Modeling electricity loads in California: ARMA models with hyperbolic noise
In this paper we address the issue of modeling and forecasting electricity loads. We apply a two-step procedure to a series of system-wide loads from the California power market. First, we remove the weekly and annual seasonalities. Then, after analyzing properties of the deseasonalized data we fit an autoregressive moving average model. The obtained residuals seem to be independent but with tails heavier than Gaussian. It turns out that the hyperbolic distribution provides an excellent fit. As a justification for our approach we supply out-of-sample forecasts. As it turns out, our method performs significantly better than the one used by the California System Operator.
|Date of creation:||2002|
|Publication status:||Published in Signal Processing 82 (2002) 1903-1915.|
|Contact details of provider:|| Postal: Wybrzeze Wyspianskiego 27, 50-370 Wroclaw|
Web page: http://prac.im.pwr.wroc.pl/~hugo
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- Rafal Weron, 2000. "Energy price risk management," HSC Research Reports HSC/00/02, Hugo Steinhaus Center, Wroclaw University of Technology.
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- Weron, R. & Kozłowska, B. & Nowicka-Zagrajek, J., 2001. "Modeling electricity loads in California: a continuous-time approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 344-350. Full references (including those not matched with items on IDEAS)
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For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Rafal Weron)
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