寒区电动公交充电站选址及定容规划研究

Low-temperature environments in cold regions can lead to a decrease in the travel ranges of electric buses (EB), which affects the service area and planning of charging facilities. In order to improve the low-temperature adaptability of EB charging stations in cold regions, a location algorithm and capacity planning model for EB charging stations are proposed. Firstly, in the charging station location problem, the gradual coverage service radius of the charging station was constructed and an improved affinity propagation (AP) clustering algorithm was used to determine the charging station location. Based on the algorithm clustering centers, a Voronoi diagram of the charging stations was constructed to divide the charging clusters. In the capacity planning problem, a low-temperature capacity attenuation model for power batteries was constructed to determine the charging demand for EBs in cold regions. Based on the truncated queue theory model with limited capacity, the constraints associated with effective service intensity, denial of service rate, and charging satisfaction of charging stations were formulated. By introducing cost balancing coefficients, a charging station capacity planning model in cold regions was established to minimize the whole social cost within the planning period. A genetic algorithm (GA) was designed for the solution. Finally, the Harbin urban area is taken as an example to conduct the numerical study. The results obtain nine locations with charging clusters for charging stations as well as the number of charging facilities and the costs for each charging station. Based on the sensitivity analysis of environmental temperature and the cost balancing coefficients, the results show that the low-temperature environment in cold regions has a significant impact on the number of chargers and various costs of charging stations. Reasonably balancing the interests of charging stations and EBs can improve the satisfaction of charging service and reduce overall social costs.