智能电网下支持充放电策略的电动汽车配送路径优化

Distribution Path Optimization of Electric Vehicles Considering Charging and Discharging Strategy in Smart Grid

针对越来越多的企业应用电动汽车进行城市物资配送的现象,提出了在智能电网下支持智能充电策略的带时间窗的电动汽车配送优化方法。在智能电网中,电动汽车可以通过车辆接入电网(V2G)进行充电或放电决策。V2G模式为电动汽车提供了更灵活的运作方式,提高电动汽车的利用率,降低充电成本。基于充放电策略和车辆路径问题,建立了非线性整数规划模型,考虑了电动汽车充放电决策,提出了一种改进的遗传算法。最后设计25组算例以验证模型和算法的可行性。仿真结果表明:与遗传算法相比,改进的遗传算法迭代效率更高,最优解质量相较于遗传算法提升了47%。

In view of the phenomenon that more and more companies use electric vehicles(EVs)to distribute cargo in urban areas,this paper presented an optimized EV distribution method with the time window by considering the intelligent charging strategy in the smart grid.The EVs can either charge or discharge when connecting to the smart grid through the vehicle to grid(V2G)system.The V2G mode provides a more flexible way for EVs to operate.It can help EVs to increase efficiency and lower the cost at the same time.Based on the recharge and vehicle routing problem,this paper proposed a nonlinear integer programming model,considered the charging and discharging decisions of EVs,and proposed an improved genetic algorithm.Finally,25 cases were designed to verify the feasibility of the algorithm.The simulation result shows that the iterative efficiency of the improved genetic algorithm(GA)is higher than other algorithms and the quality of the optimal solution is improved by 47%.