Title
A Stochastic Hybrid Method to Forecast Operating Reserve: Comparison of Fuzzy and Classical Set Theory
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
ISSN
1532-5008
Recommended Citation
"A Stochastic Hybrid Method to Forecast Operating Reserve: Comparison of Fuzzy and Classical Set Theory" (2013). Faculty Bibliography 2010s. 3639.
https://stars.library.ucf.edu/facultybib2010/3639
Comments
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