Abstract
Fault detection in photovoltaic (PV) systems using the Internet of Things (IoT) allows monitoring variables that may be of interest to users who do not have technical knowledge and wish to measure: current, voltage, temperature, power generated, and money saved by the energy generated. This study aims to present a methodology for implementing a low-cost Internet of Things (IoT) to an FS in order to identify recurring faults using the Exponentially Weighted Moving Average (EWMA) statistical technique. The system was applied to a 3500 W PV located at the Universidad Veracruzana Campus Cotzacoalcos.
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