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Settlement Accuracy Analysis

Settlement Accuracy Analysis. Prepared by ERCOT Load Profiling. Introduction and Methodology. Settlement Accuracy Analysis. Advanced metering can be used to enable 15-minute interval settlement for all ESIIDs. Alternatively, advanced metering can be used to:

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Settlement Accuracy Analysis

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  1. Settlement Accuracy Analysis Prepared by ERCOT Load Profiling

  2. 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. Meter Reading Frequency • 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

  6. Meter Reading Frequency • 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 PeriodApprox. # of Reads per month Monthly (calendar month) 1 TOU Monthly 8 Daily 28 TOU Daily 120 Hourly 720

  7. Meter Reading Frequency • 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

  9. Example of Actual vs Profiled – Monthly ReadsBUSMEDLF – COAST - July 14, 2005

  10. Example of Actual vs Profiled – Monthly TOU ReadsBUSMEDLF – COAST - July 14, 2005

  11. Example ofActual vs Profiled – Daily Reads BUSMEDLF – COAST - July 14, 2005

  12. Example of Actual vs Profiled – Daily TOU ReadsBUSMEDLF – COAST - July 14, 2005

  13. Example ofActual vs Profiled – Hourly Reads BUSMEDLF – COAST - July 14, 2005

  14. Summary Reports - kWh

  15. 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

  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 underestimating overestimating

  19. Average Day Across the Study Period RESHIWR - NCENT underestimating overestimating

  20. Average Day Across the Study PeriodBUSMEDLF - COAST underestimating overestimating

  21. Average Day Across the Study Period BUSMEDLF - NCENT underestimating overestimating

  22. Distribution of Interval Percent Differences BUSMEDLF Increasing meter reading frequency results in tighter distribution of differences Percent Difference (Profile – Actual)

  23. Distribution of Interval Percent Differences RESHIWR Increasing meter reading frequency results in tighter distribution of differences Percent Difference (Profile – Actual)

  24. Summary Reports - Dollars

  25. 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. 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 PeriodRESHIWR - COAST

  28. Average Day Across the Study PeriodRESHIWR - NCENT

  29. Average Day Across the Study PeriodBUSMEDLF - COAST

  30. Average Day Across the Study Period BUSMEDLF - NCENT

  31. Selected Weekly Profiles BUSMEDLF_NCENTRESHIWR_NCENT

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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