Beyond theory : the challenge of implementing Model Predictive Control in buildings Ji ř

Model Predictive Control (MPC) of buildings has gained lot of attention in the recent years. Several research projects have demonstrated that MPC can provide substantial energy savings and improve indoor comfort as compared to traditional control approaches. However, the application of MPC requires extensive knowledge in the areas of mathematical and computer modeling, hardand software systems, data processing, and optimal control. Therefore its application implies considerable additional cost. The key issue is if corresponding energy savings and comfort improvements can balance this cost. The present paper discusses challenges encountered during the implementation of MPC in two different pilot case studies. The first study focuses on a 50 years old building with Thermally Activated Building Systems (TABS), while the second one deals with a newly built office building. Our experience suggests that a simple (not to be confounded with simplistic) model is sufficient to economically operate MPC on a building. However, firm guidelines allowing investors to assess whether it is worth to embark in MPC for a particular building are still lacking. In our opinion the situation could be much improved if building control would be considered already at the very early stages of the building and technical systems design. In this case we believe that MPC presents an attractive option for optimal supervisory control, in particular for buildings with large thermal

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