Applied Soft Computing and Embedded System Applications in Solar Energy

This book deals with energy systems and soft-computing methods from a wide range of approaches and application perspectives. The authors examine how embedded system applications can deal with the smart monitoring and controlling of stand-alone and grid connected solar PV systems for increased efficiency. Growth in the area of artificial intelligence with embedded system applications has led to a new era in computing, impacting almost all science and engineering fields. Soft-computing methods implemented to energy-related problems regularly face data-driven tasks such as problems of optimization, classification, clustering or prediction. The authors offer real time implementation of soft computing and embedded system in the area of solar energy to address the issues with micro grid and smart grid projects (both renewable and non-renewable generation), energy management and power regulation. They also discuss and examine alternative solutions for energy capacity assessment, energy efficiency systems design, as well as other specific smart grid energy system applications. The book is intended for students, professionals, and researchers in electrical and computer engineering fields, working on renewable energy resources, micro grids, and smart grid projects.