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Evaluating user understanding and exposure effects of demand-based tariffs

Author

Listed:
  • El Gohary, F.
  • Nordin, M.
  • Juslin, P.
  • Bartusch, C.

Abstract

Conventionally, demand response functions by communicating to electricity users through price signals embedded in their tariffs. These signals are intended to encourage a change in behavior, which hinges on the ability of users to understand their tariff and link it to the appropriate curtailment actions. This study focuses on demand-based tariffs, evaluating user's understanding of these tariffs and the conceptual grasp of power (rate of energy consumption) that they implicitly require. It also explores whether users exposed to these tariffs for extended periods develop a better understanding of them. Using a survey, the following points are sequentially evaluated: (1) Respondents' abilities to intuitively distinguish between energy/power (2) Their understanding of the different effects of curtailment actions under four distinct tariffs (3) Whether those subject to demand-based pricing outperform those subject to energy-based pricing. Despite a weaker conceptual understanding of power compared to energy, there were no significant differences between respondents' understanding of energy and demand-based tariffs. Comparing those subject to energy and demand-based pricing reveals that a majority were unaware of their own tariff (and hence which group they fall into), but for the minority of users who correctly identified their own tariffs, those subject to demand-based pricing outperform their energy-based counterparts. When presented with clear and instructive tariffs, respondents are largely able to deduce the consequences of curtailment actions, despite a weak conceptual understanding of power. A deeper problem is that the price signal may be entirely disregarded by an apathetic majority, reaching only an inquisitive minority.

Suggested Citation

  • El Gohary, F. & Nordin, M. & Juslin, P. & Bartusch, C., 2022. "Evaluating user understanding and exposure effects of demand-based tariffs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
  • Handle: RePEc:eee:rensus:v:155:y:2022:i:c:s1364032121012211
    DOI: 10.1016/j.rser.2021.111956
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    References listed on IDEAS

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    1. Hainmueller, Jens, 2012. "Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies," Political Analysis, Cambridge University Press, vol. 20(1), pages 25-46, January.
    2. Dütschke, Elisabeth & Paetz, Alexandra-Gwyn, 2013. "Dynamic electricity pricing—Which programs do consumers prefer?," Energy Policy, Elsevier, vol. 59(C), pages 226-234.
    3. Bradley, Peter & Coke, Alexia & Leach, Matthew, 2016. "Financial incentive approaches for reducing peak electricity demand, experience from pilot trials with a UK energy provider," Energy Policy, Elsevier, vol. 98(C), pages 108-120.
    4. Kim, Jin-Ho & Shcherbakova, Anastasia, 2011. "Common failures of demand response," Energy, Elsevier, vol. 36(2), pages 873-880.
    5. Gyamfi, Samuel & Krumdieck, Susan & Urmee, Tania, 2013. "Residential peak electricity demand response—Highlights of some behavioural issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 71-77.
    6. Torriti, Jacopo & Hassan, Mohamed G. & Leach, Matthew, 2010. "Demand response experience in Europe: Policies, programmes and implementation," Energy, Elsevier, vol. 35(4), pages 1575-1583.
    7. Schlereth, Christian & Skiera, Bernd & Schulz, Fabian, 2018. "Why do consumers prefer static instead of dynamic pricing plans? An empirical study for a better understanding of the low preferences for time-variant pricing plans," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1165-1179.
    8. Goutam Dutta & Krishnendranath Mitra, 2017. "A literature review on dynamic pricing of electricity," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1131-1145, October.
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