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

Application of Nowcasting DNI Maps to Dynamic Solar Tower Simulation




Process Prediction, DNI Forecasting, Nowcasting, Uncertainty Analysis, Molten Salt Receiver System, Dynamic Process Simulation, Cloud Passage Simulation, Operating Assistance, Model Predictive Control


Concerning current efforts to improve operational efficiency and to lower overall costs of concentrating solar power (CSP) plants with prediction-based algorithms, this study investigates the quality and uncertainty of nowcasting data regarding the implications 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, based on a statistical uncertainty analysis, a correlation is developed, which allows for predicting the uncertainty of the net power prediction based on the corresponding DNI forecast uncertainty. However, the study reveals significant prediction errors and the demand for further improvement in the accuracy at which local shadings are forecasted.


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How to Cite

Schwager, C., Angele, F., Nouri, B., Schwarzbözl, P., Teixeira Boura, C. J., & Herrmann, U. (2024). Impact of DNI Forecast Quality on Performance Prediction for a Commercial Scale Solar Tower: Application of Nowcasting DNI Maps to Dynamic Solar Tower Simulation. SolarPACES Conference Proceedings, 1.

Conference Proceedings Volume


Analysis and Simulation of CSP and Hybridized Systems

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