Unintended biases of an electricity demand forecast based on a double-log regression

Chi Keung WOO, J. ZARNIKAU, K.H. CAO

Research output: Contribution to journalArticlespeer-review

Abstract

This paper identifies the unintended biases occasionally not recognized when using a double-log regression to make an electricity demand forecast. It shows that ignoring the stochastic nature of forecasts of income, price and weather can vastly overstate the forecast’s precision, potentially causing inadequate resource procurement for reliable service at least cost. Fortunately, the overstated precision is readily avoidable because its correction uses information available when making the forecast. Copyright © 2020 Elsevier Inc. All rights reserved.
Original languageEnglish
Article number106866
JournalThe Electricity Journal
Volume33
Issue number10
Early online date10 Oct 2020
DOIs
Publication statusE-pub ahead of print - 10 Oct 2020

Citation

Woo, C. K., Zarnikau, J., & Cao, K. H. (2020). Unintended biases of an electricity demand forecast based on a double-log regression. The Electricity Journal, 33(10). Retrieved from https://doi.org/10.1016/j.tej.2020.106866

Keywords

  • Double-log regression
  • Electricity demand forecast
  • Forecast bias
  • Forecast precision

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