Project: Data-driven control and coordination of smart converters for sustainable power system using deep reinforcement learning
Funding source: Digital Futures and C3.ai Digital Transformation Institute
PI: Qianwen Xu, KTH , [email protected]
co-PI: Sindri Magnússon, Stockholm University
co-PI: Robert Pilawa-Podgurski, UC Berkeley
Researcher: Mengfan Zhang, KTH, [email protected]
Code is for the paper:
M. Zhang, G. Guo, S. Magnússon, R. C. N. Pilawa-Podgurski and Q. Xu*, "Data Driven Decentralized Control of Inverter Based Renewable Energy Sources Using Safe Guaranteed Multi-Agent Deep Reinforcement Learning," in IEEE Transactions on Sustainable Energy, vol. 15, no. 2, pp. 1288-1299, April 2024 https://ieeexplore.ieee.org/abstract/document/10354415
Other relevant works:
M. Zhang, G. Guo, T. Zhao, Q. Xu*, DNN Assisted Projection based Deep Reinforcement Learning for Safe Control of Distribution Grids, in IEEE Transactions on Power Systems, 2023, doi: 10.1109/TPWRS.2023.3336614 https://ieeexplore.ieee.org/abstract/document/10334044
G. Guo, M. Zhang, Y. Gong, Q. Xu*, Safe multi-agent deep reinforcement learning for real-time decentralized control of inverter based renewable energy resources considering communication delay, Applied Energy, 2023, Volume 349, 2023 https://www.sciencedirect.com/science/article/pii/S0306261923010127