Review of Environmental Parameter Modeling Affecting the Performance of Solar Photovoltaic Systems

Articles in Press

Document Type : Review Paper

Authors

Department of Renewable Energy Engineering, Shahid Beheshti University, Tehran, Iran

Abstract

The main objective of this study is to systematically review research on environmental parameter modeling for photovoltaic systems and to highlight recent methodological trends. PV performance is strongly influenced by environmental factors such as solar irradiance, temperature, wind speed, dust, humidity, precipitation, and atmospheric pressure. Accurate modeling of these parameters is essential for improving efficiency and reliability. To address this, the study employs bibliometric and content analysis of Scopus publications from 1984 to 2024. Results show a 9.13% annual growth in related studies, with China, India, Italy, the U.S., and Iran as leading contributors. Modeling approaches are categorized into white-box, black-box, and hybrid methods. Findings indicate that while white-box models provide interpretability, machine learning-based black-box models achieve higher predictive accuracy. Hybrid models, integrating physical and data-driven techniques, offer the most robust solutions. The study underscores the increasing role of ML in PV performance and recommends future research on hybrid frameworks, IoT-enabled data collection, and explainable AI.

Keywords

Main Subjects

Journal of sustainable Energy Systems

Articles in Press, Accepted Manuscript
Available Online from 06 September 2025

Files

Share

How to cite

Statistics