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Short-term electricity price forecasting with time series models: A review and evaluation

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Author Info

  • Rafal Weron
  • Adam Misiorek

Abstract

We investigate the forecasting power of different time series models for electricity spot prices. The models include different specifications of linear autoregressive time series with heteroscedastic noise and/or additional fundamental variables and non-linear regime-switching TAR-type models. The models are tested on a time series of hourly system prices and loads from the California power market. Data from the period July 5, 1999 - April 2, 2000 are used for calibration and from the period April 3 - December 3, 2000 for out-of-sample testing.

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File URL: http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_06_01.pdf
File Function: Final draft, 2006
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Bibliographic Info

Paper provided by Hugo Steinhaus Center, Wroclaw University of Technology in its series HSC Research Reports with number HSC/06/01.

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Length: 22 pages
Date of creation: 2006
Date of revision:
Publication status: Published in "Complex Electricity Markets", ed. W. Mielczarski, Chapter 10, 231-254 (2006).
Handle: RePEc:wuu:wpaper:hsc0601

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Related research

Keywords: Electricity price forecasting; Autoregression (AR) model; Threshold Autoregression (TAR) model; Electricity load;

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Cited by:
  1. Krzysztof Burnecki & Rafal Weron, 2006. "Visualization tools for insurance risk processes," HSC Research Reports HSC/06/06, Hugo Steinhaus Center, Wroclaw University of Technology.
  2. Weron, Rafal & Misiorek, Adam, 2007. "Heavy tails and electricity prices: Do time series models with non-Gaussian noise forecast better than their Gaussian counterparts?," MPRA Paper 2292, University Library of Munich, Germany, revised Oct 2007.
  3. Weron, Rafal & Misiorek, Adam, 2006. "Point and interval forecasting of wholesale electricity prices: Evidence from the Nord Pool market," MPRA Paper 1363, University Library of Munich, Germany.

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