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

Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market
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摘要 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 longterm 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. 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 longterm 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.
出处 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2019年第5期1267-1279,共13页 现代电力系统与清洁能源学报(英文)
关键词 WIND RESOURCES Power market Generation expansion planning UNCERTAINTIES COURNOT game theory Stochastic dynamic PROGRAMMING Wind resources Power market Generation expansion planning Uncertainties Cournot game theory Stochastic dynamic programming
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