Authors: Jiajun Duan, Yan Zan, Tu Lan, Di Shi, Ruisheng Diao, Siqi Wang, Desong Bian, Janet Zhang
NB: This baseline only works for IEEE 14 bus environment. For other environments, corresponding modifications should be made to the agent.
S. Wang, J. Duan, D. Shi, C. Xu, H. Li, R. Diao, and Z. Wang, "A Data-driven Multi-agent Autonomous Voltage Control Framework Using Deep Reinforcement Learning," IEEE Transactions on Power Systems, Accepted, 2020.
J. Duan, D. Shi, R. Diao, H. Li, Z. Wang, B. Zhang, D. Bian, and Z. Yi, "Deep-Reinforcement-Learning-Based Autonomous Voltage Control for Power Grid Operations," IEEE Transactions on Power Systems, Accepted, 2019.
X. Wang, Y. Wang, D. Shi, J. Wang, and Z. Wang, "Two-stage WECC Composite Load Modeling: A Double Deep Q-Learning Networks Approach," IEEE Transactions on Smart Grid, Accepted, 2020.
T. Lan, J. Duan, B. Zhang, D. Shi, Z. Wang, R. Diao, and X. Zhang, “AI-Based Autonomous Line Flow Control via Topology Adjustment for Maximizing Time-Series ATCs,” IEEE PES General Meeting, Montreal, Canada, Accepted, 2020.
J. Duan, H. Li, X. Zhang, R. Diao, B. Zhang, D. Shi, X. Lu, Z. Wang, and S. Wang, "A Deep Reinforcement Learning Based Approach for Optimal Active Power Dispatch," IEEE Sustainable Power and Energy Conference, Beijing, China, 2019.
Z. Xu, Y. Zan, C. Xu, J. Li, D. Shi, Z. Wang, B. Zhang, and J. Duan, "Accelerated DRL Agent for Autonomous Voltage Control Using Asynchronous Advantage Actor-critic," IEEE PES General Meeting, Montreal, Canada, Accepted, 2020.
R. Diao, Z. Wang, D. Shi, Q. Chang, J. Duan, and X. Zhang, "Autonomous Voltage Control for Grid Operation Using Deep Reinforcement Learning," IEEE PES General Meeting, Atlanta, GA, USA, 2019.