Effect of Solar-Terrestrial Phenomena on Solar Cell's Efficiency

TL;DR

This study investigates how solar-terrestrial phenomena and meteorological parameters influence solar cell efficiency, using ARIMA and regression models to forecast and optimize efficiency based on location-specific data.

Contribution

It introduces location-dependent modeling of meteorological factors affecting solar cell efficiency using ARIMA and multiple linear regression, achieving high accuracy in predictions.

Findings

Strong correlation between actual and forecasted meteorological variables.

Models achieved R2 values above 93%, indicating high fit quality.

Better meteorological modeling can enhance solar cell efficiency.

Abstract

It is assumed that the solar cell efficiency of PV device is closely related to the solar irradiance, considered the solar parameter Global Solar Irradiance (G) and the meteorological parameters like daily data of Earth Skin Temperature (E), Average Temperature (T), Relative Humidity (H) and Dew Frost Point (D), for the coastal city Karachi and a non-coastal city Jacobabad, K and J is used as a subscripts for parameters of Karachi and Jacobabad respectively. All variables used here are dependent on the location (latitude and longitude) of our stations except G. To employ ARIMA modeling, the first eighteen years data is used for modeling and forecast is done for the last five years data. In most cases results show good correlation among monthly actual and monthly forecasted values of all the predictors. Next, multiple linear regression is employed to the data obtained by ARIMA modeling and models for mean monthly observed G values are constructed. For each station, two equations are constructed the R2 values are above 93% for each model, showing adequacy of the fit. Our computations show that Solar cell efficiency can be increased if better modeling for meteorological predictors governs the process.