Application of Expected Sarsa-Learning for Load Frequency Control of Multi-Area Power System

dc.contributor.authorMuduli, R.
dc.contributor.authorJena, D.
dc.contributor.authorMoger, T.
dc.date.accessioned2026-02-06T06:34:48Z
dc.date.issued2023
dc.description.abstractThis paper presents expected sarsa-Iearning algorithm-based control strategy for load frequency control of two-area power system. This algorithm comes under value- teration-based model-free reinforcement learning algorithm. The pre-learning for this algorithm is carried out on two area power system. Then the effectiveness of the proposed control strategy is evaluated on the modified two-area power system. DFIG-based wind power generation is incorporated into each area of the modified power system. The simulation study is demonstrated to analyse the performance of the proposed controller. © 2023 IEEE.
dc.identifier.citation5th International Conference on Energy, Power, and Environment: Towards Flexible Green Energy Technologies, ICEPE 2023, 2023, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/ICEPE57949.2023.10201593
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/29475
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectDFIG wind power generation
dc.subjectLoad frequency control
dc.subjectReinforcement learning
dc.titleApplication of Expected Sarsa-Learning for Load Frequency Control of Multi-Area Power System

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