TY - BOOK
T1 - Intelligent Fault Detection and Diagnosis Techniques for Monitoring Wind and Solar Systems
AU - Mansouri, Majdi
AU - Kouadri, Abdelmalek
AU - Hajji, Mansour
AU - Harkat, Mohamed Faouzi
AU - Nounou, Hazem N.
AU - Nounou, Mohamed N.
N1 - Publisher Copyright:
© 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - Intelligent Fault Detection and Diagnosis Techniques for Monitoring Wind and Solar Energy Systems provides innovative solutions for fault detection and diagnosis in renewable energy systems. By leveraging advanced AI-based techniques such as deep learning, multiscale representation, and statistical analysis, this book aims to enhance system reliability, performance, and cost-efficiency. Readers will gain insights into the fundamentals of FDD processes tailored for photovoltaic and wind turbine operations. The book delves into data preprocessing techniques, feature extraction and selection methods, and optimization of deep learning models. It also includes case studies and explores future directions for AI and machine learning in renewable energy, making it valuable for researchers, engineers, and policy makers.
AB - Intelligent Fault Detection and Diagnosis Techniques for Monitoring Wind and Solar Energy Systems provides innovative solutions for fault detection and diagnosis in renewable energy systems. By leveraging advanced AI-based techniques such as deep learning, multiscale representation, and statistical analysis, this book aims to enhance system reliability, performance, and cost-efficiency. Readers will gain insights into the fundamentals of FDD processes tailored for photovoltaic and wind turbine operations. The book delves into data preprocessing techniques, feature extraction and selection methods, and optimization of deep learning models. It also includes case studies and explores future directions for AI and machine learning in renewable energy, making it valuable for researchers, engineers, and policy makers.
UR - https://www.scopus.com/pages/publications/105023795194
U2 - 10.1016/C2025-0-00392-7
DO - 10.1016/C2025-0-00392-7
M3 - Book
AN - SCOPUS:105023795194
SN - 9780443450174
BT - Intelligent Fault Detection and Diagnosis Techniques for Monitoring Wind and Solar Systems
PB - Elsevier
ER -