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Updated: Jul 7, 2025

In Situ Monitoring of the Accelerated Performance Degradation of Solar Cells and Modules: A Case Study for CuIn,GaSe2 Solar Cells

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Comprehensive Analysis of Solar Panel Performance and Correlations with Meteorological Parameters.

Pranjal Sarmah¹, Dipankar Das¹, Madhurjya Saikia¹

¹Department of Mechanical Engineering, Dibrugarh University, Dibrugarh 786004, India.

|December 25, 2023

Summary

This summary is machine-generated.

Solar panel efficiency is directly linked to meteorological conditions like solar intensity and wind speed. This study develops a correlation to optimize solar power plant performance by analyzing these key environmental factors.

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Area of Science:

Renewable Energy
Environmental Science
Materials Science

Background:

Fossil fuel reliance necessitates clean energy solutions like solar power.
Solar panel efficiency is crucial for economic viability but is influenced by meteorological factors.
A clear correlation between meteorological parameters and solar panel efficiency is needed.

Purpose of the Study:

To analyze the impact of meteorological parameters on solar panel efficiency.
To develop a predictive correlation between efficiency and key environmental factors.
To provide insights for optimizing solar power plant performance.

Main Methods:

Regression analysis was performed on a dataset of 100 data points.
The study examined the influence of temperature, humidity, wind speed, solar intensity, and dew point.
An optimal tilt angle of 26° was identified for maximum power output.

Main Results:

Solar panel efficiency shows direct proportionality to solar intensity and wind speed.
Efficiency demonstrates inverse proportionality to temperature, humidity, and dew point temperature.
A strong correlation was established between efficiency and five meteorological parameters, with calculated efficiencies showing low deviation (0.08-1.20%) from experimental values.

Conclusions:

Meteorological parameters significantly affect solar panel efficiency.
The developed correlation offers a valuable tool for predicting and optimizing solar energy harvesting.
Understanding these relationships is key to enhancing the performance of solar power plants.