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N. Sterl, M. Schuss, A. Mahdavi:
"Exploring the energy saving potential of model-predictive controls via dynamic co-simulation";
Talk: Clima 2016 - 12th REHVA World Congress, Aalborg, Denmark; 2016-05-22 - 2016-05-25; in: "Clima 2016 - proceedings of the 12th REHVA World Congress", P.K. Heiselberg et al. (ed.); REHVA, (8 Volumes) (2016), ISBN: 87-91606-26-8; Paper ID 217, 10 pages.

Recent advances of environmental control technologies have led to new practical opportunities
to reduce the heating demand of buildings. The applied technologies follow different paths to achieve energy savings, the use of advanced control systems as predictive control algorithms
show promising results with considerable optimization potential.
In the present contribution, we describe the development of an advanced control algorithm that, starting from an actual room's comprehensive thermal characterization, derives a simplified
mathematical model. Moreover, the procedure involves a co-simulation setup that incorporates the implementation of a realistic dynamic heater behavior. Heating demand with different control algorithms from simple 2-point switching control,
analogue PI-controller, to predictive control and model predictive control (MPC) strategy are implemented and compared. Together with the control algorithms, the dynamic thermal characteristics of the room heating elements, realized as radiators or floor heating, are modeled with their different time constants for heating up and cooling down and considerably different orders of time constants. The energy saving potential of the proposed approach is documented
via comparative simulation studies.

(no german version available) Recent advances of environmental control technologies have led to new practical opportunities
to reduce the heating demand of buildings. The applied technologies follow different paths to achieve energy savings, the use of advanced control systems as predictive control algorithms
show promising results with considerable optimization potential.
In the present contribution, we describe the development of an advanced control algorithm that, starting from an actual room's comprehensive thermal characterization, derives a simplified
mathematical model. Moreover, the procedure involves a co-simulation setup that incorporates the implementation of a realistic dynamic heater behavior. Heating demand with different control algorithms from simple 2-point switching control,
analogue PI-controller, to predictive control and model predictive control (MPC) strategy are implemented and compared. Together with the control algorithms, the dynamic thermal characteristics of the room heating elements, realized as radiators or floor heating, are modeled with their different time constants for heating up and cooling down and considerably different orders of time constants. The energy saving potential of the proposed approach is documented
via comparative simulation studies.

co-simulation, predictive control, heater dynamics