”

“Customer technology, IT, and OT are all being molded into one,” he says.

Dave DuCharme, vice president at Capgemini and head of the firm’s North America energy practice, echoes that point. “Big data has to be done across the board,” he says, in order to take advantage of it. The model must stretch across the company’s business units and not become stuck in individ-ual silos. To do this requires consensus, budget commitment, and leadership from the top to overcome the worries and constraints of individual business units.

Broader AcceptanceCompanies see the increasing value of the grid data they collect for a variety of operations. “A lot more utilities are now looking to leverage this information,” says Paul De Martini, managing direc-tor at Newport Consulting Group in California. But he adds that we are only at the beginning of the data analytics transformation.

De Martini, who previously was vice president of advanced technology at SCE, lists three transformation stages: situational awareness; situational in-

telligence; and situational control. Most utilities are in the situational awareness phase, he says. Smart me-ters, synchrophasors, fault circuit indicators, and simi-lar smart technologies are telling companies a lot—the power is out, power has been

restored, and so forth—but, other than acting on that kind of information, companies are not yet using that infor-mation for anything else.

Some utilities are in the situational intelligence phase, says De Martini, wherein they take the data from their system and turn them into actionable intelligence. Pepco, for example, has contracted with Gridiant, a grid-man-agement software company, to fi nd out where the utility is using power fl ows on the system, so that it can pinpoint where to invest to boost system reli-ability.

OG&E, reports De Martini, is pursu-ing an aggressive DR program as part of its goal not to build another fossil-fuel plant before 2020. As part of the initia-

“CUSTOMER TECHNOLOGY, IT, AND OT ARE ALL BEING MOLDED

INTO ONE.”

“A LOT MORE UTILITIES ARE NOW

LOOKING TO LEVERAGE

THIS INFOR-MATION.”

B ig data analytics help utilities turn the smart-grid data deluge into actionable insight. Web-scale technologies make it pos-sible to integrate large amounts of data across multitudes of

previously disconnected data sets to provide utilities with end-to-end system visibility across their supply- and demand-side opera-tions. With this insight, companies can both capture the full value of

their smart grid investments and increase customer engagement and satisfaction.

It is a big job—Pacific Gas and Electric (PG&E), for example, works in partnership with Ac-

centure and C3 Energy to handle the data and analysis. PG&E uses C3 Energy’s “software as a service” analytics platform and data-integration function to collect, normalize, and analyze more than 28 billion rows of billing and smart-meter infrastructure data from 450,000 commercial and industrial customers, along with data from 18 other, independent systems. With the technology company’s on-line portals, customers can analyze and visualize their energy usage

and consumption trends across facilities, benchmark their facilities, select energy savings plans, and track their effectiveness.

“The analytics and integration solutions enable us to quickly, efficiently, and seamlessly integrate very large data volumes,” said Brian Rich, vice president of IT business technology at PG&E. “It’s a compelling architectural benefit for us.”

As the value of big data analytics becomes clearer, utilities are looking for enterprise-wide approaches that optimize business ef-ficiencies, increase system reliability, reduce costs, and deepen customer engagement. Accenture plays a big role here. “Many are concerned with the complexity and security implications of inte-grating disparate sources of data,” said Kelly P. Gallant, managing director of the consultancy’s North American utilities practice. In Accenture’s view, an overarching, business case-driven approach to leveraging data analytics can help ensure that a utility maximizes the use of the data in both a meaningful and a secure manner.

“Utilities are at the tip of the iceberg in terms of realizing the im-mense value of analytics to positively impact their businesses,” said Gallant.

Partnering to Parse the Data


tive, the utility contracted with GridGlo to use con-sumer behavior data to see how best to enhance the performance of the pro-gram.

“People are moving quickly into this phase,” he says. “They want to know how to mine the data to get a better handle on what is really happening on their system.”

In the situational control phase, utilities use their data for distribution automation and distributed control scenarios—Dominion’s EDGE software is an example, says De Martini.

Truckload of DataThe bulk of the benefi ts from the new smarter grid will come from the op-erational side, says Doug Houseman, vice president of technology and in-novations with EnerNeX and a long-time smart grid guru. And it could take

15 years to realize all of them. The problem is that there are no off-the-shelf analytic products for the operations side, he says, so the utility must custom-build everything. In addition, utilities have been grabbing the easier-to-reach benefits from billing and metering im-

provements. Still, Houseman says, “the ship is beginning to turn.”

One of the big issues going forward will be figuring out what to do with the terabytes of data now fl ooding into utility systems, he said. “The approach now is like backing the semi up, fi lling it up, and taking it back to the utility,” says Houseman. It works, but it is not ideal—too slow, too big a load.

Instead, he continues, “I would rather send out a Maserati. It would get back much quicker, and it wouldn’t have quite as much data in it.”

To run a distribution management

system properly, for example, do utili-ties need every data point, or just a sampling of data? To get the full value out of the system, utilities will have to fi gure out how to separate the data they need to run the system from every-thing else. “You don’t need big data,” Houseman points out. “You need the right pieces of big data.”

Getting the right pieces of big data is vital for another reason—economics. The data will be there, says EPRI’s Gray, but what utilities will need to hammer out is which data and which questions have value.

Here is an example. With the data now coming into many utilities, they will be able to locate where so-called momentaries (outages of fi ve or fewer minutes) are taking place, many of which are caused by vegetation brush-ing up against power lines. Having pin-pointed the location, the utility could then dispatch a crew to perform what Gray dubbed “just-in-time vegetation management.”

But this comes at a cost, he points out. If you hire a data scientist to ex-amine the data at perhaps $150,000 a year and the software and processing equipment costs another $100,000-$150,000 a year, then you’d better be getting $250,000 in benefi ts from your question, Gray says.

“However, even for those utilities that are managing the storage require-ments, there are concerns that the stor-age does not provide the processing capability to do analytics or that the uses and business cases for the data are yet to be determined,” Gray writes in a recent CIO Outlook.

Figuring out those uses and business cases is vital, but it won’t necessarily be easy. As Houseman notes: “Not all ana-lytics are created equal, and not all big data are created equal.”

Still, fi ve years from now, we proba-bly will be stunned by the transition to big data analytics. “We are at the pre-app stage of the smart phone develop-ment curve,” concludes Capgemini’s DuCharme. “Change is coming.”

Adds Applied Energy Group’s War-ner: “We are right at an inflection point.” ◆

ONE OF THE BIG ISSUES GOING

FORWARD WILL BE FIGURING OUT

WHAT TO DO WITH THE TERA-BYTES OF DATA

NOW FLOODING INTO UTILITY

SYSTEMS.

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