Next day price forecasting in deregulated market by combination of artificial neural network and ARIMA time series models

被引：5
作者：
Areekul, Phatchakorn [1 ]
Senjyu, Tomonobu [1 ]
Urasaki, Naomitsu [1 ]
Yona, Atsushi [1 ]
机构：
[1] Faculty of Engineering, University of the Ryukyus, Nakagami, Okinawa 903-0213, 1, Senbaru Nishihara-cho
来源：
IEEJ Transactions on Power and Energy | 2009年 / 129卷 / 10期
关键词：
ARIMA; Back-propagation; Combination methodology; Electricity price forecasting; Neural network;
D O I：
10.1541/ieejpes.129.1267
中图分类号：
学科分类号：
摘要：
Electricity price forecasting is becoming increasingly relevant to power producers and consumers in the new competitive electric power markets, when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper proposed a method to predict hourly electricity prices for next-day electricity markets by combination methodology of ARIMA and ANN models. The proposed method is examined on the Australian National Electricity Market (NEM), New South Wales regional in year 2006. Comparison of forecasting performance with the proposed ARIMA, ANN and combination (ARIMA-ANN) models are presented. Empirical results indicate that an ARIMA-ANN model can improve the price forecasting accuracy. © 2009 The Institute of Electrical Engineers of Japan.
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收藏
页码：1267 / 1274
页数：7
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