Safe Reinforcement Learning-Based Transient Stability Control for Islanded Microgrids With Topology Reconfiguration

Journal Article · Wed May 14 04:00:00 EDT 2025 · IEEE Transactions on Smart Grid

DOI:https://doi.org/10.1109/TSG.2025.3569696· OSTI ID:2574769

Su, Tong ^[1]; Zhao, Junbo ^[1]; Yao, Yiyun ^[2]; Selim, Alaa ^[1]; Ding, Fei ^[2]

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1. University of Connecticut
2. National Renewable Energy Lab., Golden, CO (United States)

This paper proposes a safe reinforcement learning (RL)-based transient stability emergency control (TSEC) method for islanded microgrids. RL requires extensive interaction with the environment to learn control strategies, hence, a data-driven approach is used as a substitute for time-consuming time-domain simulation calculations. Deep sigma point processes (DSPP), which is a Gaussian process model, is utilized to predict the normal distribution of transient stability of microgrids and to construct a transient stability chance constraint. Reward-constrained policy optimization (RCPO) can simultaneously achieve objective prediction, policy learning, and constraint cost coefficient update across multiple timescales. RCPO interacts with the DSPP-based microgrid environment through a multi-process parallel manner, greatly increasing the training speed. Case studies on a real islanded microgrid demonstrate that the proposed method can efficiently and quickly obtain the optimal emergency control strategy while adhering to all hard constraints.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 2574769
• Report Number(s): NREL/JA-5D00-93140
• Journal Information: IEEE Transactions on Smart Grid, Journal Name: IEEE Transactions on Smart Grid Journal Issue: 4 Vol. 16
• Country of Publication: United States
• Language: English

Related Subjects

14 SOLAR ENERGY
24 POWER TRANSMISSION AND DISTRIBUTION
97 MATHEMATICS AND COMPUTING
PVs
chance constraint
microgrid
safe reinforcement learning
stability control
topology change