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 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) developed estimate Pakistan. meteorological data from the year 2000–2017 is used while covering thirty locations five climatic zones of models’ performance statistically assessed terms normalized mean bias error (nMBE) and root square (nRMSE). results indicate that two Gaussian function model estimates with a satisfactory at most stations different zones. On average, correlation coefficient index agreement between 0.934 0.956, respectively. then further compared four existing best claimed found literature. Results show nMBE nRMSE ranges 0.87 3.00 0.95 3.21, Thus, it shows overestimate applicable for long-term planning. comparison, present take values −0.05 0.17 0.09 0.24, Furthermore, Global Performance Indicator (GPI) rank upon their prediction which −3.5626 4.1998. study revealed DYB suited hot regions Pakistan cold Also, within China Economic Corridor (CPEC) highway network have maximum accuracy. This can help energy system designers location