公开(公告)号：US20240330396A1

公开(公告)日：2024-10-03

申请号：US18550287

申请日：2023-03-14

Applicant: SOUTHEAST UNIVERSITY

Inventor： Yujian YE ,  Peiling CHEN

IPC: G06F17/11

CPC classification number: G06F17/11

Abstract: A microgrid spatial-temporal perception energy management method based on safe deep reinforcement learning includes: transforming an energy management problem of a microgrid (MG) into a constrained Markov decision process (CMDP), where an agent is an energy management agent of the MG; and solving the CMDP by using a safe deep reinforcement learning method, including: 1) building a feature extraction network combining an edge conditioned convolutional (ECC) network and a long short-term memory (LSTM) network to extract spatial and temporal features in a spatial-temporal operating status of the MG; and 2) endowing the agent with abilities to learn policy value and security simultaneously by using an interior-point policy optimization (IPO) algorithm. The microgrid spatial-temporal perception energy management method based on safe deep reinforcement learning enhances perception on the spatial-temporal operating status of the MG, safeguards the secure operation of the distribution network, and achieves superior energy management policy cost efficiency.