Centralized Charging Strategy and Scheduling Algorithm for Electric Vehicles under a Battery Swapping Scenario
Document Type
Article
Publication Date
3-1-2016
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.
Identifier
84947969685 (Scopus)
Publication Title
IEEE Transactions on Intelligent Transportation Systems
External Full Text Location
https://doi.org/10.1109/TITS.2015.2487323
ISSN
15249050
First Page
659
Last Page
669
Issue
3
Volume
17
Grant
61005090
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Kang, Qi; Wang, Jiabao; Zhou, Mengchu; and Ammari, Ahmed Chiheb, "Centralized Charging Strategy and Scheduling Algorithm for Electric Vehicles under a Battery Swapping Scenario" (2016). Faculty Publications. 10659.
https://digitalcommons.njit.edu/fac_pubs/10659
