A Novel Data-driven Excitation Control for the MPPT of Wound Rotor Synchronous Generator based Wind Turbine

Research output: Chapter in Book/Conference paperConference paperpeer-review

2 Citations (Scopus)

Abstract

This paper proposes an integral reinforcement learning (IRL)-based excitation control for the maximum power point tracking (MPPT) of wound rotor synchronous generator (WRSG)-based wind turbines. The proposed method produces superior dynamic performance over the conventional wind turbine MPPT excitation control in the presence of wind speed variations and grid disturbances. Moreover, its data-driven nature makes the proposed method independent of the system mathematical model, indicating very strong parameter robustness. Additionally, the proposed method possesses a very low computational complexity, which is desirable for real-time applications. The effectiveness of the proposed algorithm is verified by simulation results.

Original languageEnglish
Title of host publicationProceedings of 2021 31st Australasian Universities Power Engineering Conference, AUPEC 2021
EditorsSumedha Rajakaruna, Ahmed Abu Siada, Ho Ching Iu, Arindam Ghosh, Tyrone Fernando
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)9781665434515
DOIs
Publication statusPublished - 2021
Event31st Australasian Universities Power Engineering Conference, AUPEC 2021 - Virtual, Online, Australia
Duration: 26 Sept 202130 Sept 2021

Publication series

NameProceedings of 2021 31st Australasian Universities Power Engineering Conference, AUPEC 2021

Conference

Conference31st Australasian Universities Power Engineering Conference, AUPEC 2021
Country/TerritoryAustralia
CityVirtual, Online
Period26/09/2130/09/21

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