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Efficiency of wind power production and its determinants

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  • Pieralli, Simone
  • Ritter, Matthias
  • Odening, Martin

Abstract

This article examines the efficiency of wind energy production. We quantify production losses in four wind parks across Germany for 19 wind turbines with non-convex efficiency analysis. In a second stage regression, we adapt the linear regression results of Kneip, Simar, Wilson (2014) to explain electricity losses by means of a bias-corrected truncated regression. Our results show that electricity losses amount to 27% of the maximal producible electricity. These losses can be mainly traced back to changing wind conditions while only 6 % are caused by turbine errors.

Suggested Citation

  • Pieralli, Simone & Ritter, Matthias & Odening, Martin, 2015. "Efficiency of wind power production and its determinants," SFB 649 Discussion Papers 2015-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2015-004
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    References listed on IDEAS

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    1. Kneip, Alois & Simar, Léopold & Wilson, Paul W., 2015. "When Bias Kills The Variance: Central Limit Theorems For Dea And Fdh Efficiency Scores," Econometric Theory, Cambridge University Press, vol. 31(2), pages 394-422, April.
    2. Kusiak, Andrew & Zhang, Zijun & Verma, Anoop, 2013. "Prediction, operations, and condition monitoring in wind energy," Energy, Elsevier, vol. 60(C), pages 1-12.
    3. Iribarren, Diego & Vázquez-Rowe, Ian & Rugani, Benedetto & Benetto, Enrico, 2014. "On the feasibility of using emergy analysis as a source of benchmarking criteria through data envelopment analysis: A case study for wind energy," Energy, Elsevier, vol. 67(C), pages 527-537.
    4. Dominique Deprins & Léopold Simar & Henry Tulkens, 2006. "Measuring Labor-Efficiency in Post Offices," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 285-309, Springer.
    5. Iglesias, Guillermo & Castellanos, Pablo & Seijas, Amparo, 2010. "Measurement of productive efficiency with frontier methods: A case study for wind farms," Energy Economics, Elsevier, vol. 32(5), pages 1199-1208, September.
    6. Staffell, Iain & Green, Richard, 2014. "How does wind farm performance decline with age?," Renewable Energy, Elsevier, vol. 66(C), pages 775-786.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Sonja Germer & Axel Kleidon, 2019. "Have wind turbines in Germany generated electricity as would be expected from the prevailing wind conditions in 2000-2014?," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-16, February.
    2. repec:hum:wpaper:sfb649dp2016-012 is not listed on IDEAS
    3. Xiaoyan Sun & Wenwei Lian & Hongmei Duan & Anjian Wang, 2021. "Factors Affecting Wind Power Efficiency: Evidence from Provincial-Level Data in China," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    4. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    5. Matthias Ritter & Simone Pieralli & Martin Odening, 2017. "Neighborhood Effects in Wind Farm Performance: A Regression Approach," Energies, MDPI, vol. 10(3), pages 1-16, March.
    6. Carlini, Federico & Christensen, Bent Jesper & Datta Gupta, Nabanita & Santucci de Magistris, Paolo, 2023. "Climate, wind energy, and CO2 emissions from energy production in Denmark," Energy Economics, Elsevier, vol. 125(C).
    7. Tuka N Fattal, 2018. "Increasing Wind Turbine Efficiency," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 4(4), pages 120-131.
    8. Yanwei Jing & Hexu Sun & Lei Zhang & Tieling Zhang, 2017. "Variable Speed Control of Wind Turbines Based on the Quasi-Continuous High-Order Sliding Mode Method," Energies, MDPI, vol. 10(10), pages 1-21, October.
    9. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2017. "An Electricity Price Modeling Framework for Renewable-Dominant Markets," Working Paper Series in Production and Energy 23, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    10. Ritter, Matthias & Pieralli, Simone & Odening, Martin, 2016. "Neighborhood effects in wind farm performance: An econometric approach," SFB 649 Discussion Papers 2016-012, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Bent Jesper Christensen & Nabanita Datta Gupta & Paolo Santucci de Magistris, 2021. "Measuring the impact of clean energy production on CO2 abatement in Denmark: Upper bound estimation and forecasting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 118-149, January.

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    More about this item

    Keywords

    wind energy; efficiency; free disposal hull; bias correction;
    All these keywords.

    JEL classification:

    • D20 - Microeconomics - - Production and Organizations - - - General
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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