The ASTEP project is proud to announce a featured publication presented at the Proceedings of the World Conference on Climate Change and Global Warming. The study highlights the use of an artificial neural network (ANN) model, developed in MATLAB, to predict the environmental performance of ASTEP’s innovative solar thermal system over a 30-year period.
The ASTEP system, designed to supply thermal energy up to 400°C, integrates a novel rotary Fresnel Sundial, thermal energy storage (TES), and an advanced control system. It has been successfully applied to industrial processes at Mandrekas Dairy Industry (MAND) and ArcelorMittal Tubular Products (AMTP).
Validation results demonstrated the model’s accuracy in predicting GHG emissions, with differences of 2.13 kgCO2eq/kWh for AMTP, 2.43 kgCO2eq/kWh for MAND, and 0.32 kgCO2eq/kWh for a third solar thermal plant. These findings confirm the ANN model as a valuable tool for evaluating the environmental impact of solar thermal systems, aiding industries in adopting measures to reduce their carbon footprint.
