Discussion of Load Forecast Uncertainty

Transcription

1 Discussion of Load Forecast Uncertainty August 26, 2010 Load Forecasting Task Force Draft for discussion only Arthur Maniaci System & Resource Planning New York Independent System Operator

2 Summary of Discussion The New York State Reliability Council (NYSRC) determines the Installed Reserve Margin (IRM) and the Locality Requirements each year. IRM the generating capacity required to ensure reliability (loss of load due to forced outage of 1 day in 10 years), as a percent of the NYCA peak load forecast for a given year. Locality Requirement the amount of generating capacity to be located within a specific region to ensure reliability, as a percent of the locality s peak load forecast for a given year. Installed Capacity Subcommittee prepares a new study each year The Load Forecasting Task Force prepares the Installed Capacity forecast each year, for the NYCA and for each Locality as required. Preliminary NYCA peak forecast updated in September NYCA peak forecast & Locality peak forecasts updated in December 2

3 Hypothetical Response of Load to Weather Megawatts Design Condition for Peak Temperature-Humidity Index 3

4 91 89 Red lines show mean & +/- 1 sigma bandwidth NYCA Peak Producing CTHI to

5 12 10 Histogram of NYCA Peak Producing CTHI to 2010 Is this a normal distribution? 8 Frequency Histogram of CTHI 5

6 NYCA Composite PP CTHI Actual Versus Normal Distribution of PPCTHI 1975 to Deviation of actual from normal is not significant; therefore we use a normal of CTHI to perform LFU analysis Normal Actual CDF Sigmoid - Solver Fit 6

7 Hypothetical Response of Load to Weather Mega-Watts Load forecast uncertainty examines the distribution of load, given a normal distribution of the CTHI around design conditions Temperature-Humidity Index 7

8 45% 40% 35% 30% 25% 20% 15% All Bins are 1-Sigma wide, centered at 50% Normal Probability Density Function Bin Prob % % % % % % % Tot 100.0% 10% 5% 0%

9 Hypothetical Weather Response - Nonlinear A linear model of weather response would have a constant value of MW/THI Mega-Watts per THI Temperature-Humidity Index 9

10 LFU Model for With Linear & Nonlinear Models Virtually no difference between models at lower levels of MW Non-linear models indicate lower MW values at upper ranges of loads, due to saturation sigma +1 sigma Per-Unit MW at various Load Levels Linear Model Non-Linear Model 10

11 Summary of LFU Methodology Assemble daily peak MW for region or locality May be for single year or multiple years May delete outliers, holidays & Fridays Add adjustments for load management & other EOPs Assemble daily weather data for region or locality Obtain peak-producing weather data Obtain mean & standard deviation Examine distribution for normality. Fit sigmoid cdf as check or use standard statistics (check the literature.) Build MW load model for region or locality Fit linear, pw-linear, cubic or quadratic models in terms of MW & weather data Obtain Design MW (50 th percentile) for each year using 50 th percentile weather Construct Per-Unit MW models for representative years Construct LFU bins on a per-unit basis for region or locality Standard bin values are at 0, +/-1, +/-2,+/-3 sigma Can also be used for other design conditions (1-in-3 vs 1-in-2) Develop charts & graphics Review & check results 11

12 The New York Independent System Operator (NYISO) is a not-for forprofit corporation that began operations in The NYISO operates New York s s bulk electricity grid, administers the state s s wholesale electricity markets, and performs comprehensive reliability and resource planning for the state s s bulk electricity system.