A framework for electricity price spike analysis with advanced data mining methods

Zhao, J. H., Dong, Z. Y., Li, Xue and Wong, K. P. (2007) A framework for electricity price spike analysis with advanced data mining methods. IEEE Transactions on Power Systems, 22 1: 376-385.


Author Zhao, J. H.
Dong, Z. Y.
Li, Xue
Wong, K. P.
Title A framework for electricity price spike analysis with advanced data mining methods
Journal name IEEE Transactions on Power Systems  (ERA 2012 Listed)    (ERA 2010 Rank A*)   Check publisher's open access policy
Publication date 2007-02
Sub-type Article
DOI 10.1109/TPWRS.2006.889139
Volume number 22
Issue number 1
ISSN 0885-8950
Start page 376
End page 385
Total pages 10
Place of publication Piscataway
Publisher IEEE-Institute Electrical Electronics Engineers Inc
Collection year 2008
Language eng
Subject 290901 Electrical Engineering
C1
660301 Electricity transmission
Abstract There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.
Keyword Power system analysis
data mining
electricity market
electricity price forecast
price spike reduction
classification
feature selection
Q-Index Code C1
Q-Index Status Confirmed Code

 
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Created: Thu, 05 Jul 2007, 13:55:53 EST by Zhao Yang Dong on behalf of School of Information Technol and Elec Engineering