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• W4322711059 abstract "Distributed generation and electric vehicle accessed to the distribution network can reduce carbon emissions, but it will bring new challenges to optimize siting and sizing. This paper obtains a typical scenario set of wind-photovoltaic-load by the improved K-means clustering algorithm. A spatial-temporal distribution model of electric vehicle charging load is established by fusing multi-source information based on the smart charging strategy of electric vehicles. A distribution model of distributed generation and electric vehicle charging station based on source-load correlation is established through the orderly management of electric vehicle charging. A joint distribution strategy is obtained to meet the optimal goal of comprehensive benefit, load fluctuations and time-consuming cost. This model is solved by the improved particle swarm algorithm and Voronoi diagram. The results show that the optimization model can meet the planning objectives and improve the quality of voltage, which verifies the feasibility and effectiveness of the proposed model." @default.
• W4322711059 created "2023-03-02" @default.
• W4322711059 creator A5009250432 @default.
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• W4322711059 date "2022-11-18" @default.
• W4322711059 modified "2023-09-23" @default.
• W4322711059 title "Joint Optimal Allocation of DG and EV Charging Stations Based on Source-Load Correlation" @default.
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• W4322711059 doi "https://doi.org/10.1109/icpea56363.2022.10052226" @default.
• W4322711059 hasPublicationYear "2022" @default.
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