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

• Autor(a) principal: Lopes, Francisco
• Data de Publicação: 2019
• Outros Autores: Conceição, Ricardo, Silva, Hugo, Salgado, Rui, Canhoto, Paulo, Collares-Pereira, Manuel
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10174/25751; https://doi.org/Lopes, F.M., Conceição, R., Silva, H.G., Salgado, R., Canhoto, P., Collares-Pereira, M., 2019. Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation. AIP Conference Proceedings 2126, 190010 (2019). https://doi.org/10.1063/1.5117707; https://doi.org/10.1063/1.5117707

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 during partly cloudy days, due to solar intermittency. 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 focus 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 operation improvement 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 lower correlations are obtained for hourly values (≈0.88), due to cloud representation of the IFS during overcast periods, leading to small deviations with respect to those from measurements. Moreover, to measure the forecasting skill of the IFS, daily and hourly skill scores based on local measurements and a persistence model are obtained (≈0.66 and ≈0.51, 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.