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Modeling industrial loads in non-residential buildings

Author

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  • Vaghefi, A.
  • Farzan, Farbod
  • Jafari, Mohsen A.

Abstract

Industrial loads in non-residential buildings have significantly contributed in total energy use throughout the world. This paper aims to develop a data-driven risk-based framework to predict and optimally control industrial loads in non-residential buildings. In the proposed framework, first, a set of predictive analytics tools are employed to identify the patterns of industrial loads over time. This also includes a high-dimensional clustering model to allocate industrial load profiles into smaller groups with less variability and same patterns. Once the patterns of industrial loads are identified, then a classification model is implemented to estimate the best class that matches with any new load profiles. Ultimately, the proposed framework provides a risk-based model to calculate and evaluate the total risk of energy decisions for the next day. This is coupled with a utility function structure to help decision makers to take best demand-side actions. The efficiency of the proposed model is investigated through a real world use case.

Suggested Citation

  • Vaghefi, A. & Farzan, Farbod & Jafari, Mohsen A., 2015. "Modeling industrial loads in non-residential buildings," Applied Energy, Elsevier, vol. 158(C), pages 378-389.
    • Handle: RePEc:eee:appene:v:158:y:2015:i:c:p:378-389
    DOI: 10.1016/j.apenergy.2015.08.077
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    References listed on IDEAS

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    Cited by:

    1. Gourlis, Georgios & Kovacic, Iva, 2016. "A study on building performance analysis for energy retrofit of existing industrial facilities," Applied Energy, Elsevier, vol. 184(C), pages 1389-1399.
    2. Alhamwi, Alaa & Medjroubi, Wided & Vogt, Thomas & Agert, Carsten, 2018. "Modelling urban energy requirements using open source data and models," Applied Energy, Elsevier, vol. 231(C), pages 1100-1108.
    3. Brinks, Pascal & Kornadt, Oliver & Oly, René, 2016. "Development of concepts for cost-optimal nearly zero-energy buildings for the industrial steel building sector," Applied Energy, Elsevier, vol. 173(C), pages 343-354.

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