IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v32y2004i13p1545-1554.html
   My bibliography  Save this article

The learning potential of photovoltaics: implications for energy policy

Author

Listed:
  • van der Zwaan, Bob
  • Rabl, Ari

Abstract

No abstract is available for this item.

Suggested Citation

  • van der Zwaan, Bob & Rabl, Ari, 2004. "The learning potential of photovoltaics: implications for energy policy," Energy Policy, Elsevier, vol. 32(13), pages 1545-1554, September.
  • Handle: RePEc:eee:enepol:v:32:y:2004:i:13:p:1545-1554
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301-4215(03)00126-5
    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. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    2. Grubler, Arnulf & Nakicenovic, Nebojsa & Victor, David G., 1999. "Dynamics of energy technologies and global change," Energy Policy, Elsevier, vol. 27(5), pages 247-280, May.
    3. Oliver, M. & Jackson, T., 2000. "The evolution of economic and environmental cost for crystalline silicon photovoltaics," Energy Policy, Elsevier, vol. 28(14), pages 1011-1021, November.
    Full references (including those not matched with items on IDEAS)

    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. Méjean, Aurélie & Hope, Chris, 2008. "Modelling the costs of non-conventional oil: A case study of Canadian bitumen," Energy Policy, Elsevier, vol. 36(11), pages 4205-4216, November.
    2. Criqui, P. & Mima, S. & Menanteau, P. & Kitous, A., 2015. "Mitigation strategies and energy technology learning: An assessment with the POLES model," Technological Forecasting and Social Change, Elsevier, vol. 90(PA), pages 119-136.
    3. Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
    4. Mercure, J.-F. & Pollitt, H. & Chewpreecha, U. & Salas, P. & Foley, A.M. & Holden, P.B. & Edwards, N.R., 2014. "The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sector," Energy Policy, Elsevier, vol. 73(C), pages 686-700.
    5. Chen, Huayi & Ma, Tieju, 2021. "Technology adoption and carbon emissions with dynamic trading among heterogeneous agents," Energy Economics, Elsevier, vol. 99(C).
    6. Pasaoglu, Guzay & Harrison, Gillian & Jones, Lee & Hill, Andrew & Beaudet, Alexandre & Thiel, Christian, 2016. "A system dynamics based market agent model simulating future powertrain technology transition: Scenarios in the EU light duty vehicle road transport sector," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 133-146.
    7. Méjean, Aurélie & Hope, Chris, 2013. "Supplying synthetic crude oil from Canadian oil sands: A comparative study of the costs and CO2 emissions of mining and in-situ recovery," Energy Policy, Elsevier, vol. 60(C), pages 27-40.
    8. Jamasb, T., 2006. "Technical Change Theory and Learning Curves: Patterns of Progress in Energy Technologies," Cambridge Working Papers in Economics 0625, Faculty of Economics, University of Cambridge.
    9. Rout, Ullash K. & Fahl, Ulrich & Remme, Uwe & Blesl, Markus & Voß, Alfred, 2009. "Endogenous implementation of technology gap in energy optimization models--a systematic analysis within TIMES G5 model," Energy Policy, Elsevier, vol. 37(7), pages 2814-2830, July.
    10. Graham, Paul W. & Williams, David J., 2003. "Optimal technological choices in meeting Australian energy policy goals," Energy Economics, Elsevier, vol. 25(6), pages 691-712, November.
    11. Weiss, Martin & Dittmar, Lars & Junginger, Martin & Patel, Martin K. & Blok, Kornelis, 2009. "Market diffusion, technological learning, and cost-benefit dynamics of condensing gas boilers in the Netherlands," Energy Policy, Elsevier, vol. 37(8), pages 2962-2976, August.
    12. Prasad, Ravita D. & Bansal, R.C. & Raturi, Atul, 2014. "Multi-faceted energy planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 686-699.
    13. Jean-François Mercure, 2015. "An age structured demographic theory of technological change," Journal of Evolutionary Economics, Springer, vol. 25(4), pages 787-820, September.
    14. Yu, C.F. & van Sark, W.G.J.H.M. & Alsema, E.A., 2011. "Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 324-337, January.
    15. Junginger, Martin & de Visser, Erika & Hjort-Gregersen, Kurt & Koornneef, Joris & Raven, Rob & Faaij, Andre & Turkenburg, Wim, 2006. "Technological learning in bioenergy systems," Energy Policy, Elsevier, vol. 34(18), pages 4024-4041, December.
    16. Junginger, M. & Agterbosch, S. & Faaij, A. & Turkenburg, W., 2004. "Renewable electricity in the Netherlands," Energy Policy, Elsevier, vol. 32(9), pages 1053-1073, June.
    17. Handayani, Kamia & Krozer, Yoram & Filatova, Tatiana, 2019. "From fossil fuels to renewables: An analysis of long-term scenarios considering technological learning," Energy Policy, Elsevier, vol. 127(C), pages 134-146.
    18. Schoots, K. & Kramer, G.J. & van der Zwaan, B.C.C., 2010. "Technology learning for fuel cells: An assessment of past and potential cost reductions," Energy Policy, Elsevier, vol. 38(6), pages 2887-2897, June.
    19. Rout, Ullash K. & Blesl, Markus & Fahl, Ulrich & Remme, Uwe & Voß, Alfred, 2009. "Uncertainty in the learning rates of energy technologies: An experiment in a global multi-regional energy system model," Energy Policy, Elsevier, vol. 37(11), pages 4927-4942, November.
    20. Gan, Peck Yean & Li, ZhiDong, 2015. "Quantitative study on long term global solar photovoltaic market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 88-99.

    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:enepol:v:32:y:2004:i:13:p:1545-1554. See general information about how to correct material in RePEc.

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

    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 hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.