IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v59y1998i1p1-38.html
   My bibliography  Save this article

Likely market-penetrations of renewable-energy technologies

Author

Listed:
  • Mackay, R.M
  • Probert, S.D

Abstract

The learning-curve concept is considered to be an important tool for predicting the future costs of renewable-energy technology systems. This paper sets out the underlying rationale for learning-curve theory and the potential for its application to renewable technologies, such as photovoltaic-module and wind-power generator technologies. An indication of the data requirements for carrying out learning-curve projections is given together with an assessment of the requirements necessary for an analysis to be undertaken of the application of learning curves to other renewable-energy technologies. The paper includes a cost comparison and a figure-of-merit criterion applicable to photovoltaic-module and wind-power-turbine technologies.

Suggested Citation

  • Mackay, R.M & Probert, S.D, 1998. "Likely market-penetrations of renewable-energy technologies," Applied Energy, Elsevier, vol. 59(1), pages 1-38, January.
    • Handle: RePEc:eee:appene:v:59:y:1998:i:1:p:1-38
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306-2619(97)00054-8
    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.

    Citations

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


    Cited by:

    1. Malte Schwoon, 2006. "Learning-by-doing, Learning Spillovers and the Diffusion of Fuel Cell Vehicles," Working Papers FNU-112, Research unit Sustainability and Global Change, Hamburg University, revised Jun 2006.
    2. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
    3. 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.
    4. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
    5. Chinmoy, Lakshmi & Iniyan, S. & Goic, Ranko, 2019. "Modeling wind power investments, policies and social benefits for deregulated electricity market – A review," Applied Energy, Elsevier, vol. 242(C), pages 364-377.
    6. Kahouli-Brahmi, Sondes, 2009. "Testing for the presence of some features of increasing returns to adoption factors in energy system dynamics: An analysis via the learning curve approach," Ecological Economics, Elsevier, vol. 68(4), pages 1195-1212, February.
    7. Yi Zhou & Alun Gu, 2019. "Learning Curve Analysis of Wind Power and Photovoltaics Technology in US: Cost Reduction and the Importance of Research, Development and Demonstration," Sustainability, MDPI, vol. 11(8), pages 1-16, April.
    8. Loschel, Andreas, 2002. "Technological change in economic models of environmental policy: a survey," Ecological Economics, Elsevier, vol. 43(2-3), pages 105-126, December.
    9. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.
    10. Bossink, Bart, 2020. "Learning strategies in sustainable energy demonstration projects: What organizations learn from sustainable energy demonstrations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    11. Al-Ismaily, Hilal A. & Probert, Douglas, 1998. "Photovoltaic electricity prospects in oman," Applied Energy, Elsevier, vol. 59(2-3), pages 97-124, February.
    12. Blanco, María Isabel, 2009. "The economics of wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1372-1382, August.
    13. Kahouli, Sondès, 2011. "Effects of technological learning and uranium price on nuclear cost: Preliminary insights from a multiple factors learning curve and uranium market modeling," Energy Economics, Elsevier, vol. 33(5), pages 840-852, September.
    14. Rahimiyan, Morteza & Morales, Juan M. & Conejo, Antonio J., 2011. "Evaluating alternative offering strategies for wind producers in a pool," Applied Energy, Elsevier, vol. 88(12), pages 4918-4926.
    15. Purohit, Pallav & Kandpal, Tara C., 2005. "Renewable energy technologies for irrigation water pumping in India: projected levels of dissemination, energy delivery and investment requirements using available diffusion models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 9(6), pages 592-607, December.
    16. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
    17. Malte Schwoon, 2006. "A Tool to Optimize the Initial Distribution of Hydrogen Filling Stations," Working Papers FNU-110, Research unit Sustainability and Global Change, Hamburg University, revised Jun 2006.

    More about this item

    Statistics

    Access and download statistics

    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:appene:v:59:y:1998:i:1:p:1-38. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/wps/find/journaldescription.cws_home/405891/description#description .

    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.