標題: Forecasting electricity market prices: A neural network based approach
作者: Xu, YY
Hsieh, R
Lu, Y
Shen, YC
Chuang, SC
Fu, HC
Bock, C
Pao, HT
資訊工程學系
Department of Computer Science
公開日期: 2004
摘要: This paper presents a neural network approach to forecast the Phelix Base (PB) electricity market prices for European Energy Exchange (EEX). Up to now there has been little scientific work on forecasting the price development on the electricity markets. In this study, the Phelix Base moving average (PBMA), the moving difference (PBMD), and multilayer feedforward neural networks (MLNN) are used to predict various period for 7, 14, 21, 28, 63, 91, 182, and 273 days ahead of electric prices. The experimental results of forecasting by MLNNs and linear methods (autoregressive error model) are compared and discussed. The MLNNs outperform from 11.4% to 64.6% superior to the traditional linear regression method. It seems that the proposed MLNN can be very useful in predicting the electricity market prices of EEX.
URI: http://hdl.handle.net/11536/18209
ISBN: 0-7803-8359-1
ISSN: 1098-7576
期刊: 2004 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS
起始頁: 2789
結束頁: 2794
Appears in Collections:Conferences Paper