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Development of the heating load prediction model for the residential building of district heating based on model calibration

机译：基于模型校准的地区加热住宅建设的加热负荷预测模型的发展

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摘要

Heating load prediction of district heating (DH) can give the heating demand, guide the strategies formulation and avoid excessive heat. However, existing prediction models from the supply side are to learn historical inefficient operations and have no energy-saving effect. Therefore, this study proposes the demand-side method, which predicts the heating load of terminal buildings considering influence of indoor temperature. Dynamic and steady-state white box model are taken as prediction techniques due to inapplicability of data-driven model, and model calibration is used to match the models accurately with the actual. Taking an actual residential building as the case, and the results show steady-state model has application advantages over dynamic model due to the greatly reduced calculation time under the situation of limited known information, although the accuracy of dynamic model is slightly better than that of steady-state model. The steady-state model can predict the heating load under different indoor temperature. The energy-saving rate reducing the actual indoor temperature to 18 °C is 11%-27% for different periods of a heating season. The method is a novel way to conduct load prediction for DH with energy-saving effect, and provides a meaningful basis for formulating heating strategies.
机译：地区供暖（DH）的加热负荷预测可提供加热需求，引导策略配方，避免过热。然而，来自供应方的现有预测模型是学习历史低效操作并且没有节能效果。因此，本研究提出了需求侧方法，其考虑对室内温度的影响，预测了端子建筑的加热负荷。动态且稳态白盒模型被视为由于数据驱动模型的不适用性的预测技术，而模型校准用于使用实际准确地匹配模型。以实际的住宅建筑为例，结果显示稳态模型具有在动态模型上具有应用优势，因为在已知信息的情况下的情况下的情况大大降低，尽管动态模型的准确性略好于此稳态模型。稳态模型可以预测不同室内温度下的加热负荷。在加热季节的不同时期，节能率降低到18°C的实际室内温度为11％-27％。该方法是一种新的方法，用于对DH进行DH的负载预测，并为制定加热策略提供有意义的基础。

著录项

  • 来源
    《Energy》 |2020年第15期|117949.1-117949.13|共13页
  • 作者

    Qiang Zhang; Zhe Tian; Zhijun Ma; Genyan Li; Yakai Lu; Jide Niu;

  • 作者单位

    School of Environmental Science and Engineering Tianjin University Tianjin 300072 China;

    School of Environmental Science and Engineering Tianjin University Tianjin 300072 China Key Laboratory of Efficient Utilization of Low and Medium Grade Energy MOE Tianjin University Tianjin 300072 China;

    Thermal Branch of State Power Investment Group Dongfang New Energy Co. Ltd Shijiazhuang 050018 China;

    Thermal Branch of State Power Investment Group Dongfang New Energy Co. Ltd Shijiazhuang 050018 China;

    School of Environmental Science and Engineering Tianjin University Tianjin 300072 China;

    School of Environmental Science and Engineering Tianjin University Tianjin 300072 China;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Model calibration; District heating; Heating load prediction; Residential buildings; White box models;

    机译：模型校准;区域供热;加热负荷预测;住宅楼;白色盒式模型;

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