Muduli, R.Jena, D.Moger, T.2026-02-0620235th International Conference on Energy, Power, and Environment: Towards Flexible Green Energy Technologies, ICEPE 2023, 2023, Vol., , p. -https://doi.org/10.1109/ICEPE57949.2023.10201593https://idr.nitk.ac.in/handle/123456789/29475This 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.DFIG wind power generationLoad frequency controlReinforcement learning