Hierarchical control based on a hybrid nonlinear predictive strategy for a solar-powered absorption machine facility

Abstract

This work presents a hierarchical framework to control a solar thermal facility aiming to provide the required operating conditions for an absorption chiller machine. The CIESOL thermal plant, located at the University of Almería (Spain), is proposed as a case study in which all subsystems and valves are considered in a trustworthy simulation environment. Herein, the thermal plant dynamic representation is completed by presenting the absorption chiller modeling, in which three distinct models, namely, a first principle lumped parameters, an AutoRegressive with eXogenous input (ARX), and a Nonlinear ARX (NLARX) models, are validated. Accordingly, by using these models, the hierarchical control based on a hybrid nonlinear predictive controller is formulated. Dwell-time and stress zone are embedded in the operating condition constraints of the hybrid control component of the upper layer to enhance robustness and performance. Moreover, a lower layer based on Proportional–Integral (PI) controllers is also designed to overcome the valve’s nonlinear dynamics and improve disturbance rejection on the regulatory layer. The results demonstrate that the hierarchical structure controls the solar plant around 115 min more in the operating time of the solar-powered absorption chiller, with less usage of fossil fuels sources compared to a conventional operation of the system.