Advanced model insensitive control methods for energy storage systems in microgrids

Yulin Liu

Research output: ThesisDoctoral Thesis

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Abstract

This thesis is dedicated to extensive studies on the advanced model insensitive control algorithms for energy storage systems in renewable energy source-powered microgrids. The developed algorithms are employed to eliminate the controller’s model dependence and handle uncertainties to enhance the performance and stability of energy storage systems by using adaptive dynamic programming and artificial neural networks. The algorithms proposed in this paper are not simply replacements for each other but follow the design rule of functional improvement from one algorithm to the other.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • The University of Western Australia
Supervisors/Advisors
  • Zhang, Xinan, Supervisor
  • Iu, Ho Ching, Supervisor
  • Townsend, Chris, Supervisor
  • Fernando, Tyrone, Supervisor
Award date3 May 2024
DOIs
Publication statusUnpublished - 2024

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