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Customer level analysis of dynamic pricing experiments using consumption-pattern models

Author

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  • Räsänen, Mika
  • Ruusunen, Jukka
  • Hämäläinen, Raimo P.

Abstract

In the development of new tariffs, customer diversity should be taken into account to achieve more efficient demand-side management goals. This means that customers' reactions to rate changes need to be analysed at an individual customer level. We use daily consumption pattern (DCP) models for the analysis of rate effects. The DCP is assumed to consist of the daily rhythm of consumption, the effects of outdoor temperature on consumption and random variations. The models are tested with data from a Finnish dynamic pricing experiment. We show how the models are used for grouping of customers according to their DCPs and for estimating the customers' price responses to different rates. The results verify that customer-level load analysis is required, since the effects of rate changes on the DCP can vary considerably from one customer to another.

Suggested Citation

  • Räsänen, Mika & Ruusunen, Jukka & Hämäläinen, Raimo P., 1995. "Customer level analysis of dynamic pricing experiments using consumption-pattern models," Energy, Elsevier, vol. 20(9), pages 897-906.
    • Handle: RePEc:eee:energy:v:20:y:1995:i:9:p:897-906
    DOI: 10.1016/0360-5442(95)00029-G
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    Cited by:

    1. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    2. Christensen, Toke Haunstrup & Friis, Freja & Bettin, Steffen & Throndsen, William & Ornetzeder, Michael & Skjølsvold, Tomas Moe & Ryghaug, Marianne, 2020. "The role of competences, engagement, and devices in configuring the impact of prices in energy demand response: Findings from three smart energy pilots with households," Energy Policy, Elsevier, vol. 137(C).
    3. Römer, Benedikt & Reichhart, Philipp & Kranz, Johann & Picot, Arnold, 2012. "The role of smart metering and decentralized electricity storage for smart grids: The importance of positive externalities," Energy Policy, Elsevier, vol. 50(C), pages 486-495.
    4. Hamalainen, Raimo P. & Mantysaari, Juha, 2002. "Dynamic multi-objective heating optimization," European Journal of Operational Research, Elsevier, vol. 142(1), pages 1-15, October.
    5. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    6. Hämäläinen, Raimo P & Mäntysaari, Juha & Ruusunen, Jukka & Pierre-Olivier Pineau,, 2000. "Cooperative consumers in a deregulated electricity market — dynamic consumption strategies and price coordination," Energy, Elsevier, vol. 25(9), pages 857-875.
    7. Keppo, Jussi & Rasanen, Mika, 1999. "Pricing of electricity tariffs in competitive markets," Energy Economics, Elsevier, vol. 21(3), pages 213-223, June.
    8. 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.
    9. Rasanen, Mika & Ruusunen, Jukka & Hamalainen, Raimo P., 1997. "Optimal tariff design under consumer self-selection," Energy Economics, Elsevier, vol. 19(2), pages 151-167, May.

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