期刊
ENERGY ECONOMICS
卷 44, 期 -, 页码 135-142出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.eneco.2014.03.017
关键词
Support vector machines; Autoregressive model; European Energy Exchange; Day-ahead market
类别
In this paper we investigate the efficiency of a support vector machine (SVM)-based forecasting model for the next-day directional change of electricity prices. We first adjust the best autoregressive SVM model and then we enhance it with various related variables. The system is tested on the daily Phelix index of the German and Austrian control area of the European Energy Exchange (EEX) wholesale electricity market. The forecast accuracy we achieved is 76.12% over a 200 day period. (C) 2014 Elsevier B.V. All rights reserved.
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