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Improving room temperature stability and operation efficiency using a model predictive control method for a district heating station
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DOI：10.1016/j.enbuild.2023.112990.png)
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Abstract
En 中文
In China, the regulation of a district heating (DH) station is mainly based on weather compensation con-trol. This control method leads to large room temperature fluctuations and high energy consumption as the regulation of supply water temperature is solely based on outdoor meteorological parameters, which the influence of pipe delay, thermal inertia of buildings, and indoor temperature were not considered. In this study, a model predictive control (MPC) method was adopted to achieve high room temperature sta-bility and high flexibility in DH station regulation. A dynamic model of the entire DH station, which con-siders the thermal inertia of buildings and delay of pipe, was established and verified using actual operation data. The performance of the MPC method was then evaluated and compared with that of the conventional control method (CCM) using the dynamic system model. When thermal comfort was considered as the single objective of the MPC, the optimal control step of the DH station was 8 h. The room temperature stability improved significantly as the room temperature fluctuation amplitude reduced from 2.64 degrees C to 0.35 degrees C. When thermal comfort and energy consumption were combined by the objective function, the MPC method could reduce the system energy consumption by 7.4 %. The MPC method could help improve the stability of the pipe network and had a strong anti-interference abil-ity. In practical applications, during the two years after renovation, energy consumption was reduced by 5.9 % and 7.9 %, respectively. Further, the thermal comfort rate of households was improved by 0.27 % and 0.03 %, with relative incomes of 0.72 yuan/m2 and 1.04 yuan/m2, respectively.(c) 2023 Elsevier B.V. All rights reserved.
Keywords:
District heating
Model predictive control
Thermal inertia
Thermal comfort
Energy saving
Journal
IF:
7.1
Papers:
1.5W
Citations:
6.8W