基于电动汽车激励策略的主动配电网日前优化调度

The Day-Ahead Optimization Dispatch of Active Distribution Networks Based on Electric Vehicle Incentive Strategy

为克服大规模电动汽车无序充电给配电网负荷峰谷差造成的不利影响,提出一种考虑激发电动汽车用户有序充放电响应潜力的主动配电网优化调度模型。以负荷方差、系统运行成本和用户充电成为目标,在主动配电网模型的基础上考虑电动汽车有序充放电,通过增加激励策略使电动汽车用户能够充分响应电网调度。其次,针对标准飞蛾扑火算法中收敛速度慢、迭代精度低等问题,提出一种基于tent混沌映射、自适应权重和高斯-柯西变异策略的改进飞蛾扑火算法对模型进行求解。最后,在改进的IEEE33节点系统中进行仿真分析,结果表明,所建立的模型和方法具有可行性和有效性。

To address the adverse impact of large-scaled disorderly charging of EVs on the load peak-valley difference of the distribution network,this paper proposes an optimized scheduling model for active distribution networks,considering the EV users’response potential resulting from the stimulation of orderly charging and discharging.Firstly,with load variance,system operating cost and user charging as targets,the orderly charging and discharging of electric vehicles are considered on the basis of the active distribution network model,and the incentive strategy is added to make electric vehicle users fully respond to the network scheduling.Secondly,for the problems of slow convergence speed and low iteration accuracy in the standard moth-to-flame algorithm,an improved moth-to-flame algorithm based on tent chaotic mapping,adaptive weight and Gauss-Cauchy mutation strategy is proposed to solve the model.Finally,a simulation analysis is carried out in the improved IEEE33 node system.The results show that the established model and method are feasible and effective.