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

Abstract

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.