Abstract
Solar photovoltaic appears to be the most interesting renewable energy in developing countries where its deposit is abundant. Unfortunately, the lack of precise knowledge of solar radiation deposit and its limited data hinder optimal exploitation of solar installations. This study presents a performing model for daily global horizontal solar radiation for the five regional capitals in Togo: Lomé, Atakpamé, Sokodé, Kara and Dapaong. The data used for the study were obtained from the General Directorate of National Meteorology of Togo, for five years. The model developed combines linear and nonlinear methods with harmonic and exponential terms taking into account climatological parameters such as location latitude, daily relative humidity, daily ratio of sunshine duration and daily mean temperature. Statistical errors of the model were compared to those of two previous models elaborated for Togo and Nigeria. The results showed that the model is more efficient to predict global horizontal solar radiation over the five main cities in Togo. The comparison of estimated data and measured ones showed a good agreement between them.
Highlights
Energy access and environmental issues have made research on the development and mastery of renewable energy technologies more than urgent today
These independent constants express the best model approach to real data when nonlinear regression has been done for horizontal solar radiation data
The Mean Percentage Error (MPE) and Mean Absolute Percentage Error (MAPE) respectively decrease or increase from Lomé to Dapaong. These results afford to reveal that the model using in Lomé is most performed than others through the MPE and MAPE values
Summary
Energy access and environmental issues have made research on the development and mastery of renewable energy technologies more than urgent today. Amou et al [12] presented work on the linear and exponential model in order to predict the global horizontal solar radiation of many cities in Togo, parameters like relative humidity and mean daily temperature were used The performance of these empirical models showed that only a few give less than 10% of relative error between simulated and measured values [13] [14]. Amou et al [15], attempt for forecasting Togo’s potential solar radiation maps with the Multilayer Perceptron (MLP) across to artificial neural network (ANN) who depends on three parameters such as latitude, relative humidity and temperature In view of these previous studies, the statistical errors of which are relatively high, it appears necessary to work on the development of more efficient models in order to be able to generate more precise solar irradiation data for all of Togo.
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