Electric Vehicle Battery Swapping Station Coordinated Charging Dispatch Method Based On Temporal And Spatial Double Dimensions

Electric vehicle (EV) with its environmental protection, energy saving and high efficiency features to replace the traditional fuel vehicles has become the inevitable trend of the development of low carbon economy. With the popularization of electric vehicle, the out-of-order random charging behavior of large-scale EV users in time and space will increase the uncertain influence factors in power grid operation and bring new challenges to power grid economic dispatch and operation control. Therefore, it is necessary to research EV coordinated charging method according to the EV charging power and energy demands characteristics to reduce the large-scale EV charging effects on the grid and improve the efficiency of charging infrastructure and the charging convenience of EV users.The dissertation focus on EV battery swapping station coordinated charging dispatch method based on temporal dimension, spatial dimension and temporal-spatial dimensions. The main works and specific researchs are summarized as follows:(1) Out-of-order random charging behaviors of large-scale EV users in time will increase power grid peak load. Based on meeting charging demand of electric vehicles and the charging load’s schedulability at the time, this paper proposed EV battery swapping station (BSS) coordinated charging temporal dispatch method from the time dimension to improve power grid load curve and reduce the charging cost of BSS. With the stochastic constraints particle swarm optimization algorithm and its improved algorithm are taken to solve coordinated charging temporal dispatch model and achieve BSS optimized daily charging plan. Simulation example based on operation data of Olympic Charging Station show that the method can make EV charge in load valley period and meet EV energy demand at the same time. Economy of BSS operation is improved and peak load is shifted.(2) The choices of electric vehicle users for charging position from their own point of view are blind and random and may increase the users’ changing cost. It is not conducive to the economic operation of power grid and BSS.In order to satisfy the user’s and BSS’s charging load space allocation requirements, this paper proposed EV battery swapping station coordinated charging spatial dispatch method from the spatial dimension to guide EV user’s charging position. Particle swarm optimization algorithm and genetic algorithm are taken to solve coordinated charging spatial dispatch model contrastively. Simulation example based on the converted actual operation data of Shenzhen charging station and campus grid100vehicles demonstration project show that the method can meet the EV user’s charging position requirements and promote the the power grid economic operation and BSS utilization rate.(3) In order to achieve EV charging behavior guidance and scheduling both in temporal and spatial double dimensions at the same time, BSS coordinated charging temporal-spatial dispatch method is proposed. The method joined temporal dispatch and spatial dispatch together on the BSS daily plan charging energy. Real-time coordinated charging spatial dispatch as temporal-spatial dispatch method’s inner loop optimization and non real-time coordinated charging temporal dispatch as temporal-spatial dispatch method’s outer loop optimization. Simulation examples based on campus grid100vehicles demonstration project demonstrate the effectiveness of the proposed method. EV charging behavior guidance and scheduling are realized from the dimensions of time and space.