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Title |
Wavelet Approach to Electricity Spot-Price Forecasting in a Deregulated Electricity Market |
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Author |
J. JAIS, D. BENAOUDA, F. MURTAGH and A.H. HASHIM |
| Citation |
Vol. 25 No. 5 pp. 136-142 |
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Abstract |
The purpose of deregulation is to give consumers free choices of their electricity supply. Electricity generators, transmission, and distribution companies are driven by the market to maximize their profits. The accuracy of electricity spot price forecasting is crucial to any of the above participating companies, since it provides them with spot price signal in the future that is used to optimize the operational planning. In this article, we propose a wavelet multiscale decomposition based autoregressive approach for the prediction of one-hour ahead and one-day ahead electricity spot price based on historical electricity price and predicted electricity load data. This approach is based on a multiple resolution decomposition of the signal using the redundant Haar ? trous wavelet transform whose advantage is taking into account the asymmetric nature of the time-varying data. We assess results produced by this multiscale auto-regressive (MAR) method, with single resolution autoregressive (AR), and multilayer perceptron (MLP) model. Numerical results are based on the New South Wales (Australia) electricity load and price data that is provided by the National Electricity Market Management Company (NEMMCO). |
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Keywords |
Wavelet transform, electricity price forecast, time-series, multi-layer perceptron. |
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