Iranian Journal of Electrical and Electronic Engineering, Volume (4), No (8), Year (2012-12) , Pages (322-328)

Title : ( Application of a New Hybrid Method for Day-Ahead Energy Price Forecasting in Iranian Electricity Market )

Authors: Arash Asrari , Mohammad Hossein Javidi Dasht Bayaz ,

Citation: BibTeX | EndNote

Abstract

Abstract- In a typical competitive electricity market, a large number of short-term and long-term contracts are set on basis of energy price by an Independent System Operator (ISO). Under such circumstances, accurate electricity price forecasting can play a significant role in improving the more reasonable bidding strategies adopted by the electricity market participants. So, they cannot only raise their profit but also manage the relevant market more efficiently. This conspicuous reason has motivated the researchers to develop the most accurate, though sophisticated, forecasting models to predict the short-term electricity price as precisely as possible. In this article, a new method is suggested to forecast the next day\\\\\\\\\\\\\\\'s electricity price of Iranian Electricity Market. The authors have used this hybrid model successfully in their previous publications to predict the electric load data of Ontario Electricity Market [1] and of the Spinning Reserve data of Khorasan Electricity Network [2] respectively.

Keywords

, Keywords: Energy Price, Gray Model, Fuzzy Approach, Markov Chain Model, Transition Probability Matrix
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@article{paperid:1031578,
author = {Arash Asrari and Javidi Dasht Bayaz, Mohammad Hossein},
title = {Application of a New Hybrid Method for Day-Ahead Energy Price Forecasting in Iranian Electricity Market},
journal = {Iranian Journal of Electrical and Electronic Engineering},
year = {2012},
volume = {4},
number = {8},
month = {December},
issn = {1735-2827},
pages = {322--328},
numpages = {6},
keywords = {Keywords: Energy Price; Gray Model; Fuzzy Approach; Markov Chain Model; Transition Probability Matrix},
}

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%0 Journal Article
%T Application of a New Hybrid Method for Day-Ahead Energy Price Forecasting in Iranian Electricity Market
%A Arash Asrari
%A Javidi Dasht Bayaz, Mohammad Hossein
%J Iranian Journal of Electrical and Electronic Engineering
%@ 1735-2827
%D 2012

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