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The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  1. Lu, Yakai / Peng, Xingyu / Li, Conghui / Tian, Zhe / Niu, Jide / Liang, Chuanzhi (2024): A baseline model combining physics and data-driven approach for operation evaluation of district heating substation. In: Energy and Buildings, v. 321 (October 2024).

    https://doi.org/10.1016/j.enbuild.2024.114582

  2. Wu, Xia / Niu, Jide / Tian, Zhe / Li, Xiaoyuan (2024): An evidence theory-based uncertainty quantification method of building thermal parameters for accurate reliability assessment of building air-conditioning design loads. In: Energy and Buildings, v. 319 (September 2024).

    https://doi.org/10.1016/j.enbuild.2024.114424

  3. Yue, Lu / Niu, Jide / Tian, Zhe / Lin, Quanyi / Lu, Yakai (2024): A comprehensive evaluation framework for building energy systems considering economic efficiency, independence, and building–grid interaction performance indicators. In: Energy and Buildings, v. 318 (September 2024).

    https://doi.org/10.1016/j.enbuild.2024.114414

  4. Lin, Xinyi / Tian, Zhe / Song, Wenjie / Lu, Yakai / Niu, Jide / Sun, Qiang / Wang, Yanan (2024): Grey-box modeling for thermal dynamics of buildings under the presence of unmeasured internal heat gains. In: Energy and Buildings, v. 314 (July 2024).

    https://doi.org/10.1016/j.enbuild.2024.114229

  5. Yue, Lu / Niu, Jide / Tian, Zhe / Lin, Quanyi / Lu, Yakai (2024): A three-dimensional evaluation method for building energy systems to guide power grid-friendly interactions during the planning and operational stages. In: Journal of Building Engineering, v. 86 (June 2024).

    https://doi.org/10.1016/j.jobe.2024.108816

  6. Wu, Xia / Tian, Zhe / Niu, Jide / Li, Xiaoyuan (2023): Hybrid uncertainty quantification method of internal disturbance parameters for reliability assessment of building air-conditioning design load. In: Energy and Buildings, v. 299 (November 2023).

    https://doi.org/10.1016/j.enbuild.2023.113602

  7. Tian, Zhe / Song, Wenjie / Lu, Yakai / Lin, Xinyi / Niu, Jide (2023): Load extraction from actual operation data for data-driven ultra-short-term room air-conditioning load prediction. In: Energy and Buildings, v. 296 (October 2023).

    https://doi.org/10.1016/j.enbuild.2023.113348

  8. Zhang, Qiang / Tian, Zhe / Lu, Yakai / Niu, Jide / Ye, Chuang (2023): Experimental study on performance assessments of HVAC cross-domain fault diagnosis methods oriented to incomplete data problems. In: Building and Environment, v. 236 (May 2023).

    https://doi.org/10.1016/j.buildenv.2023.110264

  9. Niu, Jide / Zhou, Ruoyu / Tian, Zhe / Zhu, Jie / Lu, Yakai / Ma, Jianbo (2023): Energy-saving potential analysis for a 24-hour operating chiller plant using the model-based global optimization method. In: Journal of Building Engineering, v. 69 (June 2023).

    https://doi.org/10.1016/j.jobe.2023.106213

  10. Wu, Xia / Niu, Jide / Tian, Zhe / Zhou, Ruoyu / Hou, Xinyang (2023): A stochastic interior disturbance parameter model considering double uncertainty for probabilistic load calculation. In: Energy and Buildings, v. 285 (April 2023).

    https://doi.org/10.1016/j.enbuild.2023.112883

  11. Tian, Zhe / Lin, Xinyi / Lu, Yakai / Song, Wenjie / Niu, Jide (2023): Imbalanced data-oriented model learning method for ultra-short-term air conditioning load prediction. In: Energy and Buildings, v. 286 (May 2023).

    https://doi.org/10.1016/j.enbuild.2023.112931

  12. Zhang, Qiang / Tian, Zhe / Niu, Jide / Zhu, Jie / Lu, Yakai (2022): A study on transfer learning in enhancing performance of building energy system fault diagnosis with extremely limited labeled data. In: Building and Environment, v. 225 (November 2022).

    https://doi.org/10.1016/j.buildenv.2022.109641

  13. Wu, Xia / Niu, Jide / Tian, Zhe / Hou, Xinyang / Zhou, Ruoyu (2022): Method of constructing stochastic near-extreme daily weather data for efficient calculation of probabilistic load in air-conditioning system design. In: Building and Environment, v. 221 (August 2022).

    https://doi.org/10.1016/j.buildenv.2022.109278

  14. Hou, Xinyang / Tian, Zhe / Niu, Jide / Wu, Xia / Lu, Yakai (2022): Research on design day generation method for air-conditioning system design considering the coincidence of hourly variation coefficient. In: Energy and Buildings, v. 270 (September 2022).

    https://doi.org/10.1016/j.enbuild.2022.112300

  15. Lin, Xinyi / Tian, Zhe / Lu, Yakai / Niu, Jide / Cao, Yaqi (2022): An energy performance assessment method for district heating substations based on energy disaggregation. In: Energy and Buildings, v. 255 (January 2022).

    https://doi.org/10.1016/j.enbuild.2021.111615

  16. Lan, Bo / Tian, Zhe / Niu, Jide / Wang, Weizhang / Lu, Shichao (2020): Applicability analysis of solar heating system in China based on a reliability-based optimization method for auxiliary heater capacity. In: Sustainable Cities and Society, v. 53 (February 2020).

    https://doi.org/10.1016/j.scs.2019.101930

  17. Tian, Zhe / Duan, Baodong / Niu, Xiaolei / Hu, Qi / Niu, Jide (2014): Establishment and experimental validation of a dynamic heat transfer model for concrete radiant cooling slab based on reaction coefficient method. In: Energy and Buildings, v. 82 (October 2014).

    https://doi.org/10.1016/j.enbuild.2014.07.031

  18. Lan, Bo / Tian, Zhe / Niu, Jide / Sun, Wei (2020): Improving the design method of a solar heating system considering weather uncertainty and system reliability. In: Energy and Buildings, v. 208 (February 2020).

    https://doi.org/10.1016/j.enbuild.2019.109606

  19. Lu, Yakai / Tian, Zhe / Peng, Peng / Niu, Jide / Dai, Jiping (2019): Identification and evaluation of operation regulation strategies in district heating substations based on an unsupervised data mining method. In: Energy and Buildings, v. 202 (November 2019).

    https://doi.org/10.1016/j.enbuild.2019.07.041

  20. Lu, Yakai / Tian, Zhe / Peng, Peng / Niu, Jide / Li, Wancheng / Zhang, Hejia (2019): GMM clustering for heating load patterns in-depth identification and prediction model accuracy improvement of district heating system. In: Energy and Buildings, v. 190 (May 2019).

    https://doi.org/10.1016/j.enbuild.2019.02.014

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