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Original Research
Received:
24 January 2025
Revised:
5 March 2025
Accepted:
9 May 2025
Published online:
1 June 2025
Abstract:
The solar panel or solar cell is one of the most important components of the solar system that produces electrical energy with high efficiency compatible with electrical loads, but any defect in this cell can cause its efficiency to decrease. The objective of this work is to establish a fault diagnosis method that can be implemented in a real structure. These faults are diagnosed and located by implementing an algorithm based on the measured values of the solar panel using an intelligent recursive least squares approach. Our objective is to contribute to the diagnosis of faults in photovoltaic systems based on fuzzy logic in a recurrent manner. The integration of recursive least squares (RLS) with fuzzy logic are essential to improve system efficiency and reliability. This approach enables rapid identification and resolution of faults, helping to avoid energy losses, reduce downtime and support proactive maintenance. It guarantees the optimal functioning of solar panels, maximizing energy production and improving return on investment. Quantitatively, this method achieves high diagnostic accuracy (over 90%), reduces error rates by up to 30% under dynamic conditions, and provides real-time fault detection with minimal latency. The combination of RLS and fuzzy logic improves fault diagnosis by effectively handling uncertainties and handling ambiguous situations better than traditional methods.
Keywords: Solar panel; Fault diagnosis; Recursive least squares; Fuzzy logic
(ProQuest: ... denotes formulae omitted.)
1. Introduction
Photovoltaic solar energy is a sustainable and non-polluting energy source. It plays a significant role in research to meet future energy needs. Currently, PV module manufacturing technology has evolved considerably in quality and production cost [1].
Defects in a photovoltaic installation can occur during its design, installation, and operation [2]. These defects decrease the performance of photovoltaic systems, affecting photovoltaic production [3].
The issue of diagnosing a solar panel using fuzzy logic aims to assess its operational state based on incomplete or uncertain data. Fuzzy logic allows for simulating how individuals make decisions in the face of uncertainty. In this context, the goal is to determine whether the panel is functioning correctly, if it has minor or major defects, or if it is completely out of service....