Accenture Unlocking Value Metrics

7/31/2019 Accenture Unlocking Value Metrics

1/28

Unlocking the value of metricsMaximizing smart grid technologies for high performance


2/28

2

Introduction 3

Finding No. 1 5Although utilities have accelerated their implementationof smart grid technologies, many have yet to realize all thetargeted benefits, which is where metrics play a critical role.

Finding No. 2 11While utilities are using metrics to measure smart grid

performance, many could benefit from additional data andbenchmarks to maximize the value of follow-on analysis.

Metrics inventory 15

Implications for utilities 23

Conclusion 26

Contents


3/28

3

A smart grid is a communication-enabled electrical grid that collects

and acts on information about thebehavior of all participants (energyproviders and consumers) in order toimprove the economics, efficiency,reliability, importance and sustainabilityof electricity services. It has thepromise of self-diagnosing issues andself-healing, incorporating numerousadvanced technologies at all stagesof the electricity supply chain.

The transition from a traditional networkto a smart grid requires significant

investments in infrastructure and widedeployments of technology. The ability toefficiently monitor and ultimately managethese technologies will determine smartgrid performance and will be critical forthe success of utilities in the future.

Over the years, different energyproviders or regulating bodies haveestablished metrics that determinehow well the grid operates in termsof reliability and network availability.Such metrics have helped form leading

practices that enable providers torun their systems more reliably andenhance their customers satisfaction.

Today, in North America and Europe,government funding for smart grid

initiatives has ushered in a new wave ofreporting requirements. Around the world,utilities and government agencies areworking on quantifying and defining themost meaningful smart grid measures.

To understand what utilities are doing inthe smart grid metrics space, Accenturesurveyed utilities around the globe.The survey was designed to collect arepresentative sampling of metrics usedto track the extent to which the gridis being modernized (made smarter)

and how its performance (i.e., keybenefits of being smarter) is tracked. Inconducting the survey and its subsequentanalysis, we found regional synergiesand differences spanning the drivers/objectives of the modernization effortsto the metrics used, and the frequencyof their use. This paper delves into ametrics inventory to explore not onlywhat utilities measure, but also how theyare measured and who specifically hasresponsibility for the measurement.

Introduction


4/28

4

This quantitative survey isbased on telephone interviewswith 32 utilities executiveslocated in North America,Europe, Asia-Pacific and LatinAmerica. All survey participantsqualified themselves asinvolved in the decision-makingprocess or being an influencerregarding the decisions of theircompany related to smart gridperformance. As Figure 1 shows,more than three-quarters of

respondents were based eitherin North America or Europe, andmore than half of participatingexecutives were from utilitieswith more than $10 billion inrevenues, with cross-segmentcapabilities in generation,transmission and distributionand retail. The fieldwork wasconducted by MarketOneInternational between July andAugust 2011.

Methodological notes:

All answers are based on thetotal number of respondents toeach question, which may varyin some cases and which excludenonanswers.

Regional breakdowns shownin the survey results should beconsidered high-level trends, giventhe limited regional sample size.

More than two-thirds of therespondents had operationsspanning from generation to retail.

Methodology

Figure 1. Profile of participating utilities.

Geographic repartition

28%

3%Other

Latin America 3%

Asia-Pacific 9%

Europe

North America 56%

Group total revenue 2010 (USD)

$3 billion-$5 b illion

18%

$1 billion-$3 billion 16%

< $1 billion

16%

> $10 billion50%

Sector segments

T&D, Retail

16%

Generation, T&D, Retail

Note: Due to rounding, some totals do not equal100 percent.

Retail

3%

69%

Generation, T&D

3%

T&D

6%

Generation

3%


5/28

5

Finding No. 1

Although utilities have accelerated their

implementation of smart grid technologies,many have yet to realize all targeted

benefits, which is where metrics play a

critical role.


6/28

6

Smart grid implementationand investment are growing.

As illustrated in Figure 2, more thantwo-thirds of utilities say they haveimplemented smart grid technologieswithin the past five years.

Regardless of where any utility standstoday with its smart grid plans, themajority of utilities are accelerating thedevelopment, rollout and use of smart gridtechnologies, as more than 80 percentof respondents indicate that they willincrease their smart grid investmentsover the next five years, with just overone-quarter indicating they will increaseinvestment by 20 percent or more (seeFigure 3). The trend likely reflects the shiftin smart grid deployments from pilots tofull rollouts under way.

The main driver behind this trendvaries by region although, overall,respondents indicate grid reliabilityand improving customer choice are theprimary reasons for increased smartgrid activity (see Figure 4). In NorthAmerica, the majority of utilities citeimprove system economics as thekey driver, while European utilities alsoadded environmental drivers to the mix,though they cite the need to maintainor enhance system reliability as theirprimary driver. In both of these regions,

utilities rate increase customer choiceas a close runner-up as the key driverbehind smart grid growth.

Base: All respondents.

More than f ive

years ago31%

Between three andf ive years ago

25%

Between two and

three years ago28%

Within the past year 16%

69%

Signif icant decrease

(more than 20% lower) 0%

Moderate decrease(less than 20% lower)

3%

No change 16%

Moderate increase(less than 20% higher) 55%

Signif icant increase(more than 20% higherthan f ive years ago)

26%


Figure 2. When did you start implementing smart grid technologies in yourcompany?

Figure 3. How will your company change its total investment (including internalresources) to develop and implement smart grid technologies in the next five years?

Note: Other drivers mentionedgovernment mandates, data analytics, reduce peak load, etc.


Methodological note: Regional breakdowns shown in the survey results should be considered only high-level trends, given the limited regional sample size.

*All drivers appeared among respondents top three.

Enhance environmental compliance

Maintain or improve power quality and reliability

Improve system economics

Increase customer choice

Maintain or enhance system reliability

20%

36%

48%

54%

61%

33%

50%

43%

57%

67%

10%

40%

63%

56%

56%

Top three drivers* Europe North America

Figure 4. What were the main drivers of your companys decision to implement smart grid technologies?


7/28

7

Based on the top three drivers for smartgrid implementation (identified in Figure4), the utilities were surveyed abouteach drivers relative importance andhow priorities will change over the nextfive years (see Figure 5). Ninety percentof respondents state that the seconddriver, increase customer choice willgain significant importance as the driving

factor behind smart grid implementations.Additionally, economics and complianceissues will also lead the way as importantdrivers for smart grid implementations.Yet there was an even 50/50 split onhow utilities perceive the emphasis onthe need to maintain or improve powerquality and reliability, perhaps implyingthat this is an important issue now, andwould remain so.

Many smart grid benefits are

still unrealized.

While utilities are ramping up their smartgrid efforts, benefits realization is laggingbehind investments. This is likely anindicator that the industry is still early inits stage of smart grid implementation.In response to a list of end results,respondents say they have yet toachieve all the benefits they expect fromimplementing smart grid technologies (seeFigure 6).

Overall, a maximum one-third ofrespondents have achieved targetedresults, such as effective systemprotection and restoration and highergrid efficiency. Beyond these two results,the rate of achievement drops off.

For example, we found that enhancedtransmission and distribution gridmanagement is a result all utilities seek,yet this benefit ranked as the top targetthat has not been achieved. According toour survey responses, only one-quarter

have achieved it. Similarly, we also seeproduct and service innovation scoringan achievement factor of just 14 percentand effective demand response to reducepeak demand representing a higher butstill struggling achievement quotient of 19percent.

...will remain stable ...will increase

Improve system economics

Maintain o r improve power

quality and reliability

Enhance environmental

compliance

Increase customer choice

Maintain or enhance sys tem

reliability

36%

20%

48%

54%

61%

Top three drivers*

32%

50%

34%

41%

50%

10% 90%

66%

59%

68%

Base: All resp ondents.

*All dri vers appeared among respondents top three.

Figure 5. What were the main drivers of your companys decision to implementsmart grid technologies? Do you expect the importance of each driver to increase,decrease or remain stable in the next five years?

Optimized plug-in electric vehicleintegration

Effective system protection andrestoration

High system resiliency

Effective demand response toreduce peak demand

Optimum asset utilization

Higher grid efficiency

Deferral of capital expansion

High resiliency against naturaldisasters

Optimized bulk wind andphotovoltaic integration

Reduced greenhouse gas emissions

Product and service innovation

Enhanced transmission anddistribution grid management

33%

25%

30%

21%

19%

23%

14%

6%

16%

7%

23%

25%

64%

21% 65%

17% 60%

15% 66%

13% 66%

13% 57%

11%

55%

33%44%

39%

42%42%

50%43%

75%

64%3%

Base: All resp ondents.

Not targeted Targeted but not achieved yet Targeted and achieved

Figure 6. Which of the following results did you target and which did you achieve?


8/28

8

There are some regionaldifferences as well.

For the two regions illustrated in Figure7, utilities are fairly consistent in theirtargeted (but not achieved) benefits,although a few exceptions stand out.While, in Figure 6, almost 90 percent ofthe surveyed utilities indicated that they

targeted deferral of capital expendituresin their smart grid deployments, theregional results differ: Three-quartersof North American utilities have yet torealize their goals versus 44 percent ofEuropean utilities. Conversely, about 90percent of the European respondents saythey have yet to meet their goals aroundintegrating renewable energies whereas,in North America, that number is onlyabout a third. This likely demonstratesthe difficulties associated with large-

scale deployment of renewable energiesand integration in Europe, and possiblydiffering regional goals and the still earlyphase of adoption of smart grids.

67%50%

82%

63%

67%67%

50%67%

Higher grid efficiency

67%67%Effective demand response to reduce peak demand

Optimized bulk wind and photovoltaic integration

Reduced greenhouse gas emissions

High resiliency against natural disasters44%

28%

50%22%

56%

89%33%

High system resiliency

Effective system protection and restoration

67%

Product and service innovation63%

71%

Optimized plug-in electric vehicle integration

44%

Enhanced transmission and distribution grid management

76%

56%72%

Deferral of capital expansion

Optimum asset utilization

Base: North America and Europe respondents.Methodological note: Regional breakdowns shown in the survey results should be considered only high-level trends, given the limited regional sample size.

EuropeNorth America

Figure 7. Results targeted but not yet achieved.


9/28

9

For all, there is a need formetrics that effectively tracksmart grid performance.

While not a comprehensive global surveysample, the data may nonetheless revealtrends on the relative differences betweenNorth American and European utilities andhow they have chosen and met particular

goals. It also demonstrates the differencesin challenges both regions face in theirelectrical grids. One thing that does notvary by region is the consensus amongall respondents that it is important forutilities to have and use the metrics thathelp them accurately measure and managethe performance of their chosen smart gridtechnologies: All respondents say that doingso is critical or important to the successof their smart grid initiatives (see Figure 8).

As to the relative importance of metricslisted in Figure 9utilities across allgeographies indicate that objectivessuch as demonstrate compliance withregulations/standards and monitorreliability are the most critical ones.Among other leading objectives thatrespondents rate as either critical orimportant are the abilities to monitor

operational efficiency, analyze demandconsumption and indicate potentialrisks.

Not impo rtant at all

Not really important

Important

Critical

0%

0%

41%

59%


100%

Figure 8. How important is it for yourcompany to have metrics to measureand monitor the performance of smartgrid technologies?

44%Monetize carbon emissions reductions 9% 3%44% 47%

63%

37%

16%

7%

3%

2%

28%

38%

41%

0%

0%

0%

2%Measure the emergence of new technologies(e.g., photovoltaics installed, EV penetration)

6% 53%Monitor reliability

13% 22%

Develop and analyze economic development indicators

63%

Demonstrate compliance with regulations/standards

13%

Monitor operational eff iciency(e.g., call centers, system operations)

40% 40%

9%Indicate potential risks

66%16%

7% 53%

Analyze demand consumption 6% 56%

Important+ critical

85%

82%

47%


94%

94%

91%

90%

Not impo rtant at all No t v ery imp ortant Imp ortant Critic al

Figure 9. What is the importance of the following objectives for smart grid performance metrics?


10/28

10

Figure 10 compares how two regionsrate the importance of various metrics.All European respondents say thatto measure the emergence of newtechnologies such as photovoltaicand electric vehicle (EV) penetration iscritical or important, while only two-thirds of North American respondentssay the same. In addition, slightly less

than half of European respondentssay they strive to monetize carbonemissions reductions versus a third ofNorth American respondents. It seemsto imply that the green agenda is moreprevalent in Europe than in North America(likely due to societal demand and/orgovernment policy mandates).

Monetize carbon emissions reductions44%

33%

100%

94%

Develop and analyze economic development indicators44%

47%

Measure the emergence of new technologies(e.g., photovoltaics installed, EV penetration) 100%

67%

94%100%

Indicate potential risks 89% 100%

Analyze demand consumption

83%

Monitor operational efficiency(e.g., call centers, system operations)

89%100%

Monitor reliability

89%

EuropeNorth America

Base: North America and Europe respondents.Methodological note: Regional breakdowns shown in the survey results should be considered only high-level trends, given the limited regional sample size.

Demonstrate compliance with regulations/standards

Figure 10. Smart grid performance metrics objectives: important + critical.


11/28

11

Finding No. 2

While utilities are using metrics to measure

smart grid performance, many could benefitfrom additional data and benchmarks to

maximize the value of follow-on analysis.


12/28

12

Utilities can improve howthey apply metrics to managesmart grid performance.

Regarding the question: To what extentdo current metrics enable efficientmonitoring of smart grid performance?,the research shows significant room forimprovement in how companies design

and use metrics: Only 10 percent saythat there is no improvement requiredand that they have all the informationthey need (see Figure 11). Slightly morethan half of the respondents state thatwhile they have some information,they require improvements to optimizesmart grid performance management.About a third indicate that theyeither have limited information andsignificant improvements are requiredto optimize smart grid performancemanagement or the metrics they havedo not enable smart grid performancemanagement at all. While this may bea clear indication that smart grids arenow starting to emerge out of pilotphases, it also demonstrates that workon metrics is still needed to optimizethe deployment of technology.

Most utilities already perform somedata comparison and analysis acrosscertain metrics. As one form of analytics,providers typically compare historicalperformance data in the areas oftransmission, distribution, end-usecustomers, and societal impact (seeFigure 12). As Figure 13 shows, abouthalf of respondents always/systematicallyuse metrics for predictive analysis,with distribution being the highest.

To a great extentno improvement required/youhave all the information you need

6%

27%

57%

10%


To some extentyou have some information butimprovements are required to optimize smart gridperformance management

To a limited extentyou have limited information

and significant improvements are required tooptimize smart grid performance management

Not at allthe metrics you have do not enable smartgrid performance management at all

Figure 11. To what extent do the current metrics designed and implemented in yourcompany enable efficient monitoring of smart grid performance?

Base: All respondents.Methodological note: Respondent base varies depending on the sector segment(s) in which a given utility operates.

73%82%

62%67%

Distribution

11% 10%

22%7%

Often

Always/systematically

Transmission End-use customers

11%Rarely

Societal impact

17%

13%

25%

Figure 12. Metrics analysis performed: Comparison with historical performance.

DistributionTransmission End-use customers Societal impact

44%59%

51% 46%

22%

19%

Often

Rarely

Never

25%

21%28%

14%

Always/systematically

17%

7%

17%

22%

8%

Base: All respondents.Metho dological note: Respondent base varies depending on the sector segment(s) in which a given utility operates.

Figure 13. Metrics analysis performed: Forecast of performance using qualitative/quantitative.


13/28

13

Challenges to making betteruse of metrics stem fromspecific limitations.

According to respondents, two of themost critical challenges for utilitiesthat want to optimize smart gridperformance through better metricsand analysis are (a) difficulty to access/

collect information and (b) a lack ofactual benchmark data. As Figure 14illustrates, there are important challengesto realizing the potential of smart gridperformance through better metrics andmeasurements. Respondents indicatethey also lack tools and personnel toefficiently and effectively analyzeinformation and that, when they do try tomeasure performance, there is a lack ofgranularity in the measure. All European

respondents cite as important or criticalchallenges both a lack of sharing theinformation across the organization/lack of coordination and a lack of skillsto design, implement and analyze themetrics.

Relatively speaking, utilities seem lessconcerned about access to historical data,their ability to design proper metrics orthe frequency with which they measureperformance. Still, no less than halfof respondents say they struggle withthese issues as well. The message seemsto be that significant upside potentialexists for utilities to acquire informationresources and improve focus in orderto make effective use of metrics andmeasurements in support of better smartgrid performance.

23%

31%

21%

21%

21%

17%

17%

19%

33%54%

Lack of manpower 7% 48%14%

Insufficient frequency in measuring 10% 34% 39%

Lack of skills to design, implement and analyzethe metrics

7% 33%

66%

Lack of historical data 10% 28% 41%

Lack of sharing the information across theorganization/lack of coordination

7% 21% 51%

Lack of granularity in the measures 7%

3%

51%

Lack of efficient tools/technologies to analyzethe information

17% 57%

43%

Lack of benchmark data to analyze performance 15%

Difficulty to access/collect the information 13%

21%


Considered as a critical orimportant challenge by all therespondents in Europe

Considered as a critical orimportant challenge by all therespondents in Europe

Not important at all No t v ery imp ortant Imp ortant Critical

Figure 14. What is the importance of the following challenges that your company is facing to optimize smart grid performancemetrics?

As an industry, wereinstalling, were makingprogress, but we reallyhavent seen a forum orenough knowledge sharingyet to be able to quantify

leading practices and thenstart to benchmark againstthose leading practices.

Wade Malcolm, global senior

director, Smart Grid Operational

Technology


14/28

14


15/28

15

Metrics inventory


16/28

16

Utility executives were asked severalquestions about metrics in the areas ofdistribution, end-use customers, systemsand societal impacts.

What metrics they use to measureperformance in a given segment or area

When they measure performance ofeach segment/areafrequency

How they apply metrics and measureperformancelevel of granularity

Who is in charge of analyzingperformance in a given segment/area

Distribution system metrics

As Figure 15 shows, nearly 80 percentof respondents indicate they trackdistribution reliability and power qualityindicesperhaps due to mandates

from regulators. For example, in NorthAmerica, there are more than 35 stateutility commissions requiring reliabilityreporting, with varied degrees ofcomplexity. Many commissions haveset reliability targets that utilities are

expected to achieve, and with the trendtoward more distribution companies beingrequired to meet reliability targets, theexpectation is that use of these metrics inparticular will see an upward trend. Solidhistorical information relating to systemperformance, operational equipmentperformance and cost is necessary toachieve sound reliability decisions.

Behind the reliability-driven metrics is thegroup of metrics tracking the breadth ofdistribution automation (DA). The top DAtracked metrics, not surprisingly, measurepenetration of smart grid-enabledswitches/reclosers/capacitor banks,as these have been among the first DAapplications. Following those are other DAmetrics such as distributed generationon the system, distribution circuitsthat have Volt/Var control, distributionassets with real-time condition

monitoring diagnostics and customersconnected per automated circuit.

The importance of DA metrics is expectedto increase with smart grid investments inthe distribution and transmission systems.

New DA technologies are expected tobe adopted at a large scale to makedistribution systems more controllableand flexible based on accurate data fordecision-making applications throughmore intelligent sensors, processorsand fast communications to remotelymonitor and coordinate distributionassets. Such technologies are sought to

dynamically control voltage and reactivepower that can offer important powerefficiency improvementsbetter powerquality and faster outage detection andrestoration. It is of interest to note thatpresently half of the respondents do notuse metrics to track energy storage.

The measurement frequency fordistribution performance metrics variesfrom metric to metric: slightly morethan 80 percent of respondents saythey measure reliability and power

indices more often than once peryear (again perhaps due to regulatorymandates). Conversely, they typicallymeasure the percentage of energystorage devices on the system withthe least frequency (see Figure 16).

No

Yes

Improvementsin reliability andpower indices

Percentage of companies using metrics

Note: Additional detailed answers includedreduction of losses, kW and kWH reduction;various programs to move energy from off-peak to peak; reliability and maintenance matrix focused on customer outage impacts;transformers; SAIDI, SAIFI, CAIDI; feeder DC query; and operational cost savings due to smart grid technology.Base: All respondents.Methodological note: Respondent base varies depending on the sector segment(s) in which a given utility operates.

79%

11%

67%

20%

Percentageof smart grid-enabled switches

/reclosers/capacitor banks

30%

57%

Percentage ofdistributedgeneration

on the system

57%

30%

Percentage ofdistributioncircuits that

have Volt/VAR controls

53%

37%

Percentage ofdistribution assetswith real-time

conditionmonitoring

and diagnotics

46%

39%

Percentage ofcustomersconnected per

automated circuit

50%

33%

Percentage ofenergy storagedevices

Reliability driven Distribution automation (DA) driven

Figure 15. Can you indicate the metrics related to distribution that you are using?


17/28

17

Improvementsin reliability and

power indices

More

often

Less often

Annually

Percentage ofdistributioncircuits thathave Volt/

VAR controls

11%

28%

61%

n=17

n=21

Percentage ofdistributedgeneration

on the system

17%

39%

44%

n=17

Percentage ofdistribution assets

with real-timecondition

monitoringand diagnotics

18%

24%

59%

n=16

Percentageof smart

grid-enabledswitches

/reclosers/capacitor banks

38%

10%

52%

n=20

Percentage ofenergy storage

devices

64%

18%

18%

n=10

Percentage ofcustomers

connected perautomated circuit

17%

8%

75%

n=12

Base: All respondents.Methodological notes: Respondent base varies depending on the sector segment(s) in which a given utility operates;n= number of respondents per metric.

81%

19%

Reliability driven Distribution automation (DA) driven

Figure 16. For the different distribution metrics you are using, please indicate whether you measure them on an annual basis ormore/less frequently.

Aggregated by region 19%

Aggregated bycustomer class

3%

Aggregated bysubstation

19%

For each circuit 59%

Base: All respondents.Methodological note: Respondent base varies depending onthe sector segment(s) in which a given utility operates.

Figure 17. With what granularity do youmeasure the majority of metrics relatedto distribution?

Customer service

department31%

Maintenancedepartment

31%

Outage centerdepartment

45%

Planningdepartment

66%

Operationsdepartment

Base: All respondents.Methodological note: Respondent base vari es depending onthe sec tor segment(s) in wh ich a given utility operates.

66%

Figure 18. Thinking of the key metricsrelated to distribution, who in yourorganization is responsible for analyzingthese metrics?

In terms of the granularity with whichutilities track and report on the proposeddistribution metrics, more than halfof respondents say they measureand manage smart grid performance

metrics for each circuit, while nearlytwo out of five respondents measuresmart grid distribution performanceaggregated by substation or region(see Figure 17). Again, the mandatedreliability reporting can explain theseresults as reliability reporting, whichgranulates down to the feeder (worstperforming feeder) level in most cases.

As Figure 18 shows, the typical ownerfor tracking and managing smartgrid performance metrics around

distribution varies from operations andplanning departments to the outagecenter department. Respondentsalso mention the maintenance andcustomer service departments.


18/28

18

End-use customer metrics

Innovations in smart grid technologiesgo hand-in-hand with customer benefits.As previously illustrated in the research(Figure 4), providing customers with morechoice is the second most importantdriver behind the smart grid. Moreover,providing customers with more choice isseen as the driver to most likely become

more important in the near term (Figure5). Not surprisingly, utilities indicate thatthey actively track and manage a numberof customer-related metrics and, asfocus on smart technology deploymentmoves toward benefit realization, utilitiesare likely to begin to place a greaterimportance on end-customer metrics.

Our research shows that currently thereis broad diversity among utilities whenit comes to the spectrum of traditionalmeasures, such as customer satisfaction,to track how customers receive

information from their smart meters andappliances. With a majority of utilitiesfocusing on successful deployments,managing customer perceptions of smarttechnology and regulatory compliance,it is not surprising that the majority ofutilities (slightly less than three-quarters)are focused on managing customersatisfaction. While energy savings

seems like an obvious metric, only slightlymore than half of respondents say theytrack this measure. Also, just one-thirdactually track customers who changetheir participation in smart grid programs,which is somewhat surprising given thatend customers are central to the successof many smart grid benefit and regulatorycases.

When considering this set of end-customer metrics against a deploymentschedule, the results point toward

the relative infancy of most utilities

customer-oriented smart grid programs.While only slightly more than a quarterof respondents segment customers basedon aggregated usage and only about aquarter report their customers capableof receiving/acting on information fromthe control center, it would appearthe potential customer benefits of theadvanced smart grid capabilities are yet

to be tracked in a meaningful manner.Most utilities would appear to beprimarily focused on the technology sideof the deployment (see Figure 19).

Yes

Percentage ofcustomerscapable ofreceiving/acting on

information fromcontrol center


aggregated forthe purpose ofresponding to

grid controlrequirements

Percentageof load

which canbe managed

Percentage ofcustomer

energy savings

Improvementsin power quality

Percentage ofcustomerswho have

changed theirparticipation

as a result ofusage information

Customersatisfaction

36%

13%

74%

No

Percentage ofcustomers withsmart meters

Percentage of companies using metrics

Note: Additional detailed answers included short-term active response (STAR) and load control demand response.Base: All respondents.Methodological note: Respondent base varies depending on the sector segment(s) in which a given utility operates.

43%

36%

13%

74%

55%

24%29%

50%

22%

69%

31%

55%

45%

38%

52%

33%

Figure 19. Can you indicate the metrics related to end-use customers that you are using?


19/28

19

No one metric stands out as a leadingmeasure that providers track regularly(more than once a year), and relativelyfew respondents actually track anymetric more than annually, as Figure 20illustrates. Again, these results appearto affirm the infancy of most smart griddeployments and benefits realizationaround end customers. Moreover,

customer operations have not traditionallyseen as much investment in moreadvanced analytics capabilities as otherareas of business to effectively managedata and provide insight. With the risingemphasis on the customer, we may beginto see a shift in the frequency of thesemetrics over time, as utilities begin toimplement advanced programs andproducts to support micro-generation,electric vehicles and real-time pricing.

Percentage ofcustomerscapable ofreceiving/acting on

information fromcontrol center


aggregated forthe purpose of

respondingto grid controlrequirements

Percentageof load

which canbe managed

Percentage ofcustomer

energy savings

Improvementsin power quality

Percentage ofcustomerswho have

changed theirparticipation as a

result of usageinformation

Customersatisfaction

Percentage ofcustomers withsmart meters

59% 67% 62% 64% 55%

89%

56%

86%

27%

24% 38% 22%36%

11%

22%

Less often

Annually

14% 9% 14% 9%More often22%

14%

Base: All respondents.Methodological notes: Respondent base varies depending on the sector segment(s) in which a given utility operates; n= number of respondents per metric.

n=22n=21 n=16

n=14

n=11

n=9 n=9 n=7

Figure 20. For the different end-use customer metrics you are using, please indicate whether you measure them on an annualbasis or more/less frequently.


20/28

20

As one might expect, the majority ofrespondents tend to measure customermetrics by customer class over othermeasures, such as by circuit, substationor region (see Figure 21). It appears thata portion of the utilities surveyed domeasure customer metrics at a moregranular level. This may be due in part tothe rollout of more advanced customer

programs and products, or may be aneffort to manage the grid more effectivelyby understanding customer metrics at thecircuit and substation level (for example,advanced outage management or demandresponse).

Although the customer servicedepartment serves as the lead analysisowner of end-use customer metricsaround smart grid performance (seeFigure 22), other departments such asoperations and marketing are nearly

as responsible (both at slightly lessthan half). In about one-third of cases,respondents report that they use anenergy-efficiency department to tracksmart grid performance metrics aroundthe customer. These metrics highlightthe ongoing challenge in the deploymentof smart grids: Who owns performancearound the end customer, and whomust act upon the findings? The resultsillustrate a mixed approach across therespondents highlighting the absenceof any true leading practice. As utility

smart grid benefit cases range fromgrid optimization to provisioning for thenew energy customer, it is apparent thatdepending on utility organization design,a great many areas are charged withanalyzing the end customer. Whatever thebusiness case may be for a utility, the factremains that most utilities have many, ifnot all, of the departments listed in Figure22. What is critical to success is thedistribution and effective disseminationof customer metrics between departmentsto ensure a holistic approach to engaging

customers and providing next-generationcustomer choice.

Transmission system metrics

The survey covered metrics associatedwith deployments and use of phasormeasurement units, real-time monitoring,energy storage and dynamic ratings ontransmission systems. If desired, suchresults can be obtained from Accenture.


7%

Aggregated byregion


11%

63%Aggregated bycustomer class


Figure 21. With what granularity do you measure the majority of metrics related toend-use customers?

Customer servicedepartment

45%

52%

Energy-efficiency

department

31%

Planningdepartment

31%

Marketingdepartment

45%

Operationsdepartment


Figure 22. Thinking of the key metrics related to end-use customers, who in yourorganization is responsible for analyzing these metrics?


21/28

2

Operational and societalimpact (nonoperational)metrics

Operational benefits include improvedeconomics, such as reductions inoperations and maintenance costs.Presently, such savings in operations andmaintenance costs are mapped to savings

in distribution systems and to advancedmetering infrastructure (AMI) andassociated customer systems.

Societal impact (nonoperational)benefits refer to benefits other than theoperational savings of the smart grid. Anumber of the societal impact benefitsresult from actions undertaken bycustomers in response to communicationfrom the utility. Smart metering is anenabler for some societal impact benefits,but it does not assure that these benefits

are actually realized. Other societalbenefits are independent of the userand are only related to what the utilitydoes, such as the reduction in carbonemissions from reducing transmission anddistribution losses.

Societal impact benefits may be obtaineddirectly or indirectly due to factors suchas:

Increased customer choices on how andwhen to consume electricity and from

what source.

More accurate bills and accountservicing and possible savings on electricbills.

Service quality enhancements that mayreduce the duration of outages.

More equitable rates.

Better utilization of scarce societalresources and a decrease of the carbon

footprint.

More robust electricity markets.

The demarcation between operationaland societal impact benefits is notalways clear. While a metric trackingthe penetration of renewables fits moreon the societal side, another trackinggreenhouse gas (GHG) emissionsmay find a home on both sides: Less

GHG released is a societal impactbenefit, while abatement of GHG isan operational cost. The same appliesto the number of power interruptions:The issue of fewer interruptions is asocietal impact benefit, but the utilitycost associated with the interruptionsis an operational cost. Conversely, whileoperations and maintenance costs are

operational issues, savings in these areascan reflect in a societal benefit of lowerelectric bills. Hence, a true demarcationline between operational and societalmetrics is not possible for the metrics wegathered in our research and, therefore,we illustrate this with a dashed line inFigures 23 and 24.

Figure 23 suggests the utilities polledin our research are all likely to use themetrics we inquired about, with moreemphasis on the operational metrics.

Figure 24 shows the frequency of usingthe metrics shown. From that f igure,it is interesting to note that almosttwo-thirds of the respondents measureoperational and maintenance costs lessoften than annually.


Methodological note: Respondent base varies depending on the sector segment( s) in which a given utility operates.

Lower operationaland maintenance

costs

No

Yes

18%

75%

Operational impact metrics Societal impact (nonoperational) metrics

18%

75%

Percentage(or tons) in greenhousegas emissions decrease

Fewer and lowercosts for interruptions

21%

68%

Percentage ofrenewable generationpercentage or standard

32%

57%

36%

54%

Figure 23. Can you indicate the metrics related to societal impact that you are using

Figure 24. For the different societal impact metrics you are using, please indicatewhether you measure them on an annual basis or more/less frequently.

Operational impact metrics Societal impact (nonoperational) metrics

Base: All respondents.Methodological notes: Respondent base varies depending on the sector segment( s) in which a given utility operates;n= number of respondents per metric.

65% 72%

40% 36%

30% 22%

53%43%

Less often

Annually

More often 5% 6% 7%21%

n=20 n=18

Lower operationaland maintenance

costs

Fewer and lowercosts for

interruptions

n=15

Percentage ofrenewable generationpercentage or standard

n=14

Percentage(or tons) in

greenhouse gasemissions decrease


22/28

22

The subject metrics and measures arethe least granular, as slightly more thanhalf of respondents track them at theregional level, and almost a third bycustomer class. The less granularity forsocietal impact metrics versus othertypes of metrics may be due more tothe fact that, by definition, such metricslend themselves best to people or groups

(regions, customers) versus any sort ofhardware, such as a circuit (see Figure 25).

Responsibility for these metrics isfairly evenly split among operations,planning and marketing departments.Such metrics do not fall under the financefunction (compliance) or the corporatesustainability group (see Figure 26).


52%

Aggregated bycustomer class

31%

Aggregated by region


4%


Figure 25. With what granularity do you measure the majority of metrics related tosocietal impact?

Base: All respondents.Methodological note: Respondent base varies depending on

the sector segment(s) in which a given utility operates.

Marketing department

35%

27%

Operations department

Planning department

38%

Figure 26. Thinking of the key metrics to measure societal impact, who is

responsible in your organization for analyzing these metrics?


23/28

23

Implications for utilities


24/28

24

Smart grid pilots and deploymentactivities involve substantial investmentsin the purchasing and installation ofdevices and systems. Given such sizeableinvestments as well as the great potentialof the smart grid, there is a need for afair, consistent set of metrics to measureprogress, performance and value of thesame. Additionally, many smart grid

projects (pilots as well as full-scaleimplementation) could benefit by findingadditional improvements from enhancedmonitoring of key performance indicators,further emphasizing the need for fair andobjective metrics. Metrics suitable forthe smart grid are measurements of keyparameters linked to design, installation,planning, operation, maintenance orcustomer outreach aspects of the smartgrid transition. While the research forthis survey not does reflect the completepicture on smart grid metrics, it does

establish some foundational informationneeded for developing a framework fordefining them.

The metrics used for this survey werepartly based on those identified by theU.S. Department of Energy (DOE) smartgrid workshops1 and documents on smartgrid success factors. Other metrics wereintroduced by Accenture to contrastregional situations, trending characteristicsor other traits of the metrics.

Using DOEs terminology, the metrics canbe categorized as build and impact.A subset of the impact metrics can beidentified to as value metrics.

Build metrics

Build metrics measure progress duringthe implementation of smart grid assets.A number of build metrics were identifiedduring the DOE Smart Grid MetricsWorkshop, held June 19-20, 2008.2These metrics are aimed at monitoring

progress in building out the smart grid.Build metrics are tailored to individualutilities and their expected benefitsfrom the smart grid. Metrics couldinclude the number of smart metersinstalled, substations automated anddynamic pricing programs offered.

Build metrics are best detected in acumulative manner when possible, withbaseline data identified. A number ofbuild metrics were used in this survey.

Impact metrics

Impact metrics measure the impact,change or response of the grid and allits associated assets (including systems,

equipment and human resources) aswell as the impact on customers as aconsequence of the deployed smart gridsystems. Impact metrics measure how andto what extent a smart grid is affectinggrid operations and performance, orhow it is enabling customer programsand behavior changes. Some examplesof impact metrics include: peak demandreductions, tons of GHG reduced,maintenance cost avoided and number ofoutage minutes per year in a given area.

Recommendations

As metrics in general rely on data fromvarious sources, it will be increasinglycritical to understand all data sourceswithin the company, while also utilizingtools to build metrics from multiple datasources. For example, equipment data istypically stored in an asset managementsystem and the performance of thisequipment might be an output of thesupervisory control and data acquisition(SCADA) system. Linking these datasources could possibly provide significantvalue for a utility, as such linkage givesan excellent source of performancecomparison of various assets.

Some level of detail should be providedto describe the basis of the metric. Thiswould require describing what smartgrid assets, integration activities andsmart grid functionalities have beenassumed. System-level metrics shouldinclude the number of new smart

grid assets as well as assets alreadyinstalled on the system. For example,if a project installed 100 automatedfeeder switches and there were already300 automated feeder switches installedon the distribution system prior to thesmart grid program, both should beidentified in the metric description.

It would be beneficial for utilities toestablish teams dedicated to metricsand performance measurementit couldprevent and overcome the silo thinking ofsome utilities experience. Only if multipleparties and departments are part ofperformance metrics would utilities fullybenefit and learn from metric application.

Finally, barriers related to the transitionto smart grids exist. These include:

Lack of clear frameworks and roadmaps.

New stakeholders and theirdifferent views and needs.

Technical barriers in development androllout of equipment and systems.

Different stakeholder viewson monitoring and controllingthe smart grid processes.

Dependencies between informationin different layers, and issues such as:

- Higher layers for business applications- Lower layers for technical infrastructure

While this survey did not collectresponses related to such challenges,identifying and tracking such challengesin a structured approach is essentialfor adeptly managing and ultimatelyovercoming them to pave the road for

a smooth smart grid transformation.

Effective applications ofmetrics for performancemonitoring of the smartgrid depend on the choiceof the correct parameters,the continuous monitoringof those parameters andan understanding of theassociated targets or goals.

Nicholas Abi-Samra, senior manager,

Accenture Smart Grid Services

1Smart Grid, U.S. Department of Energy, Office of Electricity Delivery and Energy Reliability, http://energy.gov.2Metrics for Measuring Progress toward Implementation of the Smart Grid, Results of the Breakout Session Discussions at the Smart Grid ImplementationWorkshop, U.S. Department of Energy, Office of Electricity Delivery and Energy Reliability, June 19-20, 2008, Washington, DC, http://energy.gov.


25/28

Summary of metrics objectives:

Assess smart grid projectsagainst vision and roadmap

objectives Provide data to assist inmonitoring and reporting onthe effective use of smartgrid funding

Support the process forachieving stakeholder buy-in

Keep smart gridprojects on track andprovide a means toproject future progress

25

Smart grid metrics help with:

Establishment of baselinefor target setting

Identification of successesand opportunities for

improvement

Initiation of correctiveaction to address problemsidentified by trends

Alignment amongstakeholders

Benefits valuationand realization


26/28

26

There is no single version of a smart grid.Therefore, the drivers for implementation

and the success factors of deploymentvary widely and are largely dependent ongovernment policies and technical needs.

Utilities around the globe are investingsignificant resources in the deploymentof smart grid technologies. Successfulutilities will not be those that investthe most, but those that invest mosteffectively in smart grid technologies,while at the same time reaping themultiple benefits that arise from modernsmart grids.

The fact f inding and decision makingregarding which technology to applyand which is most beneficial to a utilityrelies on the deployment of standardized,multidiscipline, multisource metrics thatmeasure the impact of the installedtechnology in terms of improvement toend customers, the utility and society asa whole.

Selection of specific smart grid metricsshould be performed carefully, as

the monitoring and communicationof metric results will influence thebehavior of stakeholder groups overtime and the direction and speedof the smart grid evolution.

Conclusion


27/28

27


28/28

Copyright 2012 AccentureAll rights reserved.

About AccentureAccenture is a global managementconsulting, technology services andoutsourcing company, with more than244,000 people serving clients in morethan 120 countries. Combining unparalleledexperience, comprehensive capabilitiesacross all industries and business functions,and extensive research on the worlds

most successful companies, Accenturecollaborates with clients to help thembecome high-performance businesses andgovernments. The company generated netrevenues of US$25.5 billion for the fiscalyear ended Aug. 31, 2011. Its home page iswww.accenture.com.

About the Accenture Utilitiesindustry groupThe Accenture Utilities industry group has

more than 30 years of experience workingwith electric, gas and water utilitiesworldwide. Our group works with morethan 200 utilities in over 30 countriesand has 10,000 people supporting ourutilities clients. We work with 80 percentof businesses with utilities in their portfolioon the 2011 Global Fortune500 list. TheAccenture Utilities industry group bringsdeep industry knowledge, world-classcapabilities, leading-edge technology andinnovation to our clients to help them raisetheir performance to new heights.

Accenture Unlocking Value Metrics

Documents

Transcript of Accenture Unlocking Value Metrics