Spatial deployment optimisation for public charging stations with coverage equilibrium

In recent years, electric vehicles have developed rapidly, leading to a lack of charging facilities. In this paper, a method using spatial data such as roads, population and points of interest was proposed to identify areas with low coverage and low match of public charging stations (PCSs). Then, a modified maximal coverage location problem (MCLP) was used to install PCSs in these relatively mismatched areas. The lower the match, the higher the priority for PCS installation. To test this method, an area within the second ring road of Changsha, China, was selected as the study area. The areas with low coverage and low match were effectively extracted. A proportion of 85.3% of the low match grids were covered by constructing 100 new PCSs, and the average coverage and average match in these grids was increased by 145% and 73%, respectively. Compared to the classical MCLP, this method achieved a 7% and 10% higher coverage ratio and match ratio in the study area. This study analyses the relationship between supply and demand in charging and introduces this relationship into MCLP. This technical framework can offer a new perspective on facility sitting and can be simple and practical.