Reinforcement-learning-based damping control scheme of a PV plant in wide-area measurement system
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00202-022-01615-3.pdf
Reference29 articles.
1. Hashmy Y, Yu Z, Shi D, Weng Y (2020) Wide-area measurement system-based low frequency oscillation damping control through reinforcement learning. IEEE Trans Smart Grid 11(6):5072–5083. https://doi.org/10.1109/TSG.2020.3008364
2. Abdulrahman I, Belkacemi R, Radman G (2021) Power oscillations damping using wide-area-based solar plant considering adaptive time-delay compensation. Springer J Energy Syst 12:459–489
3. Cao D et al (2020) Reinforcement learning and its applications in modern power and energy systems: a review. J Modern Power Syst Clean Energy 8(6):1029–1042. https://doi.org/10.35833/MPCE.2020.000552
4. Sewak M (2019) Deep reinforcement learning frontiers of artificial intelligence. Springer Nature Pte Ltd, Singapore
5. Dong H et al (2020) Deep reinforcement learning fundamentals research and applications. Springer Nature Pte Ltd, Springer
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1. Design of a resilient wide-area damping controller using time delays;Electrical Engineering;2024-07-05
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