The design an intelligent PV panel’s faults detection system based on an improved Sugeno fuzzy inference technique - Al-Dulame, Abrar Abdalkareem; Al-Kafaji, Muhammed Salah Sadiq (AIP conference proceedings, 2024)
The combined worldwide photovoltaic (PV) limit has been becoming dramatically all over the planet. Issue identification and examination are significant for the productivity, unwavering quality and security of sun based photovoltaic (PV) frameworks. PV system malfunction diagnostics has been the subject of several studies in recent years. Only a few number of defect diagnosis techniques can be implemented on integrated circuits due to the high cost and complexity of the hardware necessary to do so. Implemented the technology of the Fuzzy Sugeno, which is an effective technology in detecting faults affecting the photovoltaic system. The simulation results that have been implemented prove the efficiency of the proposed technique. In addition, the suggested method is able to take into account radiation and temperature, in addition to other non-linear relationships of patterns amongst predictors, in order to pinpoint the precise location where the PV system generates the most amount of its highest power.