IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v39y2011i7p4153-4167.html
   My bibliography  Save this article

Renewable electricity production costs--A framework to assist policy-makers' decisions on price support

Author

Listed:
  • Dinica, Valentina

Abstract

Despite recent progress, the production costs for renewable electricity remain above those for conventional power. Expectations of continuous reductions in production costs, typically underpin governments' policies for financial support. They often draw on the technology-focused versions of the Experience Curve model. This paper discusses how national-contextual factors also have a strong influence on production costs, such as geographic, infrastructural, institutional, and resource factors. As technologies mature, and as they reach significant levels of diffusion nationally, sustained increases in production costs might be recorded, due to these nationally contextual factors, poorly accounted for in policy-making decisions for price support. The paper suggests an analytical framework for a more comprehensive understanding of production costs. Based on this, it recommends that the evolution of specific cost levels and factors be monitored to locate 'sources of changes'. The paper also suggests policy instruments that governments may use to facilitate cost decreases, whenever possible. The application of the framework is illustrated for the diffusion of wind power in Spain during the past three decades.

Suggested Citation

  • Dinica, Valentina, 2011. "Renewable electricity production costs--A framework to assist policy-makers' decisions on price support," Energy Policy, Elsevier, vol. 39(7), pages 4153-4167, July.
  • Handle: RePEc:eee:enepol:v:39:y:2011:i:7:p:4153-4167
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421511003041
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dinica, Valentina, 2006. "Support systems for the diffusion of renewable energy technologies--an investor perspective," Energy Policy, Elsevier, vol. 34(4), pages 461-480, March.
    2. Nemet, Gregory F., 2009. "Interim monitoring of cost dynamics for publicly supported energy technologies," Energy Policy, Elsevier, vol. 37(3), pages 825-835, March.
    3. Neij, L, 1999. "Cost dynamics of wind power," Energy, Elsevier, vol. 24(5), pages 375-389.
    4. Berry, David, 2009. "Innovation and the price of wind energy in the US," Energy Policy, Elsevier, vol. 37(11), pages 4493-4499, November.
    5. Valentina Dinica, 2010. "Wind Technology: A Framework for the Evaluation of Innovations’ Impacts on the Diffusion Potential," Sustainability, MDPI, vol. 2(3), pages 1-26, March.
    6. Bolinger, Mark & Wiser, Ryan, 2009. "Wind power price trends in the United States: Struggling to remain competitive in the face of strong growth," Energy Policy, Elsevier, vol. 37(3), pages 1061-1071, March.
    7. Zubi, Ghassan & Bernal-Agustín, José L. & Fandos Marín, Ana B., 2009. "Wind energy (30%) in the Spanish power mix--technically feasible and economically reasonable," Energy Policy, Elsevier, vol. 37(8), pages 3221-3226, August.
    8. Neij, Lena, 1997. "Use of experience curves to analyse the prospects for diffusion and adoption of renewable energy technology," Energy Policy, Elsevier, vol. 25(13), pages 1099-1107, November.
    9. Blanco, María Isabel, 2009. "The economics of wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1372-1382, August.
    10. Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
    11. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shrestha, Anil & Kakinaka, Makoto, 2023. "Nexus between renewable energy certificates and electricity prices in India: Evidence from wavelet coherence analysis," Renewable Energy, Elsevier, vol. 204(C), pages 836-847.
    2. Nicolini, Marcella & Tavoni, Massimo, 2017. "Are renewable energy subsidies effective? Evidence from Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 412-423.
    3. Bergek, Anna & Mignon, Ingrid & Sundberg, Gunnel, 2013. "Who invests in renewable electricity production? Empirical evidence and suggestions for further research," Energy Policy, Elsevier, vol. 56(C), pages 568-581.
    4. Farrell, Niall, 2023. "Policy design for green hydrogen," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    5. Schmid, Eva & Knopf, Brigitte, 2015. "Quantifying the long-term economic benefits of European electricity system integration," Energy Policy, Elsevier, vol. 87(C), pages 260-269.
    6. Bolinger, Mark & Wiser, Ryan, 2012. "Understanding wind turbine price trends in the U.S. over the past decade," Energy Policy, Elsevier, vol. 42(C), pages 628-641.
    7. Gupta, Sandeep Kumar & Purohit, Pallav, 2013. "Renewable energy certificate mechanism in India: A preliminary assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 380-392.
    8. Ortega, Margarita & del Río, Pablo & Montero, Eduardo A., 2013. "Assessing the benefits and costs of renewable electricity. The Spanish case," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 294-304.
    9. Schmid, Eva & Pahle, Michael & Knopf, Brigitte, 2013. "Renewable electricity generation in Germany: A meta-analysis of mitigation scenarios," Energy Policy, Elsevier, vol. 61(C), pages 1151-1163.
    10. Ouyang, Xiaoling & Lin, Boqiang, 2014. "Levelized cost of electricity (LCOE) of renewable energies and required subsidies in China," Energy Policy, Elsevier, vol. 70(C), pages 64-73.
    11. Chatzivasileiadis, Spyros & Ernst, Damien & Andersson, Göran, 2013. "The Global Grid," Renewable Energy, Elsevier, vol. 57(C), pages 372-383.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
    2. Clas‐Otto Wene, 2016. "Future energy system development depends on past learning opportunities," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 5(1), pages 16-32, January.
    3. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.
    4. Reinhard Haas & Marlene Sayer & Amela Ajanovic & Hans Auer, 2023. "Technological learning: Lessons learned on energy technologies," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(2), March.
    5. Wüstemeyer, Christoph & Bunn, Derek & Madlener, Reinhard, 2012. "Bridging the Gap between Onshore and Offshore Innovations by the European Wind Power Supply Industry: A Survey-based Analysis," FCN Working Papers 19/2012, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    6. Qiu, Yueming & Anadon, Laura D., 2012. "The price of wind power in China during its expansion: Technology adoption, learning-by-doing, economies of scale, and manufacturing localization," Energy Economics, Elsevier, vol. 34(3), pages 772-785.
    7. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
    8. Bolinger, Mark & Wiser, Ryan, 2012. "Understanding wind turbine price trends in the U.S. over the past decade," Energy Policy, Elsevier, vol. 42(C), pages 628-641.
    9. Candelise, Chiara & Winskel, Mark & Gross, Robert J.K., 2013. "The dynamics of solar PV costs and prices as a challenge for technology forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 96-107.
    10. Bolinger, Mark & Wiser, Ryan, 2009. "Wind power price trends in the United States: Struggling to remain competitive in the face of strong growth," Energy Policy, Elsevier, vol. 37(3), pages 1061-1071, March.
    11. Yeh, Sonia & Rubin, Edward S., 2012. "A review of uncertainties in technology experience curves," Energy Economics, Elsevier, vol. 34(3), pages 762-771.
    12. Yu, Yang & Li, Hong & Che, Yuyuan & Zheng, Qiongjie, 2017. "The price evolution of wind turbines in China: A study based on the modified multi-factor learning curve," Renewable Energy, Elsevier, vol. 103(C), pages 522-536.
    13. Kumbaroglu, Gürkan & Madlener, Reinhard & Demirel, Mustafa, 2008. "A real options evaluation model for the diffusion prospects of new renewable power generation technologies," Energy Economics, Elsevier, vol. 30(4), pages 1882-1908, July.
    14. Lehmann, Paul, 2009. "Climate policies with pollution externalities and learning spillovers," UFZ Discussion Papers 10/2009, Helmholtz Centre for Environmental Research (UFZ), Division of Social Sciences (ÖKUS).
    15. Neij, Lena, 2008. "Cost development of future technologies for power generation--A study based on experience curves and complementary bottom-up assessments," Energy Policy, Elsevier, vol. 36(6), pages 2200-2211, June.
    16. Dosi, Giovanni & Grazzi, Marco & Mathew, Nanditha, 2017. "The cost-quantity relations and the diverse patterns of “learning by doing”: Evidence from India," Research Policy, Elsevier, vol. 46(10), pages 1873-1886.
    17. Schauf, Magnus & Schwenen, Sebastian, 2021. "Mills of progress grind slowly? Estimating learning rates for onshore wind energy," Energy Economics, Elsevier, vol. 104(C).
    18. Gosens, Jorrit & Hedenus, Fredrik & Sandén, Björn A., 2017. "Faster market growth of wind and PV in late adopters due to global experience build-up," Energy, Elsevier, vol. 131(C), pages 267-278.
    19. Allan, Grant & Gilmartin, Michelle & McGregor, Peter & Swales, Kim, 2011. "Levelised costs of Wave and Tidal energy in the UK: Cost competitiveness and the importance of "banded" Renewables Obligation Certificates," Energy Policy, Elsevier, vol. 39(1), pages 23-39, January.
    20. Blanco, María Isabel, 2009. "The economics of wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1372-1382, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:39:y:2011:i:7:p:4153-4167. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.