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  • 标题:Forecasting Short Term Electricity Price Using Artificial Neural Network and Fuzzy Regression
  • 本地全文:下载
  • 作者:Reza Ghodsi ; Mohammad Saleh Zakerinia
  • 期刊名称:International Journal of Academic Research in Business and Social Sciences
  • 电子版ISSN:2222-6990
  • 出版年度:2012
  • 卷号:2
  • 期号:1
  • 页码:286-292
  • 出版社:Human Resource Management Academic Research Society
  • 摘要:It is very important to forecast electricity price in a deregulated electricity market for choosing the bidding strategy, and it is the most important signal for other players. It engulfs information for both customers and producers in order to maximize their profit. Thus, choosing the best method of price forecasting is a crucial task to have the most accurate forecast. In this paper the price forecasting is done based on different methods including autoregressive integrated moving average (ARIMA), artificial neural network (ANN) and fuzzy regression. The method is examined by using data of Ontario electricity market. The results of different methods are compared and the best method is chosen. Fuzzy regression model is a new method in forecasting and it is rare in the literature review; it is showed that it leads to the best results
  • 关键词:ARIMA; Artificial neural network; Fuzzy regression; forecasting
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