期刊
BUILDING AND ENVIRONMENT
卷 197, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.buildenv.2021.107830
关键词
Model predictive control; Field test; Optimization; Thermally activated building system (TABS); Modelica
Modern and energy-optimized buildings often lack an intelligent and advanced control strategy. Instead, conventional rule-based control strategies are still mainly used today, which do not exploit the full performance potential of these buildings. Model predictive control has shown promise in reducing energy consumption and improving occupants' comfort, especially in large-scale, fully occupied buildings.
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%.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据