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Cooperative consumers in a deregulated electricity market — dynamic consumption strategies and price coordination

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  • Hämäläinen, Raimo P
  • Mäntysaari, Juha
  • Ruusunen, Jukka
  • Pierre-Olivier Pineau,

Abstract

As the trend in electricity markets is strongly towards deregulation, new players, new rules and new behaviors will continue to emerge. One of the new developments on the demand side is purchases made by a coalition of consumers. It seems indeed likely that in the future this will be more common, and that coalitions of consumers will emerge when they are worthwhile. The aim of this paper is to study how such an organization of consumers can be set up in a hierarchical framework. This new approach has not been described before in the deregulated electricity markets but is clearly an important research topic. We focus our interest on electric space heating, which is an energy need especially important in the Nordic countries such as Finland. We examine the consumption strategies of individual electricity buyers within a coalition. The decision problem all consumers face is to find the optimal use of their space heating system with respect to changes in electricity prices and to their tolerance to indoor temperature variation. A mathematical model for this problem is defined. Physical parameters of sample houses were gathered from an experimental field test conducted in Helsinki during the winter of 1996. The coalition buys in the market at marginal cost. However, as marginal cost pricing may not always fulfill metering and communication needs of the members of the coalition, we consider Time-Of-Use (TOU) pricing within the coalition. Different groups of consumer behavior are constructed to simulate this coalition. The optimal marginal price is used as a reference point to estimate the nearest TOU price within the coalition.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:25:y:2000:i:9:p:857-875
    DOI: 10.1016/S0360-5442(00)00024-4
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    1. repec:aen:journl:1997v18-04-a05 is not listed on IDEAS
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    1. Hamalainen, Raimo P. & Mantysaari, Juha, 2002. "Dynamic multi-objective heating optimization," European Journal of Operational Research, Elsevier, vol. 142(1), pages 1-15, October.
    2. Moreno, Blanca & López, Ana J. & García-Álvarez, María Teresa, 2012. "The electricity prices in the European Union. The role of renewable energies and regulatory electric market reforms," Energy, Elsevier, vol. 48(1), pages 307-313.
    3. Fuentes, Rolando & Sengupta, Abhijit, 2020. "Using insurance to manage reliability in the distributed electricity sector: Insights from an agent-based model," Energy Policy, Elsevier, vol. 139(C).
    4. Ringler, Philipp & Keles, Dogan & Fichtner, Wolf, 2016. "Agent-based modelling and simulation of smart electricity grids and markets – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 205-215.
    5. Luthander, Rasmus & Widén, Joakim & Munkhammar, Joakim & Lingfors, David, 2016. "Self-consumption enhancement and peak shaving of residential photovoltaics using storage and curtailment," Energy, Elsevier, vol. 112(C), pages 221-231.
    6. Palander, Teijo, 2011. "Technical and economic analysis of electricity generation from forest, fossil, and wood-waste fuels in a Finnish heating plant," Energy, Elsevier, vol. 36(9), pages 5579-5590.
    7. Cong, Rong-Gang & Wei, Yi-Ming, 2010. "Potential impact of (CET) carbon emissions trading on China’s power sector: A perspective from different allowance allocation options," Energy, Elsevier, vol. 35(9), pages 3921-3931.
    8. Palander, Teijo, 2011. "Modelling renewable supply chain for electricity generation with forest, fossil, and wood-waste fuels," Energy, Elsevier, vol. 36(10), pages 5984-5993.
    9. Weidlich, Anke & Veit, Daniel, 2008. "A critical survey of agent-based wholesale electricity market models," Energy Economics, Elsevier, vol. 30(4), pages 1728-1759, July.

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