Survey of Electrical Parameters Behavior in Faulty Photovoltaic Systems Towards AI and Maintenance Advancements

This chapter delves into the intricate behavior of electrical parameters in photovoltaic (PV) systems under faulty conditions, shedding light on how these faults can significantly impact system performance and efficiency. The analysis covers a range of critical faults, including mismatch, arc, short circuit, and open circuit faults, each of which exhibits unique characteristics and effects on the system's electrical parameters. The chapter provides a detailed examination of how these faults manifest and how they can be detected and diagnosed using advanced AI techniques. By focusing on key electrical parameters such as open circuit voltage (Voc), short circuit current (Isc), output voltage (Vout), and output current (Iout), the chapter offers a comprehensive understanding of the system's response to various fault scenarios. Furthermore, it explores the potential of deep learning models in automating fault detection and maintenance, highlighting the importance of feature selection and data preprocessing in achieving accurate and efficient fault diagnosis. The chapter also discusses the challenges and limitations of current AI-based fault detection methods, paving the way for future research and advancements in this critical area. Through its detailed analysis and insights, this chapter serves as a valuable resource for anyone seeking to enhance the reliability and performance of photovoltaic systems.