电动汽车充放电多目标优化调度策略研究

Study on multi-objective optimization scheduling strategy of EV charging and discharging

电动汽车作为新型负荷接入电网给原有的配电网带来一系列问题,有效的控制策略可以减小电动汽车充放电对电网的影响。针对电动汽车的入网情况和现有的分时电价制度,从配电网方面考虑以最小化配电网负荷均方差与最小化系统负荷峰谷差为目标函数建立电网负荷波动的数学模型。兼顾电网和用户双方共同的利益,在用户侧方面以电动汽车用户充放电成本最低作为优化的目标函数建立多目标的电动汽车优化调度模型。基于某商用楼宇负荷进行算例仿真,采用常惯性粒子群算法进行求解。仿真结果表明,分时电价引导下的调度策略可以减小峰谷差,提高用户的经济性。增大平均电价情况下调峰效果显著,用户成本会因平均电价上浮而增高。

As a new type of load, the electric vehicle brings a series of problems to the original distribution network. The effective control strategy can reduce the impact of electric vehicle charging and discharging on the power grid. In order to minimize the load mean variance of the distribution network and minimize the peak valley difference of the system load as the objective function, a mathematical model of the power grid load fluctuation is set up from the distribution network. Taking into account the common interests of both the power grid and the users, the multi-objective optimization scheduling model of electric vehicles is established in the user side with the electric vehicle minimum cost of charging and discharging as the objective function of the optimization. Based on a commercial building load simulation example, the constant inertia particle swarm optimization algorithm is used to solve it. The simulation results show that: the dispatching strategy guided by TOU pricing can reduce the peak valley difference and improve the user's economy. With the increase of average electricity price, the effect of peak shaving is remarkable, and the user cost will increase as the average electricity price rises.