Forecasting solar irradiation using WRF model and refining statistics for Northeastern Brazil

Abstract:

Solar energy is referred to as variable generation sources because their electricity production varies based on the availability of sun irradiance. To accommodate this variability, electricity grid operators use a variety of tools to maintain a reliable electricity supply, one of them is to forecast solar irradiation, and to adjust other electricity sources as needed. This work reports an approach to forecast solar irradiation in the Brazilian Northeastern region (NEB) by using statistically post-processing data from mesoscale model outputs. The method assimilates the diversity of climate characteristics occurring in the region presenting the largest solar energy potentials in Brazil. Untreated solar irradiance forecasts for 24h in advance were obtained using the WRF model runs. Cluster analysis technique was employed to find out areas presenting similar climate characteristics and to reduce uncertainties. Comparison analysis between WRF model outputs and site-specific measured data were performed to evaluate the model skill in forecasting the surface solar irradiation. After that, post-processing of WRF outputs using artificial neural networks (ANNs) and multiple regression methods refined the short-term solar irradiation forecasts. A set of pre-selected variables of the WRF model outputs representing the forecasted atmospheric conditions were used as predictors by the ANNs. Several predictors were tested in the adjustment and simulation of the ANNs. We found the best ANNs architecture and a group of 10 predictors, with which more in-depth analyzes were carried out, including performance evaluation for fall and spring of 2011 (rainy and dry season in NEB). The site-specific measured solar radiation data came from 110 stations distributed throughout the NEB. Data for the rainy season were acquired from March to May, and for the dry season from September to November. We concluded that the untreated numerical forecasts of solar irradiation provided by WRF exhibited a good correlation with the observed data but presented large systematic errors and large spread of values. The post-processing of data described here proved to consistently improve the WRF model forecasts for surface solar irradiation for most of the measurement sites.

Supported by Petrobras contract No. 23000.0073552011-96