Intelligent control of a wind turbine based on reinforcement learning
Advanced controllers of modern wind turbines can help increase energy capture efficiency and reduce structural loading. However, to fulfill the modern wind turbine control demands with contradicting requirements (efficiency and reliability), innovative control methods that can handle multi-objective problems are inevitable. In this paper, we propose adaptive control techniques, which trying to extract the stochastic property of wind speed using a trained reinforcement learning (RL) agent and then apply their obtained optimal policy to the wind turbine adaptive control design. This paper includes the results of tests of the developed torque controller and a multi-input-multi-output (MIMO)-based controller using advanced RL algorithms. © 2019 IEEE.
Библиографическая ссылка Tomin N., Kurbatsky V., Guliyev H. Intelligent control of a wind turbine based on reinforcement learning // 2019 16th Conference on Electrical Machines, Drives and Power Systems, ELMA 2019 - Proceedings. ID: 8771645. 2019. ISBN (print): 9781728114132. DOI: 10.1109/ELMA.2019.8771645
Проиндексировано: WOS
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