Performance evaluation of independent global solar radiation estimation models for different climatic zones: A case study

Rapid technological advancement in solar applications requires accurately determined daily global solar radiation (DGSR). The independent models to predict DGSR are super cited as they do not require any other climatological or geographical parameter. In this study, nine day-of-the-year based (DYB) independent models are developed to estimate daily global solar radiation in Pakistan. The meteorological data from the year 2000-2017 is used while covering thirty locations from five climatic zones of Pakistan. The models' performance is statistically assessed in terms of normalized mean bias error (nMBE) and normalized root mean square error (nRMSE). The results indicate that the two Gaussian function model estimates DGSR with a satisfactory performance at most stations in different climatic zones. On average, the correlation coefficient and index of agreement between day-of-the-year and DGSR are 0.934 and 0.956, respectively. The two Gaussian function model is then further compared with four existing best claimed models found in literature. Results show that the nMBE and nRMSE ranges from 0.87 to 3.00 and 0.95 to 3.21, respectively. Thus, it shows that the existing models overestimate the DGSR and are not applicable for long-term planning. In comparison, for the present study, nMBE and nRMSE take values between -0.05 to 0.17 and 0.09 to 0.24, respectively. Furthermore, Global Performance Indicator (GPI) is used to rank the models based upon their prediction performance which ranges between -3.5626 and 4.1998. The study revealed that DYB models are best suited for hot climatic regions of Pakistan as compared to cold climatic zones. Also, the locations within the China Pakistan Economic Corridor (CPEC) highway network have maximum accuracy. This study can help energy system designers to predict DGSR values at any location in Pakistan.