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Review of data-driven models for quantifying load shed by non-residential buildings in the United States

Author

Listed:
  • Malhotra, Yashvi
  • Polly, Ben
  • MacDonald, Jason
  • Clark, Jordan D.

Abstract

Shifting and shedding power demand in buildings can be cost-effective techniques for grids to function reliably and for end users to earn compensation. Grid operators reimburse customers in proportion to the quantity of load shed. Simple data-driven methods are used to quantify this shed, which is the difference between a measured load during the event and modeled “baseline” that would have occurred in absence of the event. These methods have evolved over the years and in many cases have been integrated with building physics, to make them a hybrid between physics based and empirical models. However, there is no comprehensive analysis that provides guidance to building operators, grid operators and researchers in selecting appropriate models based on their specific needs and available data. This work aims to fill this gap by critically assessing the performance of baseline models put forward from the year 2000 through 2023. The literature reviewed includes reports generated by grid operators, reports from national laboratories and academic journal articles.

Suggested Citation

  • Malhotra, Yashvi & Polly, Ben & MacDonald, Jason & Clark, Jordan D., 2024. "Review of data-driven models for quantifying load shed by non-residential buildings in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 206(C).
    • Handle: RePEc:eee:rensus:v:206:y:2024:i:c:s1364032124005963
    DOI: 10.1016/j.rser.2024.114870
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