Effect of Data Sources and DNI Effectiveness on CSP power plants Performances Assessment. Case Studies in Algeria.

Abstract

This study presents a comparative assessment of high and medium resolution Direct Normal Irradiance (DNI) datasets, combined with real meteorological measurements and satellite-derived estimates, to evaluate their impact on the performance of Concentrated Solar Power (CSP) systems. The analysis focuses on four representative regions in Bechar, Elouad, Djelfa, and Biskra, and examines how the choice of DNI data source influences the resulting capacity factor (CF). The results show notable discrepancies across regions. In Bechar (DNI = 700 W/m²), a system with SM = 1.8 and 2 hours of TES generated 11.44 GWh/year with a CF of 6.7%. In Elouad (DNI = 750 W/m²), using SM = 1.2 and 2 hours of TES, annual production reached 7.4 GWh/year, corresponding to a CF of 4.2%. For Djelfa (DNI = 1050 W/m²), the same system with SM = 1.5 and 4 hours of TES achieved 18.45 GWh/year and a CF of 10.5%. Biskra exhibited the most striking contrast: with real DNI data (420 W/m²), SM = 1.3, and 6 hours of TES, the system delivered 71.51 GWh/year and a CF of 43.59%. When satellite-derived DNI was used instead, energy production increased to 75.7 GWh/year, raising the CF to 43.78%. These results highlight substantial performance variations driven by the choice of meteorological input data. The findings underscore the importance of selecting reliable DNI datasets for accurate CSP evaluation, ultimately supporting more effective system design, improved energy yield predictions, and the broader development of solar energy technologies in Algeria.