Multi-Scenario and Multi-Objective Collaborative Optimization of Distribution Network Considering Electric Vehicles and Mobile Energy Storage Systems

Abstract

Due to the short-term large-scale access of renewable energy and residential electric vehicles in residential communities, the voltage limit in the distribution network will be exceeded, and the quality of power supply will be seriously reduced. Therefore, this paper introduces the mobile energy storage system (MESS), which effectively solves the problem of overvoltage limit caused by the large number of distributed power sources and household electric vehicles in the distribution network. This paper proposes an optimal scheduling model for distribution network based on mobile energy storage system. First, the space-time energy transfer model of mobile energy storage is established, and the transfer cost of MESS and the income of peak shaving and valley filling are considered. According to daily driving data of household electric vehicle (EV), a prosumer group electric vehicle charging and discharging model is established; After that, by establishing a target model for maximizing MESS operating income and penalizing voltage overshoot under different scenarios such as low peak load of electric vehicles and different initial capacities of MESS, a multi-scenario multi-objective collaborative optimization model for the distribution network is established; Finally, an improved IEEE33-bus system is used to analyze the calculation example. The results of the calculation example show that the optimal scheduling model in this paper can improve the photovoltaic consumption capacity and improve the voltage limit problem, which verifies the effectiveness and economy of the scheduling model. INDEX TERMS electric vehicle (EV),mobile energy storage system (MESS), distribution network, collaborative optimization

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