Adaptive optimization method of distribution network in new energy system
In order to solve the problem of high network loss of distribution network in new energy system,an adaptive optimization method of distribution network in new energy system based on deep reinforcement learning is studied.Three constraints,including line current and node voltage constraints,distributed gen-eration output constraints and power flow constraints are set,and the objective function of adaptive optimiza-tion of distribution network of new energy system is established.The Markov decision model is used to sim-plify the solution process of the adaptive optimization objective function of the distribution network of the new energy system,and the depth deterministic strategy gradient algorithm is selected to solve the trans-formed adaptive optimization objective function to complete the adaptive optimization of the distribution net-work of the new energy system.The experiment results show that this method can reduce the equipment op-eration cost and operation network loss of the distribution network of new energy system.
deep reinforcement learningnew energy systemdistribution networkadaptiveobjective function