Application of machine learning and artificial intelligence in design, optimization, and control of power electronics converters for renewable energy-based technologies

As a promising alternative for future energy supply, using renewable energy resources has been becoming popular worldwide at a rapid pace. It covers a wide range of applications from transportation to electricity production, and cooling and heating provision, and as a key element for such systems, power electronics converters deal with transforming the system outlet to the desirable condition. Thanks to the significant development of computer science, there has been a strong tendency toward utilization of machine learning and artificial intelligence to design, optimize, and control different systems, including the power electronics converters, and considering this point, this chapter provides an insight into using such methods for power electronics converters in renewable energy-based technologies. Initially, the importance of topic is described. Then, the main concepts, including artificial intelligence, machine learning, wireless sensor networks, and analysis of power converters, are introduced. After that, by conducting a comprehensive literature review, different applications of machine learning, artificial intelligence, and wireless sensor networks in design, optimization, and control of power electronics converters for renewable energy-based technologies are discussed in detail.