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Journal of System Simulation

Abstract

Abstract: Based on the model predictive control method, this paper uses the discrete controlled autoregressive model to establish the dynamic heat transfer delay model of the secondary network and the thermal station model. The polynomial fitting method of machine learning algorithm is applied to identify and calibrate the parameters of the secondary network model and the thermal station model. The primary flow rate of the heating station under future operating conditions is predicted based on the model results, which provides a basis for the quality-based regulation of heating system. The model is verified by measured data, and the actual deviation is less than 5%, which provides a good guide for the engineering practice of heating system flow regulation.

First Page

180

Revised Date

2019-08-31

Last Page

188

CLC

TP18

Recommended Citation

Li Zhongbo, Jia Meng, Kang Yan, Wang Haihong, Li Miao, Lü Qing, Xie Jingjing, Fang Dajun. Real-Time Prediction of Primary Flow by MPC Method in Heating System[J]. Journal of System Simulation, 2021, 33(1): 180-188.

Corresponding Author

Dajun Fang,

DOI

10.16182/j.issn1004731x.joss.19-0148

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