Data-Driven Validation of Photovoltaic Performance in the Climatic Context of Malta

Optimizing photovoltaic (PV) performance in regions with challenging climates is essential for maximizing energy efficiency. This study addresses the unique environmental conditions in Malta, such as high temperatures and atmospheric salinity, that impact PV systems. The framework developed aims to validate the accuracy and reliability of PV data using advanced acquisition techniques. By correlating solar irradiance with DC current and applying statistical tests including the T-test, anomalies such as shading, and system faults are identified. Results highlight the effectiveness of this approach in detecting performance issues, ensuring data accuracy, and enhancing PV system reliability. This scalable solution not only improves fault and shading detection but also contributes to optimizing PV performance in Malta and other regions with similar climates.

Authors

Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/isgteurope62998.2024.10863628
Primary Topic
Energy Load and Power Forecasting
Type
article
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article

Data-Driven Validation of Photovoltaic Performance in the Climatic Context of Malta

Kenneth Scerri, Brian Bartolo, Brian Azzopardi
Energy Load and Power Forecasting
article

Data-Driven Validation of Photovoltaic Performance in the Climatic Context of Malta

Kenneth Scerri, Brian Bartolo, Brian Azzopardi
article en

Abstract

Optimizing photovoltaic (PV) performance in regions with challenging climates is essential for maximizing energy efficiency. This study addresses the unique environmental conditions in Malta, such as high temperatures and atmospheric salinity, that impact PV systems. The framework developed aims to validate the accuracy and reliability of PV data using advanced acquisition techniques. By correlating solar irradiance with DC current and applying statistical tests including the T-test, anomalies such as shading, and system faults are identified. Results highlight the effectiveness of this approach in detecting performance issues, ensuring data accuracy, and enhancing PV system reliability. This scalable solution not only improves fault and shading detection but also contributes to optimizing PV performance in Malta and other regions with similar climates.

Climate action
Openalex Percentile: Top 75%
Energy Load and Power Forecasting
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