Resolving challenges of monitoring PV systems: A case study for three 1.5 kW generators in Lima, Peru

Acceso al texto completo solo para la Comunidad PUCP

Abstract

Abstract This paper addresses challenges from monitoring three grid-connected PV systems with different module technologies in Lima, Peru, following the International Electrotechnical Commission (IEC) standards. Missing and erroneous data due to sensor malfunction or partial shadowing can negatively impact the measured data quality. We developed a program to automatically detect erroneous measurements, enhance the data quality, and calculate PV performance parameters following the IEC-61724 standard to resolve these challenges. The program includes mathematical methods to replace faulty or missing measurements. Finally, we present the impact of the algorithms for erroneous data detection, deletion, and correction on performance calculations.

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Photovoltaic system, Grid, Missing data, Reliability engineering, Computer science, Data quality, Quality (philosophy), Systems engineering, Data mining, Real-time computing, Engineering, Electrical engineering, Geography, Machine learning, Operations management

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