Przeglad Elektrotechniczny-Electrical Review, ( ISI ), Volume (2012), No (3), Year (2012-2) , Pages (228-237)

Title : ( Application of Gray-Fuzzy-Markov Chain Method for Day-Ahead Electric Load Forecasting )

Authors: Arash Asrari , Dawood Seyed Javan , Mohammad Hossein Javidi Dasht Bayaz , Mohammad Monfared ,

Citation: BibTeX | EndNote

Short-term load forecasting (STLF) plays a decisive role in electric power system operation and planning. Accurate load forecasting not only reduces the generation costs of power systems, but also serves to maximize profit for participants in electricity markets. In recent years, power markets have grown more deregulated and competitive, adding to the complexity and uncertainties of load, and making it more difficult for conventional techniques to accurately forecast the load. To improve the accuracy of load forecasting, this paper suggests a hybrid method, called Gray-Fuzzy-Markov Chain Method (GFMCM), comprising three stages. In the first stage, daily load is forecasted by Gray model, with its training deviations classified, in a second stage, by fuzzy-set theory, and finally, fed into Markov chain model to predict future relative errors that might be supplied by the Gray model. The proposed approach has been verified by the historical data of power consumption in Ontario, PJM and Iranian electricity markets. The obtained forecasts by GFMCM proved to have better prediction properties compared to the other forecasting techniques, such as Gray models, specifically GM(1,1) and GM(1,2), ARIMA time series, wavelet-ARIMA and multi-layer perceptron (MLP) neural network.

Keywords

, Short-term load forecasting, Gray model, Fuzzy clustering, Markov chain model, Transition probability
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@article{paperid:1026021,
author = {Asrari, Arash and Seyed Javan, Dawood and Javidi Dasht Bayaz, Mohammad Hossein and Monfared, Mohammad},
title = {Application of Gray-Fuzzy-Markov Chain Method for Day-Ahead Electric Load Forecasting},
journal = {Przeglad Elektrotechniczny-Electrical Review},
year = {2012},
volume = {2012},
number = {3},
month = {February},
issn = {0033-2097},
pages = {228--237},
numpages = {9},
keywords = {Short-term load forecasting; Gray model; Fuzzy clustering; Markov chain model; Transition probability matrix},
}

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%0 Journal Article
%T Application of Gray-Fuzzy-Markov Chain Method for Day-Ahead Electric Load Forecasting
%A Asrari, Arash
%A Seyed Javan, Dawood
%A Javidi Dasht Bayaz, Mohammad Hossein
%A Monfared, Mohammad
%J Przeglad Elektrotechniczny-Electrical Review
%@ 0033-2097
%D 2012

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