Optimal operation strategy of microgrid based on deep reinforcement learning

The uncertainty of wind power，photovoltaic and load brings challenges to the formulation of opera⁃ tion strategy for microgrid with high proportion of renewable energy，and the development of artificial intelli⁃ gence technology provides a new idea for solving the operation optimization problem of microgrid. Based on the reinforcement learning framework，the operation problem of microgrid is transformed into a Markov decision process，and an online scheduling method of microgrid based on deep reinforcement learning is proposed，which takes the maximum economic benefit of microgrid and residents’satisfaction as its object. In order to effectively use the experience in the training process of deep reinforcement learning，a PES-DDPG（Priority Experience Storage Deep Deterministic Policy Gradient） algorithm is designed to learn the optimal scheduling strategy of microgrid for different periods under each type of environment. Case results show that PES-DDPG algorithm can provide effective scheduling strategy for microgrid and realize real-time optimization of microgrid. © 2022 Electric Power Automation Equipment Press. All rights reserved.