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. © 2008 by IGI Global. All rights reserved.
| Original language | English |
|---|---|
| Title of host publication | Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications: Volume I-IV |
| Publisher | IGI Global Publishing |
| Pages | 1821-1840 |
| Volume | 1-4 |
| ISBN (Print) | 9781599049427, 1599049414, 9781599049410 |
| DOIs | |
| Publication status | Published - 1 Jan 2007 |
| Externally published | Yes |
Bibliographical note
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