Research on standardized optimization and intelligent decision-making of power dispatching operation based on reinforcement learning

With the increasing complexity of power system and the increasing proportion of new energy, power dispatching optimization has become an important task to ensure the stable operation and economy of the system. Based on the reinforcement learning theory, the standardized optimization and intelligent decision-making method for power dispatching is studied in this paper. Firstly, the basic principle of reinforcement learning and Markov decision process are summarized, and the application potential of reinforcement learning in power system dispatching is analyzed. Secondly, a power dispatching optimization model based on deep reinforcement learning is proposed, and the TD3 algorithm is combined to optimize the specific dispatching strategy. Finally, through experimental analysis, the impact of flexible resources on both sides of the source and load on the economy of power grid dispatching and new energy consumption is demonstrated.