Predictive Control of a Solar Cooling Plant

This project focuses on the modeling and predictive control of an industrial-scale medium-temperature solar cooling facility. The system enables real-time configuration switching of solar collector fields to maximize heat absorption.

Key Research Contributions:

• First-Principles Modeling: Formulated grey-box models combining thermodynamics with experimental identification data.
• Hybrid MPC: Computes optimal collector field switching over a 6-hour prediction horizon.
• Energy Optimization: Achieved significant reduction in auxiliary gas fuel consumption while strictly enforcing thermal setpoints.