摘要
从交通、环境、电力、规划、土地等6个方面界定了电动汽车充电站的选址条件,给出了基于熵权模糊物元法的充电站初步选址的技术流程,然后在初步选址的基础上建立了充电站总建设成本最低的精确选址模型,设计了精确选址模型的遗传求解算法。选取40×40平面内随机产生20个充电需求点和8个备选站点的案例,验证了电动汽车充电站分层递进式选址方法的科学性和可行性。
The conditions of site selection of electric vehicle charging stations were defined using 6 factors,including,but not limited to,environment,electric power,planning,and land,the technical process of the preliminary site selection of charging station was given based on the entropy weight fuzzy matter element method. The precise location model of charging stations with the lowest total construction cost was established and genetic algorithm model of precise location was designed.Finally,the rationality and feasibility of the hierarchical progressive charging station location method was tested and verified by selecting 20 charging demand points generated randomly and 8 alternative sites within a 40＊ 40 plane.
作者
任其亮
吴丽霞
靳旭刚
苏莉晓
REN Qiliang;WU Lixia;JIN Xugang;SU Lixiao(School of Traffic ~ Transportation, Chongqing Jiaotong University, Chongqing 400074, P.R.Chin)
出处
《重庆交通大学学报（自然科学版）》
CAS
北大核心
2018年第6期121-126,共6页
Journal of Chongqing Jiaotong University(Natural Science)
基金
国家社会科学基金西部项目(16XJY013)
关键词
城市交通
电动汽车
充电站选址
分层递进式
熵权模糊物元
建设成本最小化
遗传算法
urban traffic
electric vehicle
charging station location
hierarchical progressive
entropy weight fuzzy matter element
the minimize of the construction cost
genetic algorithm
