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- W2369933165 abstract "As the electric vehicle( EV) charging service provider,aggregator is the important coordinator between the grid and EV users. In this paper,a decentralized optimization charging model based on the Lagrangian relaxation method was formulated from the perspective of EV aggregator,which took the maximum charging profit of the aggregator as target with considering constraints: users' electricity demand,charging time and available capacity of distribution transformers,etc. The implementation mechanism and process of the decentralized optimization charging strategy were also explained.Then,M onte Carlo method was used to simulate the charging situations of EVs,and based on this simulation,the load curve,economic benefits and computational efficiency under uncoordinated charging,centralized optimization charging and decentralized optimization charging modes were compared and analyzed. The results showthat the decentralized optimization charging using the Lagrangian relaxation method can get the approximate charging profit as the centralized optimization charging and the decentralized method possesses higher computing efficiency,so it is suitable for actual application." @default.
- W2369933165 created "2016-06-24" @default.
- W2369933165 creator A5081886519 @default.
- W2369933165 date "2015-01-01" @default.
- W2369933165 modified "2023-09-25" @default.
- W2369933165 title "Decentralized Optimization Charging Strategy Based on Lagrangian Relaxation Method" @default.
- W2369933165 hasPublicationYear "2015" @default.
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