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Risk-constrained bidding strategy for wind power producer in day-ahead and balancing markets

Algebra; Stochastic models; Stochastic programming; Stochastic systems; Wind power; Algebraic modeling; Balancing market; Bidding strategy; Competitive electricity markets; Day-ahead electricity market; Electricity prices; Optimal bidding strategy; Software environments; Power markets

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Main Authors: Tahmasebi M., Pasupuleti J., Askari M.T., Reyasudin Basir Khan M.
Other Authors: 55945605900
Format: Article
Published: Engineering and Scientific Research Groups 2023
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spelling my.uniten.dspace-239322023-05-29T14:53:16Z Risk-constrained bidding strategy for wind power producer in day-ahead and balancing markets Tahmasebi M. Pasupuleti J. Askari M.T. Reyasudin Basir Khan M. 55945605900 11340187300 36103897600 57222270109 Algebra; Stochastic models; Stochastic programming; Stochastic systems; Wind power; Algebraic modeling; Balancing market; Bidding strategy; Competitive electricity markets; Day-ahead electricity market; Electricity prices; Optimal bidding strategy; Software environments; Power markets Participation of wind power producer in competitive electricity markets face to numerous challenges is caused by wind power and electricity price uncertainties. For overcome to this challenges the risk-constrained optimal bidding strategy for wind power producer in the short term electricity markets is proposed in this paper. The proposed mathematical model has been solved and optimized based on the stochastic programming method in General Algebraic Modeling System (GAMS) software environment. The comparative results of the three cases of various risk penalty factor, have been shown with the increase of the risk penalty factor, the amount of power bidding in day-ahead electricity market and expected profit decreased. Also, positive imbalance and CVaR are increased. Copyright � JES 2018 on-line: journal/esrgroups.org/jes Final 2023-05-29T06:53:15Z 2023-05-29T06:53:15Z 2018 Article 2-s2.0-85102135932 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102135932&partnerID=40&md5=4dcfadb9da8c4af77d9b7960c3b411ac https://irepository.uniten.edu.my/handle/123456789/23932 14 4 34 47 Engineering and Scientific Research Groups Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Algebra; Stochastic models; Stochastic programming; Stochastic systems; Wind power; Algebraic modeling; Balancing market; Bidding strategy; Competitive electricity markets; Day-ahead electricity market; Electricity prices; Optimal bidding strategy; Software environments; Power markets
author2 55945605900
author_facet 55945605900
Tahmasebi M.
Pasupuleti J.
Askari M.T.
Reyasudin Basir Khan M.
format Article
author Tahmasebi M.
Pasupuleti J.
Askari M.T.
Reyasudin Basir Khan M.
spellingShingle Tahmasebi M.
Pasupuleti J.
Askari M.T.
Reyasudin Basir Khan M.
Risk-constrained bidding strategy for wind power producer in day-ahead and balancing markets
author_sort Tahmasebi M.
title Risk-constrained bidding strategy for wind power producer in day-ahead and balancing markets
title_short Risk-constrained bidding strategy for wind power producer in day-ahead and balancing markets
title_full Risk-constrained bidding strategy for wind power producer in day-ahead and balancing markets
title_fullStr Risk-constrained bidding strategy for wind power producer in day-ahead and balancing markets
title_full_unstemmed Risk-constrained bidding strategy for wind power producer in day-ahead and balancing markets
title_sort risk-constrained bidding strategy for wind power producer in day-ahead and balancing markets
publisher Engineering and Scientific Research Groups
publishDate 2023
_version_ 1806425633411039232
score 13.222552

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