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Using insurance to manage reliability in the distributed electricity sector: Insights from an agent-based model

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  • Fuentes, Rolando
  • Sengupta, Abhijit

Abstract

High penetration of distributed technologies would call for a different way to manage electricity reliability for semi-independent households. One option could be to allow customers to withdraw power from the grid when their home system fails. This behavior, however, could constitute an existential threat for utilities: if consumers use the network less, and continue to pay according to their usage, the utility might be unable to recover its costs. This paper investigates whether the creation of a reliability insurance market would help to deal with these concerns. We propose a business model where utilities offer insurance to semi-independent, yet risk averse households, against the prospect of a blackout, when a pay as you go system is no longer available. With the use of an Agent Based Model, we test if contracts from this market can converge into a theoretical optimal contract where bounded perception of risks and losses impact the price of insurance and potential revenues of utilities. We find that such a market could exist as consumers efficiently transfer all or a portion of their risk to the utility, based on their willingness to pay and risk profiles, which allows them to avoid blackouts at the margin.

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  • 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).
    • Handle: RePEc:eee:enepol:v:139:y:2020:i:c:s0301421520300136
    DOI: 10.1016/j.enpol.2020.111251
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    1. Richard Green and Iain Staffell, 2017. "Prosumage and the British Electricity Market," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    2. Muller, Moritz & Sensfu[ss], Frank & Wietschel, Martin, 2007. "Simulation of current pricing-tendencies in the German electricity market for private consumption," Energy Policy, Elsevier, vol. 35(8), pages 4283-4294, August.
    3. Goerlich, Roland & Wirl, Franz, 2012. "Interdependencies between transport fuel demand, efficiency and quality: An application to Austria," Energy Policy, Elsevier, vol. 41(C), pages 47-58.
    4. Koesrinartoto, D. & Sun, Junjie & Tesfatsion, Leigh, 2005. "An agent-based computational laboratory for testing the economic reliability of wholesale power market designs," ISU General Staff Papers 200501010800001043, Iowa State University, Department of Economics.
    5. Stephenson, Janet & Barton, Barry & Carrington, Gerry & Gnoth, Daniel & Lawson, Rob & Thorsnes, Paul, 2010. "Energy cultures: A framework for understanding energy behaviours," Energy Policy, Elsevier, vol. 38(10), pages 6120-6129, October.
    6. 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.
    7. Bower, John & Bunn, Derek, 2001. "Experimental analysis of the efficiency of uniform-price versus discriminatory auctions in the England and Wales electricity market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 561-592, March.
    8. I.O. Walker & Franz Wirl, 1993. "Irreversible Price-Induced Efficiency Improvements: Theory and Empirical Application to Road Transportation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 183-205.
    9. Hunt, Lester C. & Ryan, David L., 2015. "Economic modelling of energy services: Rectifying misspecified energy demand functions," Energy Economics, Elsevier, vol. 50(C), pages 273-285.
    10. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    11. Fuentes, Rolando & Blazquez, Jorge & Adjali, Iqbal, 2019. "From vertical to horizontal unbundling: A downstream electricity reliability insurance business model," Energy Policy, Elsevier, vol. 129(C), pages 796-804.
    12. 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.
    13. John Bower & Derek W. Bunn, 2000. "Model-Based Comparisons of Pool and Bilateral Markets for Electricity," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-29.
    14. 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.
    15. Gottwalt, Sebastian & Ketter, Wolfgang & Block, Carsten & Collins, John & Weinhardt, Christof, 2011. "Demand side management—A simulation of household behavior under variable prices," Energy Policy, Elsevier, vol. 39(12), pages 8163-8174.
    16. Bower, John & Bunn, Derek W. & Wattendrup, Claus, 2001. "A model-based analysis of strategic consolidation in the German electricity industry," Energy Policy, Elsevier, vol. 29(12), pages 987-1005, October.
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    1. Farhad Billimoria & Filiberto Fele & Iacopo Savelli & Thomas Morstyn & Malcolm McCulloch, 2021. "On the Design of an Insurance Mechanism for Reliability Differentiation in Electricity Markets," Papers 2106.14351, arXiv.org.
    2. Chi-Keung Woo & Jay Zarnikau & Asher Tishler & Kang Hua Cao, 2022. "Insuring a Small Retail Electric Provider’s Procurement Cost Risk in Texas," Energies, MDPI, vol. 16(1), pages 1-12, December.
    3. Dongwei Zhao & Hao Wang & Jianwei Huang & Xiaojun Lin, 2022. "Insurance Contract for High Renewable Energy Integration," Papers 2209.10363, arXiv.org.
    4. Farhad Billimoria & Filiberto Fele & Iacopo Savelli & Thomas Morstyn & Malcolm McCulloch, 2023. "An Insurance Paradigm for Improving Power System Resilience via Distributed Investment," Papers 2302.01456, arXiv.org.

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