A Novel Adaptive Model Predictive Control Strategy of Solid Oxide Fuel Cell in Power Systems

Yulin Liu, Tat Kei Chau, Xinan Zhang, Herbert Iu, Tyrone Fernando, Ran Li, Yingjie Hu

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

2 Citations (Scopus)

Abstract

A new adaptive model predictive control (AMPC) is proposed in this paper to enhance the performance of solid oxide fuel cell (SOFC) in complex power systems. Compared to the existing methods, such as the PI control and conventional model predictive control, the proposed algorithm produces better tracking performances and overcomes the problem of model dependence. The effectiveness of the proposed algorithm under power grid fault and system parameter variations are 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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