Название: Applied Soft Computing and Embedded System Applications in Solar Energy (Mathematical Engineering, Manufacturing, and Management Sciences)
Автор: Rupendra Kumar Pachauri (Editor), Jitendra Kumar Pandey (Editor), Abhishek Sharmu (Editor), Om Prakash Nautiyal (Editor), Mangey Ram (Editor)
Издательство: CRC Press
Год: 2021
Формат: True PDF
Страниц: 254
Размер: 10 Mb
Язык: English

Applied Soft Computing and Embedded System Applications in Solar Energy 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 photovoltaic (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 fields of science and engineering. Soft computing methods implemented to energy-related problems regularly face data-driven issues 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 microgrid and smart grid projects (both renewable and non-renewable generations), 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, microgrids, and smart grid projects.
Examines the integration of hardware with stand-alone PV panels and real-time monitoring of factors affecting the efficiency of the PV panels
Offers real-time implementation of soft computing and embedded system in the area of solar energy
Discusses how soft computing plays a huge role in the prediction of efficiency of stand-alone and grid-connected solar PV systems
Discusses how embedded system applications with smart monitoring can control and enhance the efficiency of stand-alone and grid-connected solar PV systems
Explores swarm intelligence techniques for solar PV parameter estimation