Abstract
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%.
Highlights
Against the background of the environmental impact of energy use, the depletion of primary energy resources and the associated economic consequences, considerable efforts are being made to realize environmentally-friendly and energy-efficient buildings
The full potential of these buildings is not exploited. This is especially true for non-residential buildings such as large office buildings, which are equipped with complex hybrid energy supply systems and multiple heat distribution systems with different time constants, such as thermally activated building systems (TABS), floor heating, radiators and air-handling units (AHU) [3]
The proposed Model predictive control (MPC) controller was implemented in the low-rise building section G and substituted the rule-based control (RBC) of the two existing thermoactive ceilings (TAC) heating circuits in this building section
Summary
Against the background of the environmental impact of energy use, the depletion of primary energy resources and the associated economic consequences, considerable efforts are being made to realize environmentally-friendly and energy-efficient buildings. The implementation of MPC is in practice still far from trivial [6] This is due to the fact that each building is unique with regard to its construction, its subsystems and its hardware and software solutions, requiring a tailored design of advanced, model-based control strategies. This paper presents a three-month field test demonstration of MPC in a modern large-sized, energy-efficient office building in Hamburg, Germany. A gray-box model approach in combination with a dedicated parameter identification method is chosen to describe the dynamic thermal behavior of building zones These gray-box models are implemented in the equation-based modeling language Modelica [18] which allows easy formulation and efficient solution of non-linear optimization problems [19]. The unique experimental setup allows a detailed comparison of MPC and RBC controlled building sections under identical environmental and operational conditions, with regard to heating energy demand and thermal comfort. Width Clear height Floor area External wall area U-value glazing U-value facade m m m2 m2 W m−2 K−1 W m−2 K−1
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