CAJ | 학술논문

采用电池租赁和建立集中型充电站是电动汽车产业具有竞争力的发展模式。根据规划区各类型电动汽车日行驶距离概率分布，建立了电动汽车日换电需求模型。以此为基础，将集中型充电站的规划与配电网调度相结合，建立了考虑削峰填谷作用的集中型充电站选址定容二层规划模型。利用改进遗传算法与自适应粒子群相结合的混合智能算法进行求解，并将加权伏罗诺伊图应用于集中型充电站服务区域的划分，实现了集中型充电站负载率的均衡。通过仿真算例验证了所提模型和方法的有效性和可行性。
채용전지조임화건립집중형충전참시전동기차산업구유경쟁력적발전모식。근거규화구각류형전동기차일행사거리개솔분포，건립료전동기차일환전수구모형。이차위기출，장집중형충전참적규화여배전망조도상결합，건립료고필삭봉전곡작용적집중형충전참선지정용이층규화모형。이용개진유전산법여자괄응입자군상결합적혼합지능산법진행구해，병장가권복라낙이도응용우집중형충전참복무구역적화분，실현료집중형충전참부재솔적균형。통과방진산례험증료소제모형화방법적유효성화가행성。
Leasing batteries and establishing centralized charging stations are the future competitive development orientations in electric vehicle industry. Based on driving distance probability distribution of various electric vehicles obtained by statistical analysis, an uncertainty model of electric vehicle battery replacement demand is established. Considering the investment of centralized charging stations and lines, network loss and load shifting, a planning model for centralized charging stations is put forward. The hybrid intelligent optimization method, which combines the improved genetic algorithm with the self-adaptive particle swarm algorithm, is used to solve the above two layer programming models. The service area is divided by the weighted Voronoi diagram in order to balance the load rates of centralized charging stations. The simulation results show that the proposed model and method are effective and feasible for centralized charging station planning.