Predictive Value of Short-term Forecasts of DNI for Solar Energy Systems Operation

Solar power forecasting plays a critical role in power-system management, scheduling, and dispatch operations. Accurate forecasts of direct normal irradiance (DNI) are essential for an optimized operation strategy of concentrating solar thermal (CST) systems, particularly under clear-sky conditions during partly cloudy days. In this work, short-term forecasts from the radiative scheme McRad (Cycle 41R2) included in the Integrated Forecasting System (IFS), the global numerical weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF), together with in-situ ground-based measurements, are used in a simulated linear parabolic-trough power system through the System Advisor Model (SAM). Results are part of a preliminary analysis concerning the value of DNI predictions from the IFS for the improvement of the operationalization of a CST system with similar configurations as the Andasol 3 CST power plant. For a 365-day period, the present results show high correlations between predictions of energy to grid based on measurements and IFS forecasts mainly for daily values (~0.94), while the lower correlations obtained for hourly values (~0.89) are due to cloud representation of the IFS during overcast periods, leading to small deviations with respect to those from measurements. Moreover, as means to measure the forecasting skill of the IFS, daily and hourly skill scores based on local measurements and a persistence model are obtained (0.67 and 0.53, respectively), demonstrating that the IFS has a good overall performance. These aspects show the value that forecasted DNI has in the operation management of CST power systems, and, consequently, in the electricity market.This work was co-funded by the European Union through the European Regional Development Fund, framed in COMPETE 2020 (Operational Program Competitiveness and Internationalization), through the Institute of Earth Sciences (UID/GEO/04683/2013) with reference POCI-01-0145-FEDER-007690, and through the projects DNI-A (ALT20-03-0145-FEDER-000011), ALOP (ALT20-03-0145-FEDER-000004) and INSHIP (H2020, grant agreement 731287). The initial recommendations of T. Fasquelle, P. Gilman (SAM Support) and R. Hogan, is recognized and appreciated. The authors are also thankful for the availability of the ECMWF and the Portuguese Meteorological Service (IPMA) in providing data. F. M. Lopes is thankful for the FCT scholarship (SFRH/BD/129580/2017), R. Conceição to the FCT scholarship (SFRH/BD/116344/2016), and H. G. Silva to DNI-A and INSHIP for his research contract