Because of the fluctuation and randomness of power supply in power system after new energy is connected,the charge and discharge of energy storage system are unbalanced.In order to solve this problem,this paper proposes an adaptive planning method for energy storage capacity of power system with new energy access.On the one hand,taking the satisfaction degree of energy storage output and the optimal replacement times as the objective function,a planning model of energy storage capacity of power system with new energy access is constructed.On the other hand,Deep Reinforcement Learning(DRL)algorithm is introduced to solve the model,and the best energy storage capacity planning scheme is sought through automatic learning,so as to realize the adaptive planning of energy storage capacity of power system.The experimental results show that the fluctuation of energy storage capacity of power system can be controlled within a suitable range by using the method designed in this paper,which is conducive to prolonging the energy storage life.
new energy accesselectric power systemenergy storage capacityadaptive planning
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