Settlement Accuracy Analysis Prepared by ERCOT Load Profiling

Settlement Accuracy Analysis

Prepared by ERCOT Load Profiling

Introduction and Methodology

3

Settlement Accuracy Analysis Advanced metering can be used to enable 15-minute

interval settlement for all ESIIDs.

Alternatively, advanced metering can be used to: Enable 15-minute interval settlement for some ESIIDs, and Improve the accuracy of load profiling and settlement for all

other ESIIDs

The intent of this presentation is to address the use of advanced meters to improve load profiling by: Increasing the frequency of meter readings Creating the feasibility for larger more frequently updated

load research samples Facilitating the introduction of new load profiles Enabling dynamic (true/lagged) profiling

4

Meter Reading Frequency Currently monthly meter reads are used in settlement and

are profiled using adjusted static models Load profile models are structured in 3 stages

Stage 1: Monthly kWh - Daily kWh Stage 2: Daily kWh - Hourly kWh Stage 3: Hourly kWh – 15-minute interval kWh

Increasing the meter reading frequency can eliminate one or more stages from the profile model and the estimation error associated with the stages

Universal TOU meter reading (independent of pricing) could leverage the “chunking” functionality already existing in ERCOT systems to further reduce profiling error TOU meter readings would individualize the profile shape to capture

systematic difference in usage patterns across customers

5

ERCOT utilized the interval data from the Load Research Sample customers to investigate the profiling error impact associated with the levels of meter reading frequency.

ERCOT’s round 1 load research sample was approximately one-half the size anticipated to be needed

The models developed from the load research data are not as accurate as would be estimated from larger samples

Meter Reading Frequency

COAST EAST FWEST NCENT NORTH SCENT SOUTH WEST TotalBUSHILF 45 32 48 42 42 24 42 39 314

BUSMEDLF 88 105 119 146 99 149 102 90 898BUSLOLF 115 109 173 125 121 94 121 120 978

BUSNODEM 121 93 138 145 115 93 115 87 907RESLOWR 69 69 69 69 69 69 69 69 552RESHIWR 48 48 48 48 48 48 51 48 387

Total 486 456 595 575 494 477 500 453 4036

Number of Sample Points in LRS Round 1

6

ERCOT utilized the interval data from the Load Research Sample customers to investigate the impact of several levels of meter reading frequency on profiling error.

Analysis window: July 2005 - June 2006 The meter reading frequency levels analyzed are listed

below:

Time Period Approx. # of Reads per monthMonthly (calendar month) 1 TOU Monthly 8Daily 28TOU Daily 120Hourly 720


7

Interval data for each of the sample customers was summed over the appropriate time periods to determine non-IDR meter readings for the various reading frequency levels

The non-IDR meter readings were then profiled following the currently established process

The actual interval values and the profiled versions of those intervals were then extrapolated to the profile class level using standard load research statistical methodology

The difference between the actual and profiled class level estimates is a measure of the amount of profiling error (at the class level) associated with the various meter reading frequency levels


8

Meter Reading Frequency For this analysis, profile specific TOU schedules were

created to isolate periods with significant variation in load shape and high volume of consumption

TimePeriod Start Stop Start Stop Start Stop Start Stop Start Stop Start Stop

4 0:01 4:30 0:01 5:00 0:01 5:00 0:01 7:00 0:01 5:00 0:01 5:003 4:31 9:30 5:01 11:00 5:01 9:00 7:01 13:00 5:01 10:00 5:01 10:002 9:31 16:00 11:01 22:30 9:01 15:00 13:01 20:30 10:01 17:30 10:01 17:301 16:01 22:30 15:01 20:30 17:31 23:00 17:31 23:004 22:31 0:00 22:31 0:00 20:31 0:00 20:31 0:00 23:01 0:00 23:01 0:00

TimePeriod Start Stop Start Stop Start Stop Start Stop Start Stop Start Stop

4 0:01 5:30 0:01 5:30 0:01 5:15 0:01 5:00 0:01 4:30 0:01 4:303 5:31 8:30 5:31 8:30 5:16 8:30 5:01 8:45 4:31 8:15 4:31 8:302 8:31 12:15 8:31 12:15 8:31 10:45 8:46 11:00 8:16 17:00 8:31 16:301 12:16 22:00 12:16 22:00 10:46 22:30 11:01 22:30 17:01 22:00 16:31 22:004 22:01 0:00 22:01 0:00 22:31 0:00 22:31 0:00 22:01 0:00 22:01 0:00

Winter = 1/1 - 3/14 & 11/16 - 12/31Shoulder = 3/15 - 5/10 & 9/21 - 11/15Summer = 5/11 - 9/20

TOU Schedule Created for Use on RESHIWRShoulder = 1 Summer = 2 Winter = 3

Weekday =1 Weekend =2 Weekday =1 Weekend =2 Weekday =1 Weekend =2

TOU Schedule Created for Use on BUSHILFShoulder = 1 Summer = 2 Winter = 3

Weekday =1 Weekend =2 Weekday =1 Weekend =2 Weekday =1 Weekend =2

9

Example of Actual vs Profiled – Monthly Reads

BUSMEDLF – COAST - July 14, 2005

2

3

4

5

6

7

8

9

10

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

15 Min Interval Means Profiled w/ Monthly Usage15 Min Interval Means Profiled w/ 15 Min Interval Means Profiled w/ Monthly Usage15 Min Interval Means Profiled w/

10

Example of Actual vs Profiled – Monthly TOU Reads


2

3

4

5

6

7

8

9

10

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

15 Min Interval Means15 Min Interval Means Profiled w/ Monthly Usage Adjusted for 4 TOU Periods15 Min Interval Means15 Min Interval Means Profiled w/ Monthly Usage Adjusted for 4 TOU Periods

11

Example of Actual vs Profiled – Daily Reads BUSMEDLF – COAST - July 14, 2005

2

3

4

5

6

7

8

9

10

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

15 Min Interval Means Profiled w/ Daily Usage15 Min Interval Means Profiled w/ Daily Usage

12

Example of Actual vs Profiled – Daily TOU Reads


2

3

4

5

6

7

8

9

10

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

15 Min Interval Means Profiled w/ Daily Usage Adjusted for 4 TOU Periods15 Min Interval Means Profiled w/ Daily Usage Adjusted for 4 TOU Periods

13

Example of Actual vs Profiled – Hourly Reads


2

3

4

5

6

7

8

9

10

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

15 Min Interval Means Profiled w/ Hourly Usage15 Min Interval Means Profiled w/ Hourly Usage

Summary Reports - kWh

15

HOURLY READS

TOU DAILY READS

DAILY READS

TOU MONTHLY

READS

MONTHLY READS

BUSHILF -0.0000208 -0.0000228 -0.0000358 -0.0000087 -0.0000167

BUSLOLF -0.0000013 -0.0000006 -0.0000003 0.0002228 0.0000171

BUSMEDLF -0.0000031 -0.0000044 -0.0000030 0.0000489 0.0000347

BUSNODEM 0.0000001 0.0000044 0.0007965 0.0018303 0.0003466

RESHIWR -0.0000008 -0.0000018 0.0000231 -0.0000090 -0.0000029

RESLOWR -0.0007138 -0.0007140 -0.0004652 -0.0006877 -0.0007136

Study Period: J uly 2005 Thru J une 2006ERCOT-Wide

BASELINE is the LRS Mean kWh intervals.

PROFILE TYPE

Annual Average Interval kWh Difference

Profile – Actual

•Profiling spreads kWh from meter readings across intervals but does not change the total kWh use.

•Consequently, the average difference between actual and profiled kWh is zero; differences shown above are attributable to rounding.

16

Annual Average Interval Percent Difference

Profile – Actual

•Increased meter reading frequency results in improved annual average percent differences.

Across all profile types Busnodem improves the most – 1.38 % improvement from monthly to hourly reads

Residential profile types improve by 1.12% from monthly to hourly reads

•All percent differences are positive – overestimation of low load intervals underestimation of high load intervals

HOURLY READS

TOU DAILY READS

DAILY READS

TOU MONTHLY

READS

MONTHLY READS

BUSHILF 0.0141 0.0404 0.0597 0.1171 0.1176

BUSLOLF 0.1049 0.3660 0.6621 1.0847 1.1702

BUSMEDLF 0.0271 0.0982 0.1614 0.3345 0.3389

BUSNODEM 0.3868 0.8102 1.7330 3.0539 1.7705

RESHIWR 0.5612 1.1138 1.5182 1.6245 1.6809

RESLOWR 0.2925 0.8351 1.2376 1.4213 1.4163



PROFILE TYPE

17

Meter Reading Frequency All percent differences are positive – overestimation of low load intervals underestimation of high load intervals

An inherent limitation of adjusted static models because the estimation of model coefficients is driven by the preponderance of medium load intervals

The load profiling process allocates kWh from meter readings across all intervals in the period; overestimated intervals must be offset by underestimated intervals

The following slides illustrate the over/under

estimation for selected profile models

18

Average Day Across the Study Period RESHIWR - COAST

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

2.1

2.2

12AM 03AM 06AM 09AM 12PM 03PM 06PM 09PM 12AM

kW

Interv al Ending

15 Min LRS Means Settlement w/ Monthly Usage15 Min LRS Means Settlement w/ Monthly Usage

underestimating

overestimating

19

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

2.1

2.2

2.3

2.4


kW

Interv al Ending


Average Day Across the Study Period RESHIWR - NCENT

underestimating

overestimating

20

Average Day Across the Study Period BUSMEDLF - COAST

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33


kW

Interv al Ending


underestimating

overestimating

21

Average Day Across the Study Period BUSMEDLF - NCENT

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34


kW

Interv al Ending


underestimating

overestimating

22

Frequency Distribution LRS Means vs Settlement Type

NET - BUSMEDLF

0

5

10

15

20

25

30

35

-10 - -8 -8 - -6 -6 - -5 -5 - -4 -4 - -3 -3 - -2 -2 - -1 -1 - 0 0 - 1 1 - 2 2 - 3 3 - 4 4 - 5 5 - 6 6 - 8 8 - 10

Percent NET Difference

Per

cen

t o

f In

terv

als

Hourly

TOU Daily

Daily

TOU Monthly

Monthly

Distribution of Interval Percent Differences BUSMEDLF

Percent Difference (Profile – Actual)

Increasing meter reading frequency results in tighter distribution of differences

23

Frequency Distribution LRS Means vs Settlement Type

NET - RESHIWR

0

5

10

15

20

25

30

35

-25 - -20 -20 - -15 -15 - -10 -10 - -5 -5 - 0 0 - 5 5 - 10 10 - 15 15 - 20 20 - 25 25 - 30 30 - 35

Percent NET Difference

Per

cen

t o

f In

terv

als

Hourly

TOU Daily

Daily

TOU Monthly

Monthly

Percent Difference (Profile – Actual)

Distribution of Interval Percent Differences

RESHIWRIncreasing meter reading frequency results in tighter distribution of differences

Summary Reports - Dollars

25

HOURLY READS

TOU DAILY READS

DAILY READS

TOU MONTHLY

READS

MONTHLY READS

BUSHILF 0.882 1.508 1.872 2.475 2.508

BUSLOLF 2.356 4.451 5.864 7.613 7.723

BUSMEDLF 1.172 2.181 2.890 3.878 3.933

BUSNODEM 4.160 6.305 8.257 10.179 9.114

RESHIWR 5.643 8.105 9.407 10.372 10.458

RESLOWR 5.182 7.662 8.829 9.813 9.864



PROFILE TYPE

Annual Average Absolute Interval Percent Difference

Profile – Actual

•Increased meter reading frequency results in improved annual average absolute interval percent differences.

Buslolf, Busnodem, Reshiwr, and Reslowr all improve by about 5 % going from monthly to hourly reads

Bushilf and Busmedlf improve by 1.6% and 2.8% respectively

26

PROFILE GROUP

% MWh * MCPE

HOURLY READS

TOU DAILY READS

DAILY READS

TOU MONTHLY

READS

MONTHLY READS

BUSHILF 9.8% -8.82 -67.24 -143.48 -238.41 -250.41

BUSMEDLF 12.4% -1.44 -23.39 -45.61 -97.49 -116.04

BUSLOLF 16.3% -8.41 -44.39 -99.64 -179.41 -194.44

BUSNODEM 1.6% -1.46 -2.85 5.86 26.00 -4.67

RESHIWR 26.3% -1.43 -12.25 -29.20 -23.04 -26.80

RESLOWR 33.4% -0.92 -10.32 -14.32 -15.13 -15.68

Annual Total Dollar Difference Profile – Actual

Annual Dollars = ∑i kWhi * MCPEi

•Annual total dollar differences are relatively small even with monthly reads

•The differences range from $0.39 for Busnodem up to $21 for Bushilf per month

•Residential profiles account for ~ 60% of annual dollars and have a difference of about $1.70 per month

•Increased meter reading frequency results in lower annual total dollar differences.

•In general dollar differences are negative

•Overestimation of low load intervals and underestimation of high load intervals

•Positive correlation between load and MCPE

27

Average Day Across the Study Period

RESHIWR - COAST

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4


kW

Interv al Ending

0.0

0.1

0.2

0.3

0.4

$/hr

15 Min LRS Dollar Means Profiled Dollars w/ Monthly Usage

15 Min LRS kWh Means Profiled kWh w/ Monthly Usage

28


RESHIWR - NCENT

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6


kW

Interv al Ending

0.0

0.1

0.2

0.3

0.4

$/hr



29


BUSMEDLF - COAST

0

10

20

30

40


kW

Interv al Ending

0

1

2

3

4

5

$/hr



30

Average Day Across the Study Period BUSMEDLF - NCENT

0

10

20

30

40


kW

Interv al Ending

0

1

2

3

4

5

$/hr



Selected Weekly Profiles BUSMEDLF_NCENTRESHIWR_NCENT

32

15 Min LRS Means Settlement w/ Hourly Usage Settlement w/ Daily Usage

Settlement w/ Monthly UsageSettlement w/ TOU Daily Usage Settlement w/ TOU Monthly Usage



Summer Week – August 15-21, 2005 BUSMEDLF - NCENT

4

5

6

7

8

9

10

11

12

Mon 15 Tue 16 Wed 17 Thu 18 Fri 19 Sat 20 Sun 21 Mon 22

kWh

Time

33





Summer Weekday – Thursday, August 18, 2005 BUSMEDLF - NCENT

5

6

7

8

9

10

11

12

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

34





Summer Weekend – August 20-21, 2005 BUSMEDLF - NCENT

5

6

7

8

9

10

Sat 01:00 Sat 13:00 Sun 01:00 Sun 13:00

kWh

Time

35





Fall Week – October 17-23, 2005 BUSMEDLF - NCENT

4

5

6

7

8

9

10

11


kWh

Time

36





Fall Weekday – Friday, October 21, 2005 BUSMEDLF - NCENT

4

5

6

7

8

9

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

37





Fall Weekend – October 22-23, 2005 BUSMEDLF - NCENT

4

5

6

7

Sat 01:00 Sat 13:00 Sun 01:00 Sun 13:00

kWh

Time

38





Winter Week – February 13-19, 2006 BUSMEDLF - NCENT

4

5

6

7

8


kWh

Time

39





Winter Weekday – Friday, February 17, 2006 BUSMEDLF - NCENT

4

5

6

7

00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00

kWh

Time

40





Winter Weekend – February 18-19, 2006 BUSMEDLF - NCENT

4

5

6

7

Sat 00:00 Sat 12:00 Sun 00:00 Sun 12:00 Mon 00:00

kWh

Time

41





Spring Week – March 27 - April 2, 2006 BUSMEDLF - NCENT

4

5

6

7

8

9


kWh

Time

42





Spring Weekday – Tuesday, March 28, 2006 BUSMEDLF - NCENT

4

5

6

7

8

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

43





Spring Weekend – April 1-2, 2006 BUSMEDLF - NCENT

4

5

6

7

Sat 01:00 Sat 13:00 Sun 01:00 Sun 13:00

kWh

Time

44





Summer Week – August 15-21, 2005 RESHIWR - NCENT

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0


kWh

Time

45





Summer Weekday – Monday, August 15, 2005 RESHIWR - NCENT

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

46





Summer Weekend – August 20-21, 2005 RESHIWR - NCENT

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

Sat 01:00 Sat 13:00 Sun 01:00 Sun 13:00

kWh

Time

47





Fall Week – October 17-23, 2005 RESHIWR - NCENT

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8


kWh

Time

48





Fall Weekdays – Thursday-Friday, October 20-21, 2005 RESHIWR - NCENT

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Thu 01:00 Thu 13:00 Fri 01:00 Fri 13:00

kWh

Time

49





Fall Weekend – October 22-23, 2005 RESHIWR - NCENT

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Sat 01:00 Sat 13:00 Sun 01:00 Sun 13:00

kWh

Time

50





Winter Week – February 13-19, 2006 RESHIWR - NCENT

0.0

1.0


kWh

Time

51





Winter Weekdays – Thursday-Friday, February 16-17, 2006 RESHIWR - NCENT

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Thu 00:00 Thu 12:00 Fri 00:00 Fri 12:00 Sat 00:00

kWh

Time

52





Winter Weekend – February 18-19, 2006 RESHIWR - NCENT

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

Sat 00:00 Sat 12:00 Sun 00:00 Sun 12:00 Mon 00:00

kWh

Time

53





Spring Week – March 27 - April 2, 2006 RESHIWR - NCENT

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7


kWh

Time

54





Spring Weekday – Tuesday, March 28, 2006 RESHIWR - NCENT

0.0

0.1

0.2

0.3

0.4

0.5

0.6

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

55





Spring Weekend – April 1-2, 2006 RESHIWR - NCENT

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Sat 01:00 Sat 13:00 Sun 01:00 Sun 13:00

kWh

Time

Extreme Events - kWh

57





Hurricane Rita – September 21-23, 2005 BUSHILF - COAST

9

10

11

12

13

14

15

16

17

18

Wed 21 Thu 22 Fri 23 Sat 24

kWh

Time

58





Hurricane Rita – September 21-23, 2005 BUSMEDLF - COAST

2

3

4

5

6

7

8

9

10


kWh

Time

59





Hurricane Rita – September 21-23, 2005 BUSLOLF - COAST

1

2

3

4

5


kWh

Time

60





Hurricane Rita – September 21-23, 2005 BUSNODEM - COAST

0.0

0.1

0.2

0.3


kWh

Time

61





Hurricane Rita – September 21-23, 2005 RESHIWR - COAST

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1


kWh

Time

62





Hurricane Rita – September 21-23, 2005 RESLOWR - COAST

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2


kWh

Time

63





10

11

12

13

14

15

16

17

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

Extreme Temperature Event – April 17, 2006 BUSHILF - COAST

64





Extreme Temperature Event – April 17, 2006 BUSHILF - NCENT

14

15

16

17

18

19

20

21

22

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

65





Extreme Temperature Event – April 17, 2006 BUSMEDLF - COAST

2

3

4

5

6

7

8

9

10

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

66





Extreme Temperature Event – April 17, 2006 BUSMEDLF - NCENT

4

5

6

7

8

9

10

11

12

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

67





Extreme Temperature Event – April 17, 2006 RESHIWR - COAST

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

68





Extreme Temperature Event – April 17, 2006 RESHIWR - NCENT

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

01:00 04:00 07:00 10:00 13:00 16:00 19:00 22:00

kWh

Time

69

Summary and ConclusionsFor large aggregations of customers:

Profiling provides a good estimate of load even with monthly meter reads

Annual total dollar differences are relatively small with monthly reads

Hourly and daily meter reads improves profile estimates, especially during unusual or extreme weather events.

Settlement with 15-minute interval load data provides marginal improvement over what could be achieved using profiling with hourly or daily meter reads.

70

Summary and ConclusionsOpportunities for Profiling Improvement using advanced metering capabilities:

Significantly larger and more frequently updated load research samples are viable considerations

Introduction of new load profiles become faster and less costly

Dynamic (true/lagged) profiling would be facilitated To replace adjusted static models for standard profiles

Demand Response Programs

New profiles

Documents

Settlement Accuracy Analysis Prepared by ERCOT Load Profiling