Results of the Implementation of Model Predictive Control in a Large Administrative Building for Energy Efficiency and Comfort Optimization

This paper presents the results from a practical implementation of a Model Predictive Control (MPC) strategy in a large administrative building, aiming to optimize both thermal comfort and energy efficiency of the building. The core of this control strategy consists of zones models that describe the thermal and dynamic behavior of individual reference zones within the building. A hybrid gray-box modeling approach is used, combining a simplified physics-based model structure with a parameter identification using data collected from the building operation. The MPC controller was implemented in multiple sections of the building during a six-month period, controlling the supply temperature and pumps of heating circuits for thermally activated building systems (TABS). Compared to the default conventional control strategy, a monthly average saving in heating energy in the range of 5 % to 42 % can be measured during the test periods. Furthermore, an improvement in thermal comfort compared to the previous operational years can also be demonstrated. In the reference zones, a significantly higher proportion of indoor air conditions within the highest comfort category according to DIN EN 16798 is achieved.

DDC Class

620: Engineering

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Results of the Implementation of Model Predictive Control in a Large Administrative Building for Energy Efficiency and Comfort Optimization