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Towards non-intrusive thermal load Monitoring of buildings: BES calibration

Author

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  • Enríquez, R.
  • Jiménez, M.J.
  • Heras, M.R.

Abstract

It is widely believed that smart metering will lead to high power savings. Those practices rely on Non-intrusive Appliance Load Monitoring (NIALM) methodologies. In this work an extension of NIALM to thermal loads is proposed: Non-intrusive Thermal Load Monitoring (NITLM). NIALM and NITLM share the same key point: a good model to calibrate loads. Thermal loads calibration is, at present, a task far from trivial.

Suggested Citation

  • Enríquez, R. & Jiménez, M.J. & Heras, M.R., 2017. "Towards non-intrusive thermal load Monitoring of buildings: BES calibration," Applied Energy, Elsevier, vol. 191(C), pages 44-54.
    • Handle: RePEc:eee:appene:v:191:y:2017:i:c:p:44-54
    DOI: 10.1016/j.apenergy.2017.01.050
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    Cited by:

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    2. Yan, Lei & Tian, Wei & Han, Jiayu & Li, Zuy, 2022. "Event-driven two-stage solution to non-intrusive load monitoring," Applied Energy, Elsevier, vol. 311(C).
    3. Wang, Shuangyuan & Li, Ran & Evans, Adrian & Li, Furong, 2020. "Regional nonintrusive load monitoring for low voltage substations and distributed energy resources," Applied Energy, Elsevier, vol. 260(C).
    4. Liu, Chao & Akintayo, Adedotun & Jiang, Zhanhong & Henze, Gregor P. & Sarkar, Soumik, 2018. "Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network," Applied Energy, Elsevier, vol. 211(C), pages 1106-1122.
    5. Edwards, Richard E. & New, Joshua & Parker, Lynne E. & Cui, Borui & Dong, Jin, 2017. "Constructing large scale surrogate models from big data and artificial intelligence," Applied Energy, Elsevier, vol. 202(C), pages 685-699.
    6. Shen, Pengyuan & Braham, William & Yi, Yunkyu, 2018. "Development of a lightweight building simulation tool using simplified zone thermal coupling for fast parametric study," Applied Energy, Elsevier, vol. 223(C), pages 188-214.
    7. Soutullo, S. & Giancola, E. & Heras, M.R., 2018. "Dynamic energy assessment to analyze different refurbishment strategies of existing dwellings placed in Madrid," Energy, Elsevier, vol. 152(C), pages 1011-1023.
    8. Garwood, Tom Lloyd & Hughes, Ben Richard & O'Connor, Dominic & Calautit, John K. & Oates, Michael R. & Hodgson, Thomas, 2018. "A framework for producing gbXML building geometry from Point Clouds for accurate and efficient Building Energy Modelling," Applied Energy, Elsevier, vol. 224(C), pages 527-537.
    9. Díaz, J.A. & Jiménez, M.J., 2017. "Experimental assessment of room occupancy patterns in an office building. Comparison of different approaches based on CO2 concentrations and computer power consumption," Applied Energy, Elsevier, vol. 199(C), pages 121-141.

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