计及动态电价的电动汽车充放电优化调度

Optimal Scheduling of Electric Vehicle Charging and Discharging with Dynamic Electricity Price

针对传统分时电价易导致负荷出现新的尖峰和不能随实际电动汽车入网动态调整的问题,提出基于动态电价的电动汽车充电站有序充放电控制方法。考虑部分电动汽车电池电量回馈电网的能力,将电动汽车的充放电价与充放电状态及功率作为决策变量,构建以最大化充电站收益和最小化充电站与配电网交互功率波动为目标的电动汽车充放电优化调度数学模型,并采用改进的粒子群优化算法求解该多变量、高维优化问题。运用蒙特卡洛法模拟不同数量的电动汽车充放电需求,对比分析仿真结果,所提方法能够根据电动汽车入网数量动态调整电价,提高充电站收益,减小配电网负荷的峰谷差,平抑负荷波动,实现电动汽车的有序充放电和达到服务电网的目的。

Aimed at the problem that the traditional time-of-use(TOU)electricity price is easy to cause new peak loads and it cannot be dynamically adjusted with the actual demand of grid-connected electric vehicles(EVs),a charging station control method for orderly EV charging and discharging is proposed based on dynamic electricity price.Considering the capability of some EV batteries to feed power back to power grid,the charging and discharging electricity price,charging and discharging statuses,and power of EVs are taken as decision variables,and a mathematical model for the optimal dispatching of EV charging and discharging is constructed with the objective of maximizing the revenue of charging stations and minimizing the interactive power fluctuations between the charging stations and distribution network.In addition,an improved particle swarm optimization(PSO)algorithm is used to solve this multi-variable and high-dimensional optimization problem.Monte Carlo method is used to simulate the charging and discharging demand of different numbers of EVs.According to the simulation results,it can be seen that the proposed method can dynamically adjust the electricity price according to the number of grid-connected EVs,increase the revenue of charging stations,reduce the peak-to-valley difference of distribution network load,and suppress load fluctuations,thus realizing the orderly EV charging and discharging and serving the power grid.