Management of hybrid energy supply systems in buildings using mixed-integer model predictive control. (1st July 2015) - Mayer, Barbara; Killian, Michaela; Kozek, Martin
Graphical abstract: Highlights: Management of a heating supply system for buildings with storage tank is optimized. Mixed-integer model predictive controller for hybrid energy supply is proposed. Efficient management of a stratified storage tank is provided. Unit commitment problem with switching heat pump is solved for heat load prediction. Excellent and robust performance is guaranteed by extensive analysis of parameters. Abstract: In this paper a mixed-integer model predictive controller for hybrid energy supply systems in buildings is presented. This approach is based on a hierarchical building control concept where the energy supply level is coupled to the energy consumption level only by the heat load. The supply level is characterized by non-linear dynamics due to a stratified water storage tank and a switched heat pump with minimum on/off times. The mixed-integer model predictive controller optimizes the unit commitment problem at minimum costs while satisfying the consumption level's predicted heat load. The hybrid system is formulated as a piecewise affine model comprising continuous and discrete system inputs. Moreover, the proposed controller is able to manage the stratified storage tank including switching sequences of the heat pump with respect to energy price forecasts. The effectiveness of this approach is shown by a comparison to a model predictive controller with an a priori fixed operation mode profile, where the heat pump is only operating at night, and discussing the effect of the variation of the stratified storage tank size. The proposed concept is able to flexibly manage all sizes of stratified storage tanks with better performance than the reference control strategy, which is only effective for larger tanks. Additionally, a robustness analyses demonstrates that the mixed-integer model predictive controller can handle errors in the heat load prediction from the consumption level. Both analyses show promising results for the practical use of the proposed controller within the hierarchical control concept or as a control module in a similar but more general application.