1. Presented to the PWG Meeting of May 26, 2010
ERCOT Load Research Sampling Round 2 Comparison of Sample Means to Profile Models
Presented to the PWG Meeting
of May 26, 2010

2. Overview Background Information Energy Comparison
Comparisons of Scaled LRS Means vs backcasts – Interval data and daily average profiles
Summary Statistics by Profile Type and Weather Zone
Summary

3. Background Information
Analysis period 07/01/2008 – 12/31/2009
18 month period to maximize interval data availability due to Hurricane Ike
Ike exclusion: Sept 11, 2008 – Oct 31, 2008
Analysis: one calendar month per run
Ratio estimation used in this analysis
Auxiliary variable is calendarized kWh for the month
kWh
Interval
for
Estimate
Sample Y =
Calendarized
Mean
Population X
strata l of
out
Weight i
Stratum w y x

4. Background Information
An ESI ID is included in the analysis (both for the sample and population) for a month if:
Status is Active or De-energized at the time of the study and Status is Active the entire study month
At least 90% of the interval data was available
Calendarized kWh available covering the whole month
Treatment of Profile ID migrations
Eliminated from sample and population
RES → BUS, NM
BUS → RES, NM, BUSIDRRQ
WZone or Voltage changes
New ESI IDs since sample selection

5. Background Information
Sample and population stratification for analysis based on a combination of original stratum and current Profile ID

6. Background Information
Migrations due to annual validation were modeled in the Round 2 analysis.
Premises with advanced meters were removed from the population at the time of analysis (~400,000.)

7. Background Information
Two or more sample points are required per stratum.
Required for sample precision calculation
Exception: 1 ESI ID in sample and population for the stratum
Stratum eliminated if insufficient sample points to perform the calculations
All other strata included in analysis.
Mean Absolute Percent Error (MAPE) was calculated for each interval:
MAPE = ABS(backcast-LRS_Mean)/LRS_Mean * 100

8. Background Information
Precision is a measure of the variability of the sample estimate about the sample mean
Precision for each Profile Type and Weather Zone combination was impacted by:
sample sizes based on estimated Error Ratios and varying levels of accuracy depending upon the load in the cell
the number of recorders actually installed
sample points with a minimum of 90 percent data were used in the calculations
sample point migration into and out of the strata
advanced meters were removed from the population at the time of analysis.

9. Background Information
Profile Scaling
The Round 2 estimates of the Mean were scaled so that their monthly energy equals the backcast energy.
The scaled profiles provide a good indication of the allocation of energy across the day and month.

10. The following slides include:
Results
The following slides include:
Comparison of monthly energy (kWh) differences
Profile comparisons of scaled Round 2 Means vs backcast profiles for selected weeks in the analysis period
Comparisons of scaled Round 2 Means vs backcast profiles for daily average profiles across the analysis period
Summaries of Mean Absolute Percent Error (MAPE) between the Round 2 Means and the backcasts for both scaled and un-scaled Round 2 Means.
Summary of Precision by Profile Type and Weather Zone
Summary of Sample Sizes by Profile Type and Weather Zone.

11. LRS Means vs Backcast Energy Comparison
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

12. LRS Means vs Backcast Energy Comparison
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

13. LRS Means vs Backcast Energy Comparison
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

14. LRS Means vs Backcast Energy Comparison
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

15. LRS Means vs Backcast Energy Comparison
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

16. LRS Means vs Backcast Energy Comparison
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

17. Profile Comparisons
A PowerPoint file has been prepared for each profile type containing scaled LRS Means vs backcast comparisons for each profile type/weather zone combination
These files are appendices to this presentation and are posted as key documents
Two weeks containing peaks were selected:
July (2009 summer peak is on 7/13)
December (2009 winter peak is on 12/10)
Three weather zones with the highest load were selected
Coast, North Central, South Central
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

18. Profile Comparisons Week of JULY 13-19 2009
2009 Summer Peak occurred on July 13
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

19. BUSHILF COAST
Week of July

20. BUSHILF NCENT
Week of July

21. BUSHILF SCENT
Week of July

22. BUSMEDLF COAST
Week of July

23. BUSMEDLF NCENT
Week of July

24. BUSMEDLF SCENT
Week of July

25. BUSLOLF COAST
Week of July

26. BUSLOLF NCENT
Week of July

27. BUSLOLF SCENT
Week of July

28. BUSNODEM COAST
Week of July

29. BUSNODEM NCENT
Week of July

30. BUSNODEM SCENT
Week of July

31. RESHIWR COAST
Week of July

32. RESHIWR NCENT
Week of July

33. RESHIWR SCENT
Week of July

34. RESLOWR COAST
Week of July

35. RESLOWR NCENT
Week of July

36. RESLOWR SCENT
Week of July

37. Profile Comparisons Week of December 7-13 2009
2009 Winter Peak occurred on December 10
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

38. BUSHILF COAST
Week of December

39. BUSHILF NCENT
Week of December

40. BUSHILF SCENT
Week of December

41. BUSMEDLF COAST
Week of December

42. BUSMEDLF NCENT
Week of December

43. BUSMEDLF SCENT
Week of December

44. BUSLOLF COAST
Week of December

45. BUSLOLF NCENT
Week of December

46. BUSLOLF SCENT
Week of December

47. BUSNODEM COAST
Week of December

48. BUSNODEM NCENT
Week of December

49. BUSNODEM SCENT
Week of December

50. RESHIWR COAST
Week of December

51. RESHIWR NCENT
Week of December

52. RESHIWR SCENT
Week of December

53. RESLOWR COAST
Week of December

54. RESLOWR NCENT
Week of December

55. RESLOWR SCENT
Week of December

56. Average Day Across the Study Period
BUSMEDLF COAST
Average Day Across the Study Period

57. Average Day Across the Study Period
BUSMEDLF FWEST
Average Day Across the Study Period

58. Average Day Across the Study Period
BUSLOLF COAST
Average Day Across the Study Period

59. Average Day Across the Study Period
BUSLOLF NCENT
Average Day Across the Study Period

60. Average Day Across the Study Period
RESHIWR COAST
Average Day Across the Study Period

61. Average Day Across the Study Period
RESHIWR NCENT
Average Day Across the Study Period

62. Average Day Across the Study Period
RESLOWR COAST
Average Day Across the Study Period

63. Average Day Across the Study Period
RESLOWR NCENT
Average Day Across the Study Period

64. Summary
The current models, based on Round 1 data in , are “best fit” regressions on the Round 1 estimated means.
Round 2 is a “full sample” with sample sizes based on estimated Error Ratios and targeted ±15% accuracy at 90% confidence. (Round 1 was a “half sample”.)
Ratio estimation analysis was used to calculate the Round 2 means.
How well do the Round 1 models estimate the Round 2 means?
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

65. Summary by Profile Type and WZone

66. Summary by Profile Type and WZone

67. Summary
MAPE’s using scaled Round 2 Means by Profile Type and Weather Zone range between 2.8 % (BUSHILF, NCENT) and 27.9% (BUSNODEM, COAST) with the mean for all profile types and weather zones = 8.5%.
Mean MAPE’s using un-scaled Round 2 Means by Profile Type and Weather Zone range between 6.2 % (BUSNODEM, NCENT) and 36.7% (BUSHILF, EAST) with the mean for all profile types and weather zones = 14.1%.
Mean Precisions by Profile Type and Weather Zone range between 2.7 % (BUSHILF, SCENT) and 20.3% (BUSNODEM, SOUTH) with the Mean Precision for all profile types and weather zones = 9.8%.
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

68. Summary
Reasons the current models do not do a better job of estimating the Round 2 means.
The population has changed in the 3 years since the Round 1 models were developed.
Because Round 1 was a “half sample”, there were cells in the Round 1 analysis that had the minimum number of sample points required to do the analysis thereby lowering the accuracy of the estimate.
The minimum sample size in the Round 2 sample is 88 points in the BUSNODEM/SOUTH cell.
See example on this slide –
Graph 1: Pick days that are exceptionally different comparing kWh for profile to sample data.
Graph 2: Same as above but presenting interval % of kWh

69. Questions for Discussion