Empirical Models for Predicting Global Solar Radiation on the African Continent Based on Factors of Location and Season

• 作者: Olabode M. Bamigbola Shola E. Atolagbe
• 来源期刊: 建模与仿真(英文)
• 学科: 数学
• 关键词: Solar Radiation Modelling Empirical Data Prediction INTERPOLATION
• 年，卷（期）: 2021,（1）
• 页码范围: 59-73
• 页数: 15页
• 分类号: O17

摘要

The importance of accurate knowledge about available global solar radiation in the design and development of various solar energy systems cannot be overemphasized. Most of the available models for predicting global solar radiation involve a plethora of input factors, some of which require special skills and equipment to measure. Such multi-factor models are complex and computationally demanding. To remove some burdens associated with such models, the use of</span><span style="font-family:Verdana;"> simplified prototypes with reduced input factors ha</span></span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> been proposed. It has </span><span style="font-family:Verdana;">been </span><span style="font-family:Verdana;">shown that a model with fewer input factors, that can be determined in a definite manner or whose attributes are directly observable, is often a better alternative. Therefore, the main object of this paper is to have models with a few variables that can easily be measured, developed for predicting global solar radiation. Two input factors</span><span style="font-family:Verdana;">, </span><span style="font-family:Verdana;">geographical location and season of the year</span><span style="font-family:Verdana;">, </span><span style="font-family:Verdana;">were considered. Using a 22-year interannual average daily insolation data from the database of the National Aeronautics and Space Administration (NASA) blended with the art of interpolation, empirical models were fashioned with </span><span style="font-family:""><span style="font-family:Verdana;">the data for the five subregions of Africa. The results of the models’ analysis indicate that the latitude component is the dominant locational factor. Furthermore, the new models exhibit optimal performance in comparison with existing </span><span style="font-family:Verdana;">models</span><span style="font-family:Verdana;"> and constitute reliable predictive tools that are suitable for estimating global solar radiation for any