Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market
Commerce; 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; Investments
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Springer Heidelberg
2023
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my.uniten.dspace-244772023-05-29T15:23:50Z Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market Askari M.T. Kadir M.Z.A.A. Tahmasebi M. Bolandifar E. 36103897600 25947297000 55945605900 55861921300 Commerce; 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; Investments In 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). Final 2023-05-29T07:23:50Z 2023-05-29T07:23:50Z 2019 Article 10.1007/s40565-019-0505-x 2-s2.0-85073069129 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073069129&doi=10.1007%2fs40565-019-0505-x&partnerID=40&md5=40c843f02aae5eb8a52b43a3595c96b3 https://irepository.uniten.edu.my/handle/123456789/24477 7 5 1267 1279 All Open Access, Gold Springer Heidelberg Scopus |
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Malaysia |
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Universiti Tenaga Nasional |
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| description |
Commerce; 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; Investments |
| author2 |
36103897600 |
| author_facet |
36103897600 Askari M.T. Kadir M.Z.A.A. Tahmasebi M. Bolandifar E. |
| format |
Article |
| author |
Askari M.T. Kadir M.Z.A.A. Tahmasebi M. Bolandifar E. |
| spellingShingle |
Askari M.T. Kadir M.Z.A.A. Tahmasebi M. Bolandifar E. Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market |
| author_sort |
Askari M.T. |
| title |
Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market |
| title_short |
Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market |
| title_full |
Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market |
| title_fullStr |
Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market |
| title_full_unstemmed |
Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market |
| title_sort |
modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market |
| publisher |
Springer Heidelberg |
| publishDate |
2023 |
| _version_ |
1806428500326875136 |
| score |
13.222552 |