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

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

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

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

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

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.)

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

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.

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.

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.

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

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

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

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

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

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

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 13-19 2009 (2009 summer peak is on 7/13) December 7-13 2009 (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

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

BUSHILF COAST Week of July 13-19 2009

BUSHILF NCENT Week of July 13-19 2009

BUSHILF SCENT Week of July 13-19 2009

BUSMEDLF COAST Week of July 13-19 2009

BUSMEDLF NCENT Week of July 13-19 2009

BUSMEDLF SCENT Week of July 13-19 2009

BUSLOLF COAST Week of July 13-19 2009

BUSLOLF NCENT Week of July 13-19 2009

BUSLOLF SCENT Week of July 13-19 2009

BUSNODEM COAST Week of July 13-19 2009

BUSNODEM NCENT Week of July 13-19 2009

BUSNODEM SCENT Week of July 13-19 2009

RESHIWR COAST Week of July 13-19 2009

RESHIWR NCENT Week of July 13-19 2009

RESHIWR SCENT Week of July 13-19 2009

RESLOWR COAST Week of July 13-19 2009

RESLOWR NCENT Week of July 13-19 2009

RESLOWR SCENT Week of July 13-19 2009

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

BUSHILF COAST Week of December 7-13 2009

BUSHILF NCENT Week of December 7-13 2009

BUSHILF SCENT Week of December 7-13 2009

BUSMEDLF COAST Week of December 7-13 2009

BUSMEDLF NCENT Week of December 7-13 2009

BUSMEDLF SCENT Week of December 7-13 2009

BUSLOLF COAST Week of December 7-13 2009

BUSLOLF NCENT Week of December 7-13 2009

BUSLOLF SCENT Week of December 7-13 2009

BUSNODEM COAST Week of December 7-13 2009

BUSNODEM NCENT Week of December 7-13 2009

BUSNODEM SCENT Week of December 7-13 2009

RESHIWR COAST Week of December 7-13 2009

RESHIWR NCENT Week of December 7-13 2009

RESHIWR SCENT Week of December 7-13 2009

RESLOWR COAST Week of December 7-13 2009

RESLOWR NCENT Week of December 7-13 2009

RESLOWR SCENT Week of December 7-13 2009

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

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

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

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

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

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

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

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

Summary The current models, based on Round 1 data in 2004-2006, 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

Summary by Profile Type and WZone

Summary by Profile Type and WZone

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

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

Questions for Discussion