September 10, 2025Applied SciencesOpen Access

Explainable Machine Learning and Predictive Statistics for Sustainable Photovoltaic Power Prediction on Areal Meteorological Variables

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This framework ranks meteorological variables impacting photovoltaic output, suggesting improved grid integration.

The framework identifies key weather parameters affecting photovoltaic generation, ensuring reliable predictions.
Using 27 variables over a two-year timeframe, the model achieves a predictive accuracy with R2 ≅ 0.91.
The study employs a three-stage feature-selection pipeline to streamline model inputs, enhancing performance.
Applications include guiding plant siting and sensor prioritization for better grid operation strategies.

Nematzadeh et al. (2025) studied this question.

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September 10, 2025Applied SciencesOpen Access

View Full Paper

Ask AI

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Authors

This framework ranks meteorological variables impacting photovoltaic output, suggesting improved grid integration.

The framework identifies key weather parameters affecting photovoltaic generation, ensuring reliable predictions.
Using 27 variables over a two-year timeframe, the model achieves a predictive accuracy with R2 ≅ 0.91.
The study employs a three-stage feature-selection pipeline to streamline model inputs, enhancing performance.
Applications include guiding plant siting and sensor prioritization for better grid operation strategies.

Nematzadeh et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark