Artificial intelligence (AI)-based optimization of power electronic converters for improved power system stability and performance

The present review paper provides an overview of the recent advances in AI-based techniques for the design and optimization of power electronic converters. There is an increased demand on power converters in applications like renewable energy generation, microgrids, electric and hybrid vehicles, hig...

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Bibliographic Details
Published in2023 IEEE 14th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED) pp. 204 - 210
Main Authors Gros, Ioana-Cornelia, Lu, Xiaoshu, Oprea, Claudiu, Lu, Tao, Pintilie, Lucian
Format Conference Proceeding
LanguageEnglish
Published IEEE 28.08.2023
Subjects
artificial intelligence
Control systems
Maintenance engineering
Microgrids
optimization
power electronic converters
Power system dynamics
Power system stability
Reinforcement learning
renewable energy generation
Renewable energy sources
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Summary:The present review paper provides an overview of the recent advances in AI-based techniques for the design and optimization of power electronic converters. There is an increased demand on power converters in applications like renewable energy generation, microgrids, electric and hybrid vehicles, high-voltage DC power transmission etc. with focus on their design and optimization. In this context, various AI techniques are discussed, such as: machine learning, deep learning, reinforcement learning, and evolutionary algorithms, artificial neural networks, fuzzy logic control, expert systems and their applications in power electronics and electric drives. Some case studies from the literature are referred and potential benefits of AI-assisted design and optimization of power electronic converters with aspects of enhanced power system stability and performance are highlighted.
DOI:10.1109/SDEMPED54949.2023.10271490