Research Article Performance Analysis of Clear Sky Global Horizontal Irradiance Models: Simple Models Adapted for Local Conditions Nicholas Kwarikunda 1 and Zivayi Chiguvare 2 1 Department of Physics, Makerere University, P.O. Box 7062, Kampala, Uganda 2 Department of Physics, University of Namibia, Private Bag 13301, Windhoek, Namibia Correspondence should be addressed to Nicholas Kwarikunda; nicholas.kwarikunda@mak.ac.ug Received 5 May 2021; Accepted 11 September 2021; Published 27 September 2021 Academic Editor: Koray Ulgen Copyright © 2021 Nicholas Kwarikunda and Zivayi Chiguvare. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Evaluation of the maximum solar energy potential of a given area for possible deployment of solar energy technologies requires assessment of clear sky solar irradiance for the region under consideration. Such localized assessment is critical for optimal sizing of the technology to be deployed in order to realize the anticipated output. As the measurements are not always available where they are needed, models may be used to estimate them. In this study, three different models were adapted for the geographical location of the area under study and used to estimate clear sky global horizontal irradiance (GHI) at three locations in the subtropical desert climate of Namibia. e three models, selected on the basis of input requirements, were used to compute clear sky GHI at Kokerboom, Arandis, and Auas. e models were validated and evaluated for performance using irradiance data measured at each of the sites for a period of three years by computing statistical parameters such as mean bias error (MBE), root mean square error (RMSE), and the coefficient of determination (R 2 ), normalized MBE, and normalized RMSE. Comparative results between modelled and measured data showed that the models fit well the measured data, with normalized root mean square error values in the range 4–8%, while the R 2 value was above 98% for the three models. e adapted models can thus be used to compute clear sky GHI at these study areas as well as in other regions with similar climatic conditions. 1.Introduction Deployment of solar energy technologies for solar pho- tovoltaic (PV) or thermal applications requires an as- sessment of the solar energy resource available at the location of interest. Quite often, such measurements may not be available for that location and so have to be esti- mated under clear sky conditions [1–3]. In some areas, even when measurements are available, gaps may exist in the measurement records that may need to be filled up to efficiently characterize the resource [4, 5]. Clear sky irra- diance, in particular, the global horizontal irradiance (GHI), provides information about the maximum possible solar energy resource available at the location under consideration, which is crucial in estimating or forecasting the performance of solar energy technologies [6]. It is therefore important to estimate, locally, the clear sky GHI in order to forecast the optimal performance of the solar technologies before deployment. Different kinds of models for clear skies, with varying levels of complexity and input parameters, have been de- veloped over time to estimate clear sky global solar irradi- ance for various solar energy conversion applications especially in areas where the measurements are not available. ese models are either based on empirical expressions [7–9] or may be broadband [10, 11]. Empirical-based ir- radiance models require geometric parameters such as ze- nith angle and or basic meteorological parameters such as sunshine hours, relative humidity, pressure, clearness index, and temperature [12, 13] as input parameters, while the broadband irradiance models require parameters that characterize the atmospheric conditions in detail, including but not limited to parameters such as aerosol optical depth, amount of precipitable water, and ozone column [1, 14–16]. Hindawi Journal of Renewable Energy Volume 2021, Article ID 4369959, 12 pages https://doi.org/10.1155/2021/4369959