Our paper “A Deep Reinforcement Learning-based Multi-agent Framework to Enhance Power System Resilience Using Shunt Resources” is accepted by IEEE Transactions on Power Systems. In this paper, a data driven multi-agent framework based on a deep-reinforcement learning is proposed to overcome the computation and scalability concerns related to precise system models and to plan for the deployment of shunts for power system resilience enhancement
Paper on Power System Resilience Enhancement through Multi-agent Deep Reinforcement Learning is accepted by IEEE Trans. Power Systems.
