Modelling and predictive control of a solar cooling plant with flexible configuration. (April 2019)

• Record Type: Journal Article
• Authors: Rathod, Niraj; Bella, Alessio La; Puleo, Gianluca; Scattolini, Riccardo; Rossetti, Andrea; Sandroni, Carlo
• Is Part Of: Journal of process control. Volume 76(2019)
• Page Start: 74
• Page End: 86
• Publication Date: 2019-04
• Subjects: Solar cooling plant -- Modelling -- Model identification -- Model Predictive Control (MPC) -- Hybrid systems; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2019.01.009
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: A real solar cooling plant is modelled using both thermodynamic principles and identification techniques. A novel formulation of a Hybrid-MPC problem is proposed in order to change the plant configuration based on the forecasts of weather and user demand. The performances of the control system are evaluated both in simulation and through experimental tests on the real plant. The results witness that the designed control system achieves satisfactory performances in terms of energy saving. Abstract: This paper focuses on the modelling and predictive control of a real medium temperature solar cooling system made up of a solar collector, an absorption chiller, a gas heater, hot and cold water storage tanks, connecting pipes, pumps, and a number of valves, allowing to modify the plant configuration in order to optimize its performance in terms of electric power and gas consumption. A detailed model of the plant is first obtained as a mix of first principle equations, validated with data collected on the plant, and identification techniques. Then, the model is simplified and used to formulate a hybrid Model Predictive Control (MPC) problem computing the optimal plant configuration over a prediction horizon of six hours, or more, and based on the available forecast of the solar radiation and user demand. The developed MPC algorithm has been used to control the plant; some of the collected results are reported here to witness the potentialities of the proposed approach.