基于多主体博弈和强化学习的微电网群与配电网协调优化调度方法OA北大核心CSTPCD

With the promotion of the"coal to electricity"project,the rural weak distribution networks may face the prob-lems such as line congestion due to the increase in heating loads,the long payback period of power grid investment as well as low utilization rate of power grid assets during the non-heat-ing season in the traditional line expansion scheme.It is an ef-fective means to solve these problems that establish a mi-crogrid that has the ability of friendly interaction and demand response based on the local renewable energy resource.For that reason,a coordinated optimization method for microgrids and distribution networks based on a multi-agent game and rein-forcement learning was proposed for a practical microgrid project in Hebei Province.Each microgrid reports the optimal bidding strategy based on the intra-day rolling dispatching plan,considering the impact of the auxiliary service strategy on the future operation economy in the finite time domain;Taking minimizing the operation cost as an object,the distribution net-work determines the clearing scheme of the auxiliary service market based on the power demand of the auxiliary service and the quotation of each microgrid.Finally,The win or learn fast-policy hill-clipping(WoLF-PHC)algorithm was used to real-ize the fast solution of multi-agent game problems,and the ef-fectiveness of the proposed method was verified based on the actual case of the micro-electric network group demonstration project.