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Stochastic Collaborative Planning of Electric Vehicle Charging Stations and Power Distribution System

The increasing prevalence of electric vehicles (EVs) calls for the effective planning of the charging infrastructure. In this study, a multi-objective, multistage collaborative planning model is proposed for the coupled EV charging station infrastructure and power distribution network. The planning model aims to minimize the investment and operation costs of the distribution system while maximize the annually captured traffic flow. The uncertainties of EV charging loads are modeled for three different types of charging stations. The FISK's stochastic traffic assignment model is utilized to model realistic traffic flows. And a new class of volume-delay functions, conical congestion functions, is employed to overcome the shortcomings of the conventional Bureau of Public Roads function. The multi-objective evolutionary algorithm based on decomposition (MOEA/D) algorithm is applied to find the nondominated solutions of the proposed collaborative planning model. Finally, simulations based on a 54-node distribution system are conducted to validate the  effectiveness of the proposed method.