Optimal placement of charging infrastructures for large-scale integration of pure electric vehicles into grid. Xu, H., Miao, S., Zhang, C., & Shi, D. International Journal of Electrical Power & Energy Systems, 53:159-165, 12, 2013.
Website abstract bibtex The optimal placement of charging infrastructures owns fundamental importance to the popularization of pure electric vehicles (PEVs). This paper focuses on the optimal configuration of centralized charging stations (CCSs) under the condition of large-scale integration of PEVs into grid. A mathematical model to formulate the optimal CCS placement problem is firstly established. Then the distribution discipline of CCSs in the optimum CCS configuration with minimum total transportation distance (TTD) is shed light on according to the mathematical model, and it in turn helps to identify the candidate CCS locations which turn out to be discrete, finite, fit for numerical calculation and reliable. Finally a further optimization model within the searching space of these candidate CCS locations is proposed to identify the optimum CCS configuration, and solved by a modified binary particle swarm optimization (BPSO) based on Taboo mechanism (TM). The resultant optimization method, named TM-BPSO, can make up the defect of premature convergence of the original BPSO to a certain extent. A large number of numerical examples verify the correctness of the proposed strategy and the applicability of the modified BPSO in this study.
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title = {Optimal placement of charging infrastructures for large-scale integration of pure electric vehicles into grid},
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abstract = {The optimal placement of charging infrastructures owns fundamental importance to the popularization of pure electric vehicles (PEVs). This paper focuses on the optimal configuration of centralized charging stations (CCSs) under the condition of large-scale integration of PEVs into grid. A mathematical model to formulate the optimal CCS placement problem is firstly established. Then the distribution discipline of CCSs in the optimum CCS configuration with minimum total transportation distance (TTD) is shed light on according to the mathematical model, and it in turn helps to identify the candidate CCS locations which turn out to be discrete, finite, fit for numerical calculation and reliable. Finally a further optimization model within the searching space of these candidate CCS locations is proposed to identify the optimum CCS configuration, and solved by a modified binary particle swarm optimization (BPSO) based on Taboo mechanism (TM). The resultant optimization method, named TM-BPSO, can make up the defect of premature convergence of the original BPSO to a certain extent. A large number of numerical examples verify the correctness of the proposed strategy and the applicability of the modified BPSO in this study.},
bibtype = {article},
author = {Xu, Hao and Miao, Shihong and Zhang, Chunyong and Shi, Dongyuan},
journal = {International Journal of Electrical Power & Energy Systems}
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