Artificial Intelligence in Electricity Market Operations and Management

Artificial Intelligence in Electricity Market Operations and Management

Zhao Y. Dong, Tapan K. Saha, Kit P. Wong
Copyright: © 2006 |Pages: 24
DOI: 10.4018/978-1-59140-702-7.ch008
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Abstract

This chapter introduces advanced techniques such as artificial neural networks, wavelet decomposition, support vector machines, and data-mining techniques in electricity market demand and price forecasts. It argues that various techniques can offer different advantages in providing satisfactory demand and price signal forecast results for a deregulated electricity market, depending on the specific needs in forecasting. Furthermore, the authors hope that an understanding of these techniques and their application will help the reader to form a comprehensive view of electricity market data analysis needs, not only for the traditional time-series based forecast, but also the new correlation-based, price spike analysis.

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