Jan 11, 2022 · In this work, a data-driven decentralized secondary control scheme is proposed for multiple heterogeneous battery energy storage systems (BESSs).
The authors in [64] propose a CNN-based multi-agent deep reinforcement learning algorithm for secondary frequency control and state of charge balancing in ...
In this work, a data-driven decentralized secondary control scheme is proposed for multiple heterogeneous battery energy storage systems (BESSs). The proposed ...
2018. Multi-agent reinforcement learning for decentralized resilient secondary control of energy storage systems against DoS attacks. P Chen, S Liu, B Chen, L ...
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Yu, “Multi-Agent Reinforcement Learning for Decentralized Resilient Secondary Control of Energy Storage Systems Against DoS Attacks”. Link to abstract: http ...
Cyberwheel is a Reinforcement Learning (RL) simulation environment built for training and evaluating autonomous cyber defense models on simulated networks. It ...
Multi-Agent Reinforcement Learning for Decentralized Resilient Secondary Control of Energy Storage Systems Against DoS Attacks IEEE Transactions on Smart ...
Dec 1, 2023 · The review meticulously examines the inherent challenges and limitations entailed in integrating DRL into power and energy system resilience, ...
The present article proposes an intelligent secondary controller for islanded microgrids using the Deep Deterministic Policy Gradient (DDPG).
We presented a system that uses intelligent agents embedded in machines to determine which procedures are most critical and how they should be distributed.