Residential Demand Response - A Randomized Controlled Trial in California
Datong Zhou

Citation
Datong Zhou. "Residential Demand Response - A Randomized Controlled Trial in California". Talk or presentation, 24, August, 2017.

Abstract
Residential Demand Response has emerged as an instrument of the modern smart grid to alleviate supply and demand imbalances of electricity. Utilizing their flexibility of electricity demand, residential households are offered monetary incentives to temporarily reduce energy consumption during times when the grid is strained due to a supply shortage. In this paper, we estimate the effect of hour-ahead interventions of a Residential Demand Response program on the reduction of electricity consumption, using a large-scale Randomized Controlled Trial on residential households in California. In addition to estimating this effect with this experimental gold standard, we develop a non-experimental approach that allows for an estimation of the desired treatment effect on an individual level by estimating user-level counterfactuals using time-series prediction. This approach crucially eliminates the need for a randomized experiment, which in many settings is often hard to conduct due to financial and ethical constraints. Since both estimates are close to each other, we claim that this methodology can be applied to predict treatment effects of any future Demand Response program.

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Citation formats

• HTML

  Datong Zhou. <a
  href="http://www.cps-forces.org/pubs/280.html"
  ><i>Residential Demand Response - A Randomized
  Controlled Trial in California</i></a>, Talk or
  presentation,  24, August, 2017.

• Plain text

  Datong Zhou. "Residential Demand Response - A
  Randomized Controlled Trial in California". Talk or
  presentation,  24, August, 2017.

• BibTeX

  @presentation{Zhou17_ResidentialDemandResponseRandomizedControlledTrialIn,
      author = {Datong Zhou},
      title = {Residential Demand Response - A Randomized
                Controlled Trial in California},
      day = {24},
      month = {August},
      year = {2017},
      abstract = {Residential Demand Response has emerged as an
                instrument of the modern smart grid to alleviate
                supply and demand imbalances of electricity.
                Utilizing their flexibility of electricity demand,
                residential households are offered monetary
                incentives to temporarily reduce energy
                consumption during times when the grid is strained
                due to a supply shortage. In this paper, we
                estimate the effect of hour-ahead interventions of
                a Residential Demand Response program on the
                reduction of electricity consumption, using a
                large-scale Randomized Controlled Trial on
                residential households in California. In addition
                to estimating this effect with this experimental
                gold standard, we develop a non-experimental
                approach that allows for an estimation of the
                desired treatment effect on an individual level by
                estimating user-level counterfactuals using
                time-series prediction. This approach crucially
                eliminates the need for a randomized experiment,
                which in many settings is often hard to conduct
                due to financial and ethical constraints. Since
                both estimates are close to each other, we claim
                that this methodology can be applied to predict
                treatment effects of any future Demand Response
                program.},
      URL = {http://cps-forces.org/pubs/280.html}
  }
  

Posted by Carolyn Winter on 24 Aug 2017.
Groups: forces
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