Improving room temperature stability and operation efficiency using a model predictive control method for a district heating station

模型预测控制 灵活性(工程) 能源消耗 热舒适性 理论(学习稳定性) 补偿(心理学) 温度控制 惯性 环境科学 热的 高效能源利用 汽车工程 控制(管理) 工程类 控制理论(社会学) 计算机科学 气象学 控制工程 电气工程 数学 人工智能 机器学习 心理学 统计 物理 经典力学 精神分析
作者
Zhiwei Li,Junjie Liu,Lizhi Jia,Yanmin Wang
出处
期刊:Energy and Buildings [Elsevier BV]
卷期号:287: 112990-112990 被引量:14
标识
DOI:10.1016/j.enbuild.2023.112990
摘要

In China, the regulation of a district heating (DH) station is mainly based on weather compensation control. 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 stability and high flexibility in DH station regulation. A dynamic model of the entire DH station, which considers 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 °C to 0.35 °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 ability. 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.

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