基于动态分时电价的含电动汽车电网无功优化策略

Reactive Power Optimization Strategy of Power Grid with Electric Vehicles Based on Dynamic Time-of-use Tariffs

电动汽车大规模无序充电会导致电压下降、网损增加、变压器寿命下降等问题,传统无功补偿设备往往灵活性较差,不能主动适应电动汽车带来的随机性、波动性。因此,提出了一种基于动态分时电价的含电动汽车电网无功优化策略,该策略首先根据预测无功负荷值制定动态分时电价,结合消费者心理学原理量化车主对电价刺激的响应,通过改变充电装置的运行模式,使处于占位期的车辆配合无功补偿元件共同协调参与无功优化,最后构建以减小电压偏差、降低网损为目标的无功优化模型,并采用二阶锥混合整数规划法进行求解。算例通过蒙特卡洛舍选抽样法模拟用户出行及充电需求,在电动汽车无序充电及有序充电模式下分别求解无功优化问题。仿真结果验证了所提方法能够在减小电动汽车接入节点的电压偏差、降低网损的同时,减轻传统无功补偿设备的运行压力。

Large scale disorderly charging of electric vehicles will cause voltage sag,increase of network loss,transformer life reduction and other problems.Traditional reactive power compensation equipment is often less flexible,and cannot actively adapt to the randomness and volatility of electric vehicles.This paper proposes a reactive power optimization strategy based on dynamic time-of-use(TOU)tariffs for power grid with electric vehicles.With the strategy we first formulated dynamic TOU tariffs according to the predicted reactive load and quantified the response of vehicle owners to the stimulation of electricity price based on the principle of consumer psychology.Then we changed the operation mode of the charging device to allow the vehicles in the occupying period to cooperate with the reactive power compensation elements to participate in the reactive power optimization.Finally,a reactive power optimization model with the goal of reducing voltage deviation and network loss is constructed,and the second-order cone mixed integer programming method was used to solve the model.In the example,the Monte Carlo sampling method was used to simulate the traveling and charging demand of users,and the reactive power optimization problems in the uncoordinated and coordinated charging modes were solved respectively.The simulation results show that the proposed method can not only reduce the voltage deviation of EV access node and the network loss,but also relieve the operating pressure of traditional reactive power compensation equipment.