Implementation of model predictive control in a large-sized, low-energy office building

Modern and energy-optimized buildings often lack an intelligent and advanced control strategy. Instead, conventional rule-based control (RBC) strategies are still mainly used today, which do not exploit the full performance potential of these buildings. Model predictive control (MPC) has proven in simulation studies and pilot cases to be a promising approach to reduce the energy consumption of buildings, while improving occupants’ comfort. However, there is still a lack of implementing MPC in real, large-scale and fully occupied buildings, to further prove this potential in real building operations. This paper describes the implementation and operation of MPC in a large-sized, low-energy office building. The MPC controller was implemented in a section of the building during a three-month test period from February to April 2020, controlling the supply temperature of heating circuits for thermally activated building systems (TABS). Its performance was compared to the default rule-based control which is active in the other building sections. This allows for a detailed evaluation of MPC versus RBC under identical environmental and operational conditions. The MPC controlled building section used 30% less heating energy than RBC controlled building sections, while the existing high level of thermal comfort could be maintained. Especially in transition periods (i. e. interseasonal periods like late winter/early spring), the MPC is superior to the conventional heating-curve based control strategy, with heating energy savings of 75%.

Subjects

Field test

Model predictive control

Modelica

Optimization

Thermally activated building system (TABS)

DDC Class

600: Technik

Publication version

publishedVersion

Lizenz

https://creativecommons.org/licenses/by/4.0/

Name

1-s2.0-S0360132321002365-main.pdf

Size

2.01 MB

Format

Adobe PDF

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Implementation of model predictive control in a large-sized, low-energy office building