Zhang, Y; Fei, M; Du, D; Hu, Y; (2025) Resilient Secondary Frequency Control in Distributed Renewable Energy Microgrids Under Cyber Attacks: A Double Replay Q-Learning Approach. IEEE Transactions on Smart Grid 10.1109/TSG.2025.3643161. (In press).

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Abstract

This paper addresses the challenge of resilient secondary frequency control in distributed renewable energy microgrids under False Data Injection Attacks. A rigorous Lyapunov based stability analysis is conducted, and a formal theorem is established that quantifies the maximum tolerable attack intensity under both actuator and sensor side intrusions. This theoretical tolerance boundary provides a principled and interpretable threshold for real time attack detection and secure control activation. Building upon this result, we propose a resilience framework that tightly integrates the derived physical safety boundary with an adaptive reinforcement learning controller. Specifically, a Double Replay Q-learning algorithm is developed, leveraging dual Q-tables and prioritized experience replay to enhance convergence speed and robustness under nonlinear REM dynamics. Simulation results conducted on both a real world experimental REM platform and a modified IEEE 9-Node test system validate the effectiveness and scalability of the proposed approach.

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