{"id":8918,"date":"2022-07-13T12:54:43","date_gmt":"2022-07-13T10:54:43","guid":{"rendered":"https:\/\/reuniwatt.com\/en\/?p=8918"},"modified":"2025-07-02T09:20:33","modified_gmt":"2025-07-02T07:20:33","slug":"wrf-solar-eps-a-new-probabilistic-solar-power-forecasting-tool","status":"publish","type":"post","link":"https:\/\/reuniwatt.com\/en\/company-news\/wrf-solar-eps-a-new-probabilistic-solar-power-forecasting-tool\/","title":{"rendered":"WRF-Solar EPS: A new probabilistic solar power forecasting tool"},"content":{"rendered":"

Among the many existing numerical weather prediction (NWP) models, the Weather Research and Forecasting (WRF) model is the most widely used open-source predictive model for weather forecasting worldwide. The recently developed WRF-Solar Ensemble Prediction System (EPS) allows us to provide high quality probabilistic solar irradiance forecasts.<\/strong><\/p>\n

What is WRF-Solar?<\/h2>\n

As more and more photovoltaic (PV) systems are being installed around the Globe, intraday and day-ahead solar power forecasting<\/a> becomes increasingly important. In numerical weather prediction (NWP) models, shortwave radiation is not a state variable, but a diagnostic variable. In other words, NWP models originally had not been designed for solar radiation forecasting.<\/p>\n

WRF-Solar is an enhancement of the WRF model for a more accurate simulation of the aerosol-cloud-radiation interplay. In the recent years, the weather research and forecasting (WRF) model has been augmented and specifically adapted for better modelling the interaction of aerosols, clouds, and radiation 1,2<\/sup>. Numerous improvements in the parameterisation schemes of the WRF model have been implemented in WRF 3,4<\/sup>. This allows to largely reduce the forecast error of solar irradiance, especially in clear sky situations.<\/em><\/p>\n

What is the WRF-Solar Ensemble Prediction System (EPS)?<\/h2>\n

WRF-Solar EPS is an extension to the WRF-Solar components of the WRF model. It introduces stochastic perturbations in the parameterisation variables that are most relevant for solar radiation arriving at the ground. These variables have been identified with tangent linear models. The stochastic perturbation methods in this state-of-art forecasting tool are especially chosen to account for uncertainties of representation in cloud, aerosol, and radiation processes 5<\/sup>. A high-quality ensemble prediction system like WRF-Solar EPS enables us to identify and quantify solar energy resources, as each ensemble member depicts a possible future state. The ensemble spread can be used to assess the range and uncertainty of solar power predictions and lead to improved probabilistic solar irradiance forecasting.<\/p>\n

This interactive plot shows an example of global horizontal irradiance (GHI) as predicted by WRF-Solar EPS for Lindenberg (Germany) on 4 March 2022. WRF is set up to run on two domains: One with a horizontal grid spacing of 9 km, and the other one with a grid spacing of 3 km. The spread of the 5-member ensemble differs from one domain to the other. The observations originate from DWD\u2019s Open Data portal.<\/p>\n<\/div>