Artificial Intelligence for Solar Photovoltaic Systems: Approaches, Methodologies, and Technologies (Explainable AI (XAI) for Engineering Applications)

This book provides a clear explanation of how to apply artificial intelligence (AI) to solve the challenges in solar photovoltaic technology. It introduces readers to new AI-based approaches and technologies that help manage and operate solar photovoltaic systems effectively. It also motivates readers to find new AI-based solutions for these challenges by providing a comprehensive collection of findings on AI techniques.

It covers important topics including solar irradiance variability, solar power forecasting, solar irradiance forecasting, maximum power point tracking, hybrid algorithms, swarm optimization, evolutionary optimization, sensor-based sun- tracking systems, single-axis and dual-axis sun-tracking systems, smart metering, frequency regulation using AI, emerging multilevel inverter topologies, and voltage and reactive power control using AI.

This book is useful for senior undergraduate students, graduate students, and academic researchers in areas such as electrical engineering, electronics and communication engineering, computer science, and renewable energy.