【摘要】 电动私家车入网无序充放电造成电网日间负荷波动,强制干预会降低用户参与调度的积极性。针对这种情况,提出一种面向私家车的用户电网双向优化的电动汽车调度模型。通过蒙特卡洛模拟电动汽车日行驶里程,通过充放电后要完成的行驶里程获得所需的日间充放电电量,得到电动汽车充放电策略;利用改进狼群算法最小化电网峰值平均功率比和电动汽车使用成本。该模型得出充放电策略和初始荷电状态有关,并给出最佳充放电时间分布。案例分析表明,用户电网双向优化的电动汽车调度优化模型既能降低电动汽车使用成本,又能对电网进行削峰填谷。更多还原

【Abstract】 As the disordered charging and discharging of electric private cars in the grid causes the daytime load fluctuation in the grid. Forced intervention will reduce the enthusiasm of users to participate in the dispatching. Aiming at this situation, we propose an electric vehicle dispatching model for two-way optimization of the customer and grid for private cars. Using Monte Carlo simulate the daily driving mileage of electric vehicles, the daytime driving mileage was divided into two stages. By the traveled mileage after charging and discharging, the required electric quantity and the electric vehicle charging and discharging strategy was obtained. The improved grey wolf algorithm was used to minimize the peak-to-average power ratio of the grid and the user’s charge and discharge cost. The model draws the conclusion that the initial state of charge is related to the charge and discharge strategy, and gives the optimal charge and discharge time distribution. The case study shows that the two-way optimization electric vehicle dispatch optimization model can not only reduce the use cost of electric vehicles, but also cut the peaks and fill the grid.更多还原