Application of Expected Sarsa-Learning for Load Frequency Control of Multi-Area Power System
| dc.contributor.author | Muduli, R. | |
| dc.contributor.author | Jena, D. | |
| dc.contributor.author | Moger, T. | |
| dc.date.accessioned | 2026-02-06T06:34:48Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | This 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.citation | 5th International Conference on Energy, Power, and Environment: Towards Flexible Green Energy Technologies, ICEPE 2023, 2023, Vol., , p. - | |
| dc.identifier.uri | https://doi.org/10.1109/ICEPE57949.2023.10201593 | |
| dc.identifier.uri | https://idr.nitk.ac.in/handle/123456789/29475 | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.subject | DFIG wind power generation | |
| dc.subject | Load frequency control | |
| dc.subject | Reinforcement learning | |
| dc.title | Application of Expected Sarsa-Learning for Load Frequency Control of Multi-Area Power System |
