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- W2292607291 abstract "Centralized charging of electric vehicles (EVs) based on battery swapping is a promising strategy for their large-scale utilization in power systems. The most outstanding feature of this strategy is that EV batteries can be replaced within a short time and can be charged during off-peak periods or on low electric price and scheduled in any battery swap station. This paper proposes a novel centralized charging strategy of EVs under the battery swapping scenario by considering optimal charging priority and charging location (station or bus node in a power system) based on spot electric price. In this strategy, a population-based heuristic approach is designed to minimize total charging cost, as well as to reduce power loss and voltage deviation of power networks. We introduce a dynamic crossover and adaptive mutation strategy into a hybrid algorithm of particle swarm optimization and genetic algorithm. The resulting algorithm and several others are executed on an IEEE 30-bus test system, and the results suggest that the proposed one is effective and promising for optimal EV centralized charging." @default.
- W2292607291 created "2016-06-24" @default.
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- W2292607291 date "2016-03-01" @default.
- W2292607291 modified "2023-10-17" @default.
- W2292607291 title "Centralized Charging Strategy and Scheduling Algorithm for Electric Vehicles Under a Battery Swapping Scenario" @default.
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- W2292607291 doi "https://doi.org/10.1109/tits.2015.2487323" @default.
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