Modeling electricity loads in California: ARMA models with hyperbolic noise

Joanna Nowicka-Zagrajek and Rafał Weron

No HSC/02/02, HSC Research Reports from Hugo Steinhaus Center, Wroclaw University of Science and Technology

Abstract: 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.

Keywords: Electricity load; ARMA model; Heavy tails; Hyperbolic distribution; Forecast (search for similar items in EconPapers)
JEL-codes: C16 C52 C53 Q40 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2002
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (34)

Published in Signal Processing 82 (2002) 1903-1915.

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http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_02_02.pdf Final draft, 2002 (application/pdf)
http://dx.doi.org/doi:10.1016/S0165-1684(02)00318-3 Final printed version, 2002 (text/html)
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