Load Forecast Model Development

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Transcription:

Load Forecast Model Development Load Analysis Subcommittee June 20, 2018

Disclaimer This is the current status of ongoing model development. The results are not final and are only indicative of what potential impacts on the forecast might be. 2

Potential Process First Model Estimated Base Load Day-type Economics Model Estimation Forecasted Base Load End-Use Characteristics Load Forecast Distribution Weather Simulation Model Estimation Base Load Weather End-Use Characteristics Second Model 3

Commercial Load Previously used a static weight to transform employment trends to square footage trends. Stakeholder concern that this would miss the changing relationship over time. Looked at the relationship of U.S. square footage to U.S. employment Commercial Equipment indexes are expressed in intensity per square foot (not per customer). Getting a proxy for square foot per customer, can establish intensity per customer. 4

1.6 U.S. Building Space and Employment Index, 1998 = 1.0 1.5 1.4 1.3 1.2 1.1 1.0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 Commercial Square Footage Employment Sources: Itron, Moody s Analytics 5

1.3 Ratio of Building Space to Employment 1.2 1.1 1.0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 Sources: Itron, Moody s Analytics 6

Coincident Peak Model Spreadsheet Base Contains base history and forecast values assumed in the model Coefficients Model parameters from the Second Model Residuals Model Estimates and Residuals 7

PJM RTO Summer Forecast 180,000 170,000 160,000 150,000 140,000 130,000 120,000 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 Unrestricted Peak Weather Normalized Peak 2018 Forecast Test Model 8

Summer 2021 Forecast Distributions 1.2 Per-Unitized Peak 1.1 1.0 0.9 0.8 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Peak Percentile 2018 Forecast Test Model 9

6% Summer Zonal CP Differences Test Model vs 2018 Forecast For Delivery Year 2021/22 4% 2% 0% -2% -4% -6% 10

Summer Forecast Model Accuracy Forecast Model Solved vs Top Ten Summer Days per Year Mean Absolute Percent Error 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% 0 1 2 3 4 5 Forecast Horizon Current Model Test Model 11

Summer Error Zero Year Forecast Horizon Percent Error 8% 6% 4% 2% 0% -2% -4% -6% -8% 2010 2011 2012 2013 2014 2015 2016 2017 Forecast Vintage Pct Err on Rank Day 2-10 Pct Err on Rank Day 1 Current Model (Abs Pct Err) Test Model (Abs Pct Err) 12

Summer Forecast Observations Test Model has very similar growth pattern (0.3-0.4% growth) to 2018 forecast, though starts out about 0.7% lower Summer forecast distribution is a little bit more spread out, with generally slightly higher per-unitized values above the median. Zonal changes generally range between +/- 2%. Several zones in New Jersey have positive changes outside this range, while several Pennsylvania zones have negative changes outside this range. 13

PJM RTO Winter Forecast 160,000 150,000 140,000 130,000 120,000 110,000 100,000 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 Unrestricted Peak Weather Normalized Peak 2018 Forecast Test Model 14

Winter 2021/22 Forecast Distributions 1.2 Per-Unitized Peak 1.1 1.0 0.9 0.8 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Peak Percentile 2018 Forecast Test Model 15

Winter Zonal CP Differences Test Model vs 2018 Forecast For Delivery Year 2021/22 10% 8% 6% 4% 2% 0% -2% -4% -6% -8% -10% 16

4.0% Winter Forecast Model Accuracy Forecast Model Solved vs Top Ten Winter Days per Year Mean Absolute Percent Error 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% 0 1 2 3 4 5 Forecast Horizon Current Model Test Model 17

8% Winter Error Zero Year Forecast Horizon 6% 4% Pct Error 2% 0% -2% -4% -6% -8% 2010 2011 2012 2013 2014 2015 2016 2017 Forecast Vintage Pct Error on Rank Day 2-10 Pct Err on Rank Day 1 Current Model (Abs Pct Err) Test Model (Abs Pct Err) 18

Winter Forecast Observations While starting higher, Test Model has slower growth relative to 2018 forecast (0.2% vs 0.4%). More so than Summer, Winter forecast distribution is also spread out, with higher per-unitized values above the median. Zonal changes generally range between +/- 2%. PENLC, DQE, and RECO stood out as zones with negative changes outside this range. EKPC, PEPCO, and VEPCO stood out as zones with positive changes outside this range. 19

Next Steps Stakeholder Feedback Investigate additional refinements Develop Energy, Non-Coincident, and LDA CP models 20