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• W4205675903 abstract "Currently, the lack of regulation ability in distribution systems causes severe limitations in the wide grid connection of high-penetration renewable distributed generation (DG). By improving the access of SOPs, it will considerably improve the economy, flexibility, and controllability of distribution system operation. A bi-level coordinated planning model of DG and soft open points (SOPs) in an active distribution network is proposed based on a complete information dynamic game to coordinate the interests and demands of DG investors, distribution companies, and electricity consumers, and flexibly adjust the power between feeders. The model's planning stage determines the sequential decision relationship from the perspective of improving the consumption of DG and providing economic value. It analyzes the dynamic game behavior and builds the planning model to determine the optimal installation sites and capacities of DG and SOPs for different stakeholders. At the optimization stage, the operation model of the distribution network is established to reduce the network loss and voltage deviation and balance the feeder load. A hybrid optimization method is used to solve the operation-planning model using the iterative search method and mixed-integer second-order cone programming. Furthermore, numerous simulations and comparisons are carried out on IEEE 33-node system, and the results show that the proposed method can not only meet the balance of interests of different stakeholders, improve the feasibility and economy of planning schemes, but also comprehensively improve the operation state of distribution system." @default.
• W4205675903 created "2022-01-26" @default.
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• W4205675903 date "2022-06-01" @default.
• W4205675903 modified "2023-10-09" @default.
• W4205675903 title "Coordinated planning of distributed generation and soft open points in active distribution network based on complete information dynamic game" @default.
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• W4205675903 doi "https://doi.org/10.1016/j.ijepes.2021.107953" @default.
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