Design and Implementation of a Detection and Diagnostic System for Anomalies in a Grid-Connected Photovoltaic System
Abstract
This paper presents the design and implementation of a detection and diagnostic system for anomalies in a photovoltaic (PV) installation connected to the national EEC grid in Congo Brazzaville, under the framework of Denis SASSOU NGUESSO University. The main objective is to reduce maintenance costs and improve energy productivity, given that PV systems are inherently prone to operational failures. The study focuses on faults affecting the PV generator and proposes a method for detecting and precisely localizing anomalies that reduce energy output. The approach is based on analyzing the current–voltage (I–V) and power–voltage (P–V) characteristics of the PV generator under varying operating conditions. Results, summarized in tables for clarity, demonstrate that the Lambert W/numerical model accurately reproduces the module’s electrical behavior, with a root mean square error (RMSE) of 0.1608 A for current (≈2 % of nominal current, 8 A) and 3.686 W for power (≈1.2 % of maximum power, 300 W). These low and unbiased errors validate the model for rapid performance drift detection, fault localization, and operating point optimization. The system provides a solid foundation for intelligent supervision and predictive maintenance, ensuring enhanced reliability, reduced downtime, and improved energy efficiency.
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References
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Copyright (c) 2026 Ursula Vanelie Kani Mboyo, Aristide Mankiti Fati, Rene Evrard Josue Samba
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