Prediction of system marginal price of electricity using wavelet transform analysis

This paper proposes a novel wavelet transform based technique for prediction of the system marginal price (SMP) of electricity. Daubechies D1(Haar), D2 and D4 wavelet transforms are adopted, and the numerical results reveal that certain wavelet components can effectively be used to identify the SMP...

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Bibliographic Details
Published inEnergy conversion and management Vol. 43; no. 14; pp. 1839 - 1851
Main Authors Kim, Chang-il, Yu, In-Keun, Song, Y.H
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 01.09.2002
Elsevier
Subjects
Applied sciences
Economic data
Electric energy
Energy
Energy economics
Exact sciences and technology
General, economic and professional studies
Methodology. Modelling
Power pool
System marginal price
Wavelet transform
System marginal price
Wavelet transform
Power pool
Electricity
Methodology
Wavelet transformation
Price
Energy economy
Load curve
Regression analysis
Marginal cost
Forecasting
Multiple regression
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Summary:This paper proposes a novel wavelet transform based technique for prediction of the system marginal price (SMP) of electricity. Daubechies D1(Haar), D2 and D4 wavelet transforms are adopted, and the numerical results reveal that certain wavelet components can effectively be used to identify the SMP characteristics with relation to the system demand in electric power systems. The wavelet coefficients associated with certain frequency and time localization are adjusted using the conventional multiple regression method and then reconstructed in order to predict the SMP for the next scheduling day through a five scale synthesis technique. The outcome of the study clearly indicates that the proposed wavelet transform approach can be used as an attractive and effective means for SMP forecasting.
ISSN:0196-8904
1879-2227
DOI:10.1016/S0196-8904(01)00127-3