Installation optimization for charging stations of electric vehicle considering intelligent level and power size

Consumers’ range anxiety and subpar charging experiences have led to increased demand for a more extensive network of charging stations and intelligent charging management. However, the relevant studies on the investment behavior analysis of intelligent charging stations and the corresponding incentive policies are still limited. This paper applies a Stackelberg game method to explore the installation optimization problem between the government and an investor in the intelligent charging station market. Charging prices, intelligent level and power size of charging stations are considered as influencing factors that affect consumers’ comfort and economic costs. The government and an investor are modeled to make optimal investment decisions and the optimal incentive choices according to the consumers’ responses. The results show that the optimal operation subsidy is significantly more effective in supporting the intelligent and power upgrades of charging stations compared to the optimal construction subsidies. But the corresponding optimal operation subsidy level is significantly higher than that of construction subsidies. The determination of optimal government subsidy policies needs to meet specific threshold conditions. High consumer basic demand and environment benefits are found to encourage government subsidies, whereas high charging service costs of investor may hinder the government from offering subsidy policies. These findings are highly valuable for governments and investors in shaping the intelligent charging station market.