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Title: Load Forecasting in Electric Utility Integrated Resource Planning

Abstract

Integrated resource planning (IRP) is a process used by many vertically-integrated U.S. electric utilities to determine least-cost/risk supply and demand-side resources that meet government policy objectives and future obligations to customers and, in many cases, shareholders. Forecasts of energy and peak demand are a critical component of the IRP process. There have been few, if any, quantitative studies of IRP long-run (planning horizons of two decades) load forecast performance and its relationship to resource planning and actual procurement decisions. In this paper, we evaluate load forecasting methods, assumptions, and outcomes for 12 Western U.S. utilities by examining and comparing plans filed in the early 2000s against recent plans, up to year 2014. We find a convergence in the methods and data sources used. We also find that forecasts in more recent IRPs generally took account of new information, but that there continued to be a systematic over-estimation of load growth rates during the period studied. We compare planned and procured resource expansion against customer load and year-to-year load growth rates, but do not find a direct relationship. Load sensitivities performed in resource plans do not appear to be related to later procurement strategies even in the presence of large forecastmore » errors. These findings suggest that resource procurement decisions may be driven by other factors than customer load growth. Our results have important implications for the integrated resource planning process, namely that load forecast accuracy may not be as important for resource procurement as is generally believed, that load forecast sensitivities could be used to improve the procurement process, and that management of load uncertainty should be prioritized over more complex forecasting techniques.« less

Authors:
 [1];  [1];  [1];  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1371722
Report Number(s):
LBNL-1006395
ir:1006395
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
29 ENERGY PLANNING, POLICY, AND ECONOMY

Citation Formats

Carvallo, Juan Pablo, Larsen, Peter H., Sanstad, Alan H, and Goldman, Charles A. Load Forecasting in Electric Utility Integrated Resource Planning. United States: N. p., 2017. Web. doi:10.2172/1371722.
Carvallo, Juan Pablo, Larsen, Peter H., Sanstad, Alan H, & Goldman, Charles A. Load Forecasting in Electric Utility Integrated Resource Planning. United States. doi:10.2172/1371722.
Carvallo, Juan Pablo, Larsen, Peter H., Sanstad, Alan H, and Goldman, Charles A. Wed . "Load Forecasting in Electric Utility Integrated Resource Planning". United States. doi:10.2172/1371722. https://www.osti.gov/servlets/purl/1371722.
@article{osti_1371722,
title = {Load Forecasting in Electric Utility Integrated Resource Planning},
author = {Carvallo, Juan Pablo and Larsen, Peter H. and Sanstad, Alan H and Goldman, Charles A.},
abstractNote = {Integrated resource planning (IRP) is a process used by many vertically-integrated U.S. electric utilities to determine least-cost/risk supply and demand-side resources that meet government policy objectives and future obligations to customers and, in many cases, shareholders. Forecasts of energy and peak demand are a critical component of the IRP process. There have been few, if any, quantitative studies of IRP long-run (planning horizons of two decades) load forecast performance and its relationship to resource planning and actual procurement decisions. In this paper, we evaluate load forecasting methods, assumptions, and outcomes for 12 Western U.S. utilities by examining and comparing plans filed in the early 2000s against recent plans, up to year 2014. We find a convergence in the methods and data sources used. We also find that forecasts in more recent IRPs generally took account of new information, but that there continued to be a systematic over-estimation of load growth rates during the period studied. We compare planned and procured resource expansion against customer load and year-to-year load growth rates, but do not find a direct relationship. Load sensitivities performed in resource plans do not appear to be related to later procurement strategies even in the presence of large forecast errors. These findings suggest that resource procurement decisions may be driven by other factors than customer load growth. Our results have important implications for the integrated resource planning process, namely that load forecast accuracy may not be as important for resource procurement as is generally believed, that load forecast sensitivities could be used to improve the procurement process, and that management of load uncertainty should be prioritized over more complex forecasting techniques.},
doi = {10.2172/1371722},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jul 19 00:00:00 EDT 2017},
month = {Wed Jul 19 00:00:00 EDT 2017}
}

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