Impact of DNI Forecast Quality on Performance Prediction for a Commercial Scale Solar Tower

Kurzfassung

Concerning current efforts to improve operational efficiency and to lower overall costs of concentrating solar power plant with prediction-based algorithms this study investigates the quality and uncertainty of nowcasting data regarding the implication for process predictions. DNI (direct normal irradiation) maps from an all-sky imager based nowcasting system are applied to a dynamic prediction model coupled with ray tracing. The results underline the need for high-resolution DNI maps in order to predict net yield and receiver outlet temperature realistically. Furthermore, a correlation developed based on a statistical uncertainty analysis allows for predicting the uncertainty of the net power prediction based on the current DNI forecast uncertainty. However, the study reveals significant prediction errors suggesting the need for improvement in the accuracy at which local shadings are forecasted.