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A subspace based method for modelling building’s thermal dynamic in district heating system and parameter extrapolation verification

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  • Advances in Modeling and Simulation Tools
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Abstract

The district heating system (DHS) consumes a lot of energy in winter, and its control accuracy needs to be improved urgently. To apply advanced process control (APC) in DHS, the thermal dynamic model of the existing buildings is essential. This paper uses the subspace method which is a data-driven approach for modelling the thermal dynamics of the building. The model’s performance is analyzed using the collected data, and the differences compared to the classical methods are also analyzed. The method reduces the RMSE by about 20% compared with the ARX model for the same complexity. Subsequently, the analysis of the training residuals indicates that the estimate of periodic intra-building disturbance can be obtained by minimizing the training residuals. By introducing the estimated disturbance function, the RMSE on the test set is further reduced by 26%. At the end of the article, a simple parameter extrapolation experiment is conducted, and the result shows that the parameters can be extrapolated to other buildings without large errors.

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Abbreviations

APC:

advanced process control

ARX:

auto regressive with exogenous inputs

CHP:

combined heat and power

DHS:

district heating system

HVAC:

heating, ventilation and air-conditioning

IoT:

Internet of things

MPC:

model (based) predictive control

SVD:

singular value decomposition

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Authors and Affiliations

  1. University of Science and Technology Beijing, 30 Xueyuan Road, Beijing, 100083, China

    Junfeng Zhang & Lanbin Liu

  2. Beijing Nuanliu Technology Co., Ltd., Beijing, 100083, China

    Yameng Liu

Authors
  1. Junfeng Zhang
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  2. Lanbin Liu
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  3. Yameng Liu
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Correspondence to Lanbin Liu.

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Zhang, J., Liu, L. & Liu, Y. A subspace based method for modelling building’s thermal dynamic in district heating system and parameter extrapolation verification. Build. Simul. 16, 2145–2158 (2023). https://doi.org/10.1007/s12273-023-1002-8

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  • DOI: https://doi.org/10.1007/s12273-023-1002-8

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