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ABSTRACT

This paper investigates predictive control strategies applied to radiant floor heating system in a net-zero energy solar home. Control operations are performed by adjusting variables such as the temperature set-point, the radiant floor heating system's heat delivery rate, and the solar gains transmitted through the fenestration (for instance, by changing the position of motorized shading devices). The mathematical models used for the implementation of control strategies are simplified linear transfer function models, based on thermal networks models. The use of transfer function models, which can also be obtained from system identification of building simulation output data, considerably facilitates the implementation of computationally demanding control strategies. Applications of Model Predictive Control (MPC), a set of algorithms that employ a model of the system to predict its response to future disturbances, are presented and discussed. MPC techniques -or alternative predictive control algorithms- are necessary to manage the collection, storage and delivery of passive solar gains, and thus to regulate indoor temperatures and maintain comfortable indoor conditions for the occupants.