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This paper presents a new detection method of fault and partial shading condition (PSC) in a photovoltaic (PV) domestic network, considering maximum power point tracking (MPPT). The MPPT has been executed by employing a boost converter using particle swarm optimization (PSO) technique. The system is composed of two photovoltaic arrays. Each PV array contains three panels connected in series, including distinct MPPT. The PSC detection exploits the neighboring PV system data. This suggested innovative algorithm is proficient in detecting these subjects: (a) fault, (b) partial shading condition, (c) solar panel (d) panel’s relevant bypass diode failure, (d) converter failure alongside specifying the failed semiconductor, and (e) PV disconnection failure. The simulation process has been implemented using MATLAB/Simulink software. To this end, the proposed method was investigated experimentally using two 250 W PV solar set under various PSCs and faults. A data exchange link is used to implement an integrated management system. The Zigbee protocol was also chosen to data exchange of converters. The results validated the applicability and practicality of this algorithm in domestic PV systems.

international journal of photoenergy

A Novel Experimental and Approach of Diagnosis, Partial Shading, and Fault Detection for Domestic Purposes Photovoltaic System Using Data Exchange of Adjacent Panels