考虑电动汽车与微电网参与的配电网双层协调控制策略

Bi-layer Coordinated Control Strategy of Distribution Network Considering Participation of Electric Vehicles and Microgrid

含有大规模分布式电源的微电网的大规模建设与车网互动(V2G)技术的应用导致配电网运行电压不稳定与电动汽车(EV)用户需求损失的同时,也给电力系统的调控带来了新的手段。为此,文中提出基于改进进化-深度强化学习(EDRL)的含V2G的配电网与微电网的有功功率-无功功率双层协调控制策略。首先,考虑V2G过程对EV用户需求的影响,构建了基于出行链的含V2G的配电网-微电网双层协调控制模型;其次,构建了改进EDRL算法,进一步增强了智能体的收敛能力;然后,以配电网运行信息为状态集,以各单元功率调节信号为动作集,以电压偏差、网损、用户需求损失等综合成本为奖励函数指标,完成双层协调控制的结构设计。算例结果表明,所提策略能够在保证EV用户充电需求的前提下,降低配电网电压偏差与网损。

The large-scale construction of microgrids with large-scale distributed power sources and the application of the vehicle-togrid(V2G)technology lead to the instability of the operation voltage of the distribution network and the demand loss of electric vehicle(EV)users,and also bring a new means for the regulation of the power system.Therefore,this paper proposes a bi-layer active power-reactive power coordinated control strategy based on enhanced evolutionary-deep reinforcement learning(EDRL)for distribution networks and microgrids with V2G.Firstly,considering the influence of V2G process on the demand of EV users,a bilayer coordinated control model including distribution networks and microgrids with V2G is constructed based on the travel chain.Secondly,the enhanced EDRL algorithm is constructed to further enhance the convergence ability of the agent.Then,defining the operation information of the distribution network as the state set,the power regulation signal of each unit as the action set,and the comprehensive cost such as voltage deviation,network loss and user demand loss as the reward function index,the structure design of the bi-layer coordinated control is completed.The case results show that,the proposed strategy can reduce the voltage deviation and network loss of the distribution network on the premise of meeting the charging demand of EV users.