Experimental operation of a solar‐driven climate system with thermal energy storages using mixed‐integer nonlinear model predictive control
Adrian Bürger, Daniel Bull, Parantapa Sawant, Markus Bohlayer, Andreas Klotz, Daniel Beschütz, Angelika Altmann‐Dieses, Marco Braun, Moritz Diehl
Abstract
Abstract This work presents the results of experimental operation of a solar‐driven climate system using mixed‐integer nonlinear model predictive control (MPC). The system is installed in a university building and consists of two solar thermal collector fields, an adsorption cooling machine with different operation modes, a stratified hot water storage with multiple inlets and outlets as well as a cold water storage. The system and the applied modeling approach is described and a parallelized algorithm for mixed‐integer nonlinear MPC and a corresponding implementation for the system are presented. Finally, we show and discuss the results of experimental operation of the system and highlight the advantages of the mixed‐integer nonlinear MPC application.