Modelling of Solar Power Production in Dry and Rainy Seasons Using Some Selected Meteorological Parameters

Abstract

In this paper, we deployed the multiple linear regression method in developing a solar power output model for solar energy production, where the meteorological parameters are the independent variables. We fitted the model and found that the meteorological variables considered accounted for 94.88% and 99.61% of the power output in both dry and rainy seasons. We observed from the work that the solar panel performs well in all seasons but slightly better in the rainy seasons. This could be attributed to the washing away of dust particles from solar panels by the rain and higher operating temperature different from the specified manufactured temperature of 25˚C. We observed that other factors such as the cloud slightly affect the optimal performance of the system. Panels inclined at an angle of 5˚ (Tilt) and facing south azimuth performs optimally, periodic washing of the surface of solar panels enhances optimal performance.

Design and Implementation of a Photovoltaic Data Acquisition System for Some Meteorological Variables

“…From the Analysis of Variance presented in Table 3, we observed that all the parameters such as; Irradiation (X 1 ), Temperature (X 2 ), Wind speed (X 3 ) and Humidity (X 4 ) were significant in solar power output in this quarter, this also correspond to the work of [13]. In this case, we accept the alternative hypothesis (H 1 :) and conclude that these parameters (Irradiation, Temperature, Wind speed and Humidity) contributed significantly to the solar power output.…”

“…From the analysis in Table 3, we observe that the fit was very much adequate and a little better than the corresponding fit in work of [13]. This is attributed to precision due to the developed data logger system.…”

“…This research comprises two segments; the first section is the development of solar PV data logger and monitoring system while the second section is concerned with the modeling; analysis of the data obtained from the developed system and comparing the result with the data collected from Nigeria Environmental Climatic Observatory Project (NECOP), sees [13]. The study was conducted in Port Harcourt, Nigeria a metropolitan city which is densely populated.…”

“…The model for this study was the multiple linear regression (meteorological) model adapted from [13], since our interest was to compare the performance of the developed system with the already existing work. Hence, the model for the study is…”

“…Therefore, this research seeks develop a solar PV data acquisition and monitoring system for improved solar PV panel performance. We will also adopt the approach by [13] to evaluate the performance of the system and compare the results.…”