Research on heat consumption detection, restoration and prediction methods for discontinuous heating substation

Ke Huang, Shilei Lu, Zhao Han and Jianjuan Yuan

Energy, 2023, vol. 266, issue C

Abstract: Under the goal of low-carbon heating, the control modes of heating substation will develop from traditional continuous heating to discontinuous heating, indicating that the existing methods for detection, restoration and prediction are not applicable. Based on data-knowledge analysis, this paper conducts a systematic study. Firstly, the associated parameters of the control mode were determined according to professional knowledge, including date, daily heat consumption and standard deviation, and the control mode of discontinuous heating substation was successfully identified by K-means. Secondary, by analyzing the internal heating parameters affecting the changing of heat consumption, the detection methods for different types of abnormal data are proposed. Thirdly, the restoration effect of statistics methods and Data-driven methods on abnormal data are compared, and data-driven methods with input parameters of secondary supply temperature, return temperature and temperature difference can successfully restore different abnormal heat consumption with an average error of less than 5%. Finally, the input parameters for heat consumption prediction of discontinuous heating stations, including outdoor temperature, time point and secondary return temperature were determined, and extreme gradient boosting had a higher prediction accuracy than support vector machine and multiple linear regression, with R2 >0.85.

Keywords: Discontinuous heating; Detection method; Restoration method; Prediction methods; Machine learning methods (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:266:y:2023:i:c:s0360544223000026

DOI: 10.1016/j.energy.2023.126608

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