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Optimization of ordered charging strategy for large scale electric vehicles based on quadratic clustering
ZHANG Jie, YANG Chunyu, JU Fei, XU Xiaolong
Journal of Computer Applications    2017, 37 (10): 2978-2982.   DOI: 10.11772/j.issn.1001-9081.2017.10.2978
Abstract618)      PDF (745KB)(412)       Save
Aiming at the problem of unbalanced utilization rate distribution of charging station caused by disordered charging for a large number of electric vehicles, an orderly charging strategy for electric vehicles was proposed. Firstly, the location of the electric vehicle's charging demand was clustered, and the hierarchical clustering and quadratic division based on K-means were used to achieve the convergence of electric vehicles with similar properties. Furthermore, the optimized path to charging station was determined by Dijkstra algorithm, and by using the even distribution and the shortest charging distance of electric vehicles as objectives functions, the charging scheduling model based on electric vehicle clustering was constructed, and the genetic algorithm was used to solve the problem. The simulation results show that compared with the charging scheduling strategy without clustering of electric vehicles, the computation time of the proposed method can be reduced by more than a half for large scale vehicles, and it has higher practicability.
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