Sayed Abulanwar

Hybrid AC/DC Microgrids: Optimization, Energy Management, and Protection, a new release in the Advances in Sustainable Microgrid Technologies series, offers a comprehensive exploration of modern microgrid technologies, focusing on the integration of alternating and direct current systems. This book serves as a practical guide for foundational principles and advanced applications, addressing the complexities of design, operation, and management. By examining energy generation methods such as wind, solar, and hydrogen, the text prepares readers for real-world challenges. Detailed case studies, hands-on objectives, and worked problems foster practical learning, making this resource invaluable for students, researchers, and industry engineers invested in sustainable energy solutions. The book not only covers power management and quality control, but also delves into risk assessment and resilience strategies for microgrids. It highlights advanced modeling techniques, fault detection, and protection using both physical and artificial intelligence methods. Guidance is provided for grid protection in normal and abnormal conditions, emphasizing the need to maintain reliable energy systems amid climate change. Clear formatting, including objectives and case studies, enhances comprehension and application.

Rising shares of renewable energy are needed to stave off catastrophic climate change, but also bring about the challenge of intermittency, jeopardizing power quality. Instead of large central generation units, many distributed generators and loads need to be managed in order to integrate renewable energy with power systems. Artificial intelligence (AI) can meet this challenge with adaptive control and demand side management. When managing distributed and changing network components, AI can give control computers human-level performance, helping to solve key issues with intermittency, power quality and distributed generation and loads including EV. Use of AI for power systems has therefore become a research hotspot. This reference book systematically treats the applications of AI in power electronics and renewable energy systems. The book begins with an introduction to AI in power systems, then subsequent chapters cover the use of AI for electric machine fault diagnosis, for power electronic reliability, design, and control, in dual-active-bridge converters; AI for distribution network voltage control, signal stability control, and energy management of hybrid systems as well as for renewable energy systems with AI. The book ends with conclusions and an outlook for AI in power systems. Numerous worked examples throughout the text help readers understand the operating and controlling guidelines. Written by a team of well-known scientists and power system experts, AI for Power Electronics and Renewable Energy Systems is a valuable resource for researchers and PhD students, as well as experts in industry and utilities involved with electric power systems.