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• W3082265624 abstract "Abstract The large-scale utilization and sharing of renewable energy in interconnected systems is crucial for realizing “instrumented, interconnected, and intelligent” power grids. The traditional optimal dispatch method can not coordinate the economic benefits of all the stakeholders from multiple regions of the transmission network, comprehensively. Hence, this study proposes a large-scale wind-power coordinated consumption strategy based on the Nash-Q method and establishes an economic dispatch model for interconnected systems considering the uncertainty of wind power, with optimal wind- power consumption as the objective for redistributing the shared benefits between regions. Initially, based on the equivalent cost of the interests of stakeholders from different regions, the state decision models are respectively constructed, and the noncooperative game Nash equilibrium model is established. The Q-learning algorithm is then introduced for high-dimension decision variables in the game model, and the dispatch solution methods for interconnected systems are presented, integrating the noncooperative game Nash equilibrium and Q-learning algorithm. Finally, the proposed method is verified through the modified IEEE 39-bus interconnection system, and it is established that this method achieves reasonable distribution of interests between regions and promotes large-scale consumption of wind power." @default.
• W3082265624 created "2020-09-08" @default.
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• W3082265624 date "2020-06-01" @default.
• W3082265624 modified "2023-10-16" @default.
• W3082265624 title "Nash-Q learning-based collaborative dispatch strategy for interconnected power systems" @default.
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• W3082265624 doi "https://doi.org/10.1016/j.gloei.2020.07.004" @default.
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