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Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market

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dc.citedby6
dc.contributor.authorAskari M.T.en_US
dc.contributor.authorKadir M.Z.A.A.en_US
dc.contributor.authorTahmasebi M.en_US
dc.contributor.authorBolandifar E.en_US
dc.contributor.authorid36103897600en_US
dc.contributor.authorid25947297000en_US
dc.contributor.authorid55945605900en_US
dc.contributor.authorid55861921300en_US
dc.date.accessioned2023-05-29T07:23:50Z
dc.date.available2023-05-29T07:23:50Z
dc.date.issued2019
dc.descriptionCommerce; Data mining; Dynamic programming; Game theory; Markov processes; Monte Carlo methods; Power markets; Stochastic systems; Strategic planning; Wind power; Cournot game theory; Generation expansion planning; Stochastic dynamic programming; Uncertainties; Wind resources; Investmentsen_US
dc.description.abstractIn this paper, a novel framework for the estimation of optimal investment strategies for combined wind-thermal companies is proposed. The medium-term restructured power market was simulated by considering the stochastic and rational uncertainties, the wind uncertainty was evaluated based on a data mining technique, and the electricity demand and fuel price were simulated using the Monte Carlo method. The Cournot game concept was used to determine the Nash equilibrium for each state and stage of the stochastic dynamic programming (DP). Furthermore, the long-term stochastic uncertainties were modeled based on the Markov chain process. The long-term optimal investment strategies were then solved for combined wind-thermal investors based on the semi-definite programming (SDP) technique. Finally, the proposed framework was implemented in the hypothetical restructured power market using the IEEE reliability test system (RTS). The conducted case study confirmed that this framework provides robust decisions and precise information about the restructured power market for combined wind-thermal investors. � 2019, The Author(s).en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/s40565-019-0505-x
dc.identifier.epage1279
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85073069129
dc.identifier.spage1267
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85073069129&doi=10.1007%2fs40565-019-0505-x&partnerID=40&md5=40c843f02aae5eb8a52b43a3595c96b3
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24477
dc.identifier.volume7
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleJournal of Modern Power Systems and Clean Energy
dc.titleModeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power marketen_US
dc.typeArticleen_US
dspace.entity.typePublication
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