Improved ECMWF forecasts of direct normal irradiance: A tool for better operational strategies in concentrating solar power plants

• Autor(a) principal: Lopes, Francisco
• Data de Publicação: 2020
• Outros Autores: Conceição, Ricardo, Silva, Hugo, Salgado, Rui, 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/10174/28624; https://doi.org/10.1016/j.renene.2020.08.140
• topic: ECMWF; Direct normal irradiance; Short-term forecasting; Model output statistics; Concentrating solar power operalation; Energy production simulations

To contribute for improved operational strategies of concentrating solar power plants with accurate forecasts of direct normal irradiance, this work describes the use of several post-processing methods on numerical weather prediction. Focus is given to a multivariate regression model that uses measured irradiance values from previous hours to improve next-hour predictions, which can be used to refine daily strategies based on day-ahead predictions. Short-term forecasts provided by the Integrated Forecasting System, the global model from the European Centre for Medium-Range Weather Forecasts (ECMWF), are used together with measurements in southern Portugal. As a nowcasting tool, the proposed regression model significantly improves hourly predictions with a skill score of z0.84 (i.e. an increase of z27.29% towards the original hourly forecasts). Using previous-day measured availability to improve next-day forecasts, the model shows a skill score of z0.78 (i.e. an increase of z6% towards the original forecasts), being further improved if larger sets of data are used. Through a power plant simulator (i.e. the System Advisor Model), a preliminary economic analysis shows that using improved hourly predictions of electrical energy allows to enhance a power plant’s profit in z0.44 MV/year, as compared with the original forecasts. Operational strategies are proposed accordingly.