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Specifying An Efficient Renewable Energy Feed-in Tariff

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  • Farrell, Niall
  • Devine, Mel
  • Lee, William
  • Gleeson, James
  • Lyons, Seán

Abstract

This paper derives efficient pricing formulae for renewable energy Feed-in Tariff (FiT) designs that incorporate exposure to uncertain market prices by using option pricing theory. Such FiT designs are presented as a means to delineate market price risk amongst investors and policymakers when designing renewable energy support schemes. Sequential game theory provides the theoretical framework through which we model the strategic interaction of policymakers and investors during policy formulation. This model is solved using option pricing theory when a FiT is comprised of market prices combined with a guaranteed element. This solution also allows for an analytical formulation of the policy cost of subsidisation. Partial derivatives characterise sensitivity of policy cost and investor remuneration to deviations in market conditions beyond those expected. Analytical derivations provide a set of tools which may guide more efficient FiT policy and investment decisions. Numerical simulations demonstrate application for a stylised Irish case study, with a scenario analysis providing further insight into the relative sensitivity of policy cost and investor remuneration under different market conditions.

Suggested Citation

  • Farrell, Niall & Devine, Mel & Lee, William & Gleeson, James & Lyons, Seán, 2013. "Specifying An Efficient Renewable Energy Feed-in Tariff," MPRA Paper 49777, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:49777
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    Cited by:

    1. Farrell, Niall & Devine, Mel, 2015. "How do External Costs affect Pay-as-bid Renewable Energy Connection Auctions?," Papers WP517, Economic and Social Research Institute (ESRI).
    2. Farrell, Niall, 2023. "Policy design for green hydrogen," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    3. Mel T. Devine & Valentin Bertsch, 2023. "The role of demand response in mitigating market power: a quantitative analysis using a stochastic market equilibrium model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 555-597, June.
    4. Curtis, John & Lynch, Muireann Á. & Zubiate, Laura, 2016. "The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland," Energy Economics, Elsevier, vol. 58(C), pages 186-198.
    5. Curtis, John & Devitt, Niamh & di Cosmo, Valeria & Farrell, Niall & FitzGerald, John & Hyland, Marie & Lynch, Muireann & Lyons, Sean & McCoy, Daire & Malaguzzi Valeri, Laura & Walsh, Darragh, 2014. "Irish Energy Policy: An Analysis of Current Issues," Research Series, Economic and Social Research Institute (ESRI), number rs37 edited by FitzGerald, John & Malaguzzi Valeri, Laura, June.
    6. Assereto, Martina & Byrne, Julie, 2021. "No real option for solar in Ireland: A real option valuation of utility scale solar investment in Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    7. Amedeo Argentiero, Tarek Atalla, Simona Bigerna, Silvia Micheli, and Paolo Polinori, 2017. "Comparing Renewable Energy Policies in EU-15, U.S. and China: A Bayesian DSGE Model," The Energy Journal, International Association for Energy Economics, vol. 0(KAPSARC S).
    8. Patrice Bougette and Christophe Charlier, 2018. "Antidumping and Feed-In Tariffs as Good Buddies? Modeling the EU-China Solar Panel Dispute," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    9. Menton, Cathal & Longoria, Genaro & Farrell, Niall & Lynch, Muireann Á, 2022. "All-island coordination of energy infrastructure and renewable energy supports," Research Series, Economic and Social Research Institute (ESRI), number RS155, June.
    10. Bertsch, Valentin & Devine, Mel, 2019. "The Role of Demand Response in Mitigating Market Power — A Quantitative Analysis Using a Stochastic Market Equilibrium Model," Papers WP635, Economic and Social Research Institute (ESRI).
    11. Farrell, Niall & Devine, Mel T. & Soroudi, Alireza, 2018. "An auction framework to integrate dynamic transmission expansion planning and pay-as-bid wind connection auctions," Applied Energy, Elsevier, vol. 228(C), pages 2462-2477.
    12. Zhu, Lei & Li, Li & Su, Bin, 2021. "The price-bidding strategy for investors in a renewable auction: An option games–based study," Energy Economics, Elsevier, vol. 100(C).
    13. Jeon, Chanwoong & Lee, Jeongjin & Shin, Juneseuk, 2015. "Optimal subsidy estimation method using system dynamics and the real option model: Photovoltaic technology case," Applied Energy, Elsevier, vol. 142(C), pages 33-43.

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    More about this item

    Keywords

    Renewable Energy; Feed-in Tariff; Option Pricing; Renewable Energy Support Schemes �;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

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