A Stochastic Hybrid Method to Forecast Operating Reserve: Comparison of Fuzzy and Classical Set Theory

    Authors

    A. Asrari; A. Kargarian; M. H. Javidi; M. Monfared;S. Lotfifard

    Comments

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    Abbreviated Journal Title

    Electr. Power Compon. Syst.

    Keywords

    operating reserve; Gray model; Markov chain model; fuzzy approach; NEURAL-NETWORK; ELECTRICITY MARKETS; WAVELET TRANSFORM; SYSTEM; MODEL; Engineering, Electrical & Electronic

    Abstract

    Accurate operating reserve forecasting helps the system operator to make decisions contributing to the security of the power system. It also helps market participants to adopt proper strategic bidding for the day-ahead ancillary services market to enhance their financial profit. This article proposes a stochastic hybrid method to forecast the operating reserve requirement in day-ahead electricity markets. At the first stage, based on using a modified Gray model, the day-ahead operating reserve is forecasted. In order to improve the accuracy of the operating reserve forecasting, at the next stage, a Markov chain model is used to predict the forecasting error of the Gray model. These two models are linked to each other using two different approachesclassical and fuzzy. The proposed approach is verified by the historical data of the operating reserve for spring and autumn seasons in the Khorasan Electricity Network located in Khorasan Province, Iran.

    Journal Title

    Electric Power Components and Systems

    Volume

    41

    Issue/Number

    8

    Publication Date

    1-1-2013

    Document Type

    Article

    Language

    English

    First Page

    806

    Last Page

    823

    WOS Identifier

    WOS:000318282300004

    ISSN

    1532-5008

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