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Published on: October 3, 2018
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.
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.
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.
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