SOLAR PV FAULT DETECTION AND DIAGNOSIS CONCEPTS AND TECHNIQUES by Mrs. J. Jerila Dr. C. Mythili

In the rapidly evolving landscape of renewable energy, solar photovoltaic
(PV) technology stands out as a key pillar for sustainable electric power
generation. The global push towards clean energy has resulted in
unprecedented growth in the deployment of solar PV systems. However,
as these systems scale both in size and complexity, ensuring their
optimal performance and reliability remains a significant challenge.
Faults and anomalies in PV systems can drastically reduce energy yield,
increase operational costs, and shorten system lifespan. Hence, the
importance of effective fault detection and diagnosis techniques cannot
be overstated. This book, “Solar PV Fault Detection and Diagnosis:
Concepts and Techniques,” is dedicated to addressing these critical
aspects in a structured and comprehensive manner.
Over recent years, the scientific and engineering communities have made
remarkable advances in understanding the diverse nature of faults that
can occur in solar PV systems—ranging from physical and electrical
malfunctions to environmental impacts like shading and soiling. This has
spurred the development of numerous diagnostic methodologies,
leveraging classical statistical techniques, signal processing, thermal
imaging, and more recently, artificial intelligence and machine learning.
The book bridges fundamental theories with these modern approaches to
equip readers with a holistic understanding of the subject.
The scope of this work covers classification and characterization of
faults, monitoring strategies, data acquisition methods, and state-of-theart
detection algorithms. We delve into model-based and data-driven
fault diagnosis frameworks, including neural networks, support vector
machines, decision trees, and deep learning architectures tailored for PV
system condition assessment. Emphasis is also placed on practical considerations such as implementation challenges, environmental
variations, and maintenance optimization. By integrating theory with
application-oriented insights, the book aims to support researchers,
engineers, system designers, and students to develop robust, efficient,
and automated diagnostic tools for solar PV systems.
We are deeply aware that photovoltaic technology forms a cornerstone of
the transition to clean energy economies worldwide. Reliable fault
detection and diagnosis not only improve the performance and safety of
PV installations but also contribute significantly to reducing the levelized
cost of electricity (LCOE) from solar power. With this understanding, the
motivation behind this book is to provide an authoritative reference
consolidating concepts, methodologies, and best practices in the fault
management domain.
It is our belief that the readers will find this book a balanced blend of
academic rigor and practical guidance, fostering both knowledge
development and innovation in solar PV fault diagnosis. We hope it will
inspire researchers to explore new frontiers in automated diagnostics
and encourage practitioners to adopt cutting-edge technologies for
enhancing PV system reliability and sustainability.
We wish to express our sincere gratitude to all the contributors,
reviewers, and supporting institutions whose efforts have enriched this
work. It is our pleasure to present this book to the global community,
contributing to the ongoing efforts to make solar energy more dependable
and accessible.