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Responsive feed-in tariff adjustment to dynamic technology development

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  • Grau, Thilo

Abstract

This paper reviews the adjustments of the feed-in tariffs for new solar photovoltaic (PV) installations in Germany. As PV system prices declined rapidly since 2009, the German government implemented automatic mechanisms to adjust the remuneration level for new installations in response to deployment volumes. This paper develops an analytic model to simulate weekly installations of PV systems of up to 30kW based on project profitability and project duration. The model accurately replicates observed market developments and is used to assess different adjustment mechanisms against multiple scenarios for PV system price developments. The analysis shows that responsive feed-in tariff schemes with frequent tariff adjustments and short qualifying periods reach deployment targets most effectively.

Suggested Citation

  • Grau, Thilo, 2014. "Responsive feed-in tariff adjustment to dynamic technology development," Energy Economics, Elsevier, vol. 44(C), pages 36-46.
  • Handle: RePEc:eee:eneeco:v:44:y:2014:i:c:p:36-46
    DOI: 10.1016/j.eneco.2014.03.015
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    References listed on IDEAS

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    Cited by:

    1. Zipp, Alexander, 2017. "The marketability of variable renewable energy in liberalized electricity markets – An empirical analysis," Renewable Energy, Elsevier, vol. 113(C), pages 1111-1121.
    2. Thilo Grau & Karsten Neuhoff, 2016. "Coordination of Renewable Energy Remuneration Schemes through Information Exchange," Discussion Papers of DIW Berlin 1574, DIW Berlin, German Institute for Economic Research.
    3. Hitaj, Claudia & Löschel, Andreas, 2019. "The impact of a feed-in tariff on wind power development in Germany," Resource and Energy Economics, Elsevier, vol. 57(C), pages 18-35.
    4. Germeshausen, Robert, 2016. "Effects of Attribute-Based Regulation on Technology Adoption - The Case of Feed-In Tariffs for Solar Photovoltaic," VfS Annual Conference 2016 (Augsburg): Demographic Change 145712, Verein für Socialpolitik / German Economic Association.
    5. Burtt, D. & Dargusch, P., 2015. "The cost-effectiveness of household photovoltaic systems in reducing greenhouse gas emissions in Australia: Linking subsidies with emission reductions," Applied Energy, Elsevier, vol. 148(C), pages 439-448.
    6. Ramli, Makbul A.M. & Twaha, Ssennoga, 2015. "Analysis of renewable energy feed-in tariffs in selected regions of the globe: Lessons for Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 649-661.
    7. Rogge, Karoline S. & Schleich, Joachim, 2018. "Do policy mix characteristics matter for low-carbon innovation? A survey-based exploration of renewable power generation technologies in Germany," Research Policy, Elsevier, vol. 47(9), pages 1639-1654.
    8. Klein, Martin & Deissenroth, Marc, 2017. "When do households invest in solar photovoltaics? An application of prospect theory," Energy Policy, Elsevier, vol. 109(C), pages 270-278.
    9. Xia, Fang & Lu, Xi & Song, Feng, 2020. "The role of feed-in tariff in the curtailment of wind power in China," Energy Economics, Elsevier, vol. 86(C).
    10. Strupeit, Lars, 2017. "An innovation system perspective on the drivers of soft cost reduction for photovoltaic deployment: The case of Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 273-286.
    11. Nuñez-Jimenez, Alejandro & Knoeri, Christof & Rottmann, Fabian & Hoffmann, Volker H., 2020. "The role of responsiveness in deployment policies: A quantitative, cross-country assessment using agent-based modelling," Applied Energy, Elsevier, vol. 275(C).
    12. Kästel, Peter & Gilroy-Scott, Bryce, 2015. "Economics of pooling small local electricity prosumers—LCOE & self-consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 718-729.
    13. Coffman, Makena & Wee, Sherilyn & Bonham, Carl & Salim, Germaine, 2016. "A policy analysis of Hawaii's solar tax credit," Renewable Energy, Elsevier, vol. 85(C), pages 1036-1043.
    14. Sirin, Selahattin Murat & Yilmaz, Berna N., 2020. "Variable renewable energy technologies in the Turkish electricity market: Quantile regression analysis of the merit-order effect," Energy Policy, Elsevier, vol. 144(C).
    15. Karoline S. Rogge & Elisabeth Dütschke, 2017. "Exploring Perceptions of the Credibility of Policy Mixes: The Case of German Manufacturers of Renewable Power Generation Technologies," SPRU Working Paper Series 2017-23, SPRU - Science Policy Research Unit, University of Sussex Business School.
    16. Balta-Ozkan, Nazmiye & Yildirim, Julide & Connor, Peter M., 2015. "Regional distribution of photovoltaic deployment in the UK and its determinants: A spatial econometric approach," Energy Economics, Elsevier, vol. 51(C), pages 417-429.

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    More about this item

    Keywords

    Feed-in tariff; Solar photovoltaic; Renewable energy deployment;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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