IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v38y2010i8p4163-4172.html
   My bibliography  Save this article

Global technology learning and national policy--An incentive scheme for governments to assume the high cost of early deployment exemplified by Norway

Author

Listed:
  • Martinsen, Thomas

Abstract

In this paper it is argued that technology learning may be both a barrier and an incentive for technology change in the national energy system. The possibility to realize an ambitious global emission reduction scenario is enhanced by coordinated action between countries in national policy implementation. An indicator for coordinated action is suggested. Targeted measures to increase deployment of nascent energy technologies and increasing energy efficiency in a small open economy like Norway are examined. The measures are evaluated against a set of baselines with different levels of spillover of technology learning from the global market. It is found that implementation of technology subsidies increase the national contribution to early deployment independent of the level of spillover. In a special case with no spillover for offshore floating wind power and endogenous technology learning substantial subsidy or a learning rate of 20% is required. Combining the high learning rate and a national subsidy increases the contribution to early deployment. Enhanced building code on the other hand may reduce Norway's contribution to early deployment, and thus the realization of a global emission reduction scenario, unless sufficient electricity export capacity is assured.

Suggested Citation

  • Martinsen, Thomas, 2010. "Global technology learning and national policy--An incentive scheme for governments to assume the high cost of early deployment exemplified by Norway," Energy Policy, Elsevier, vol. 38(8), pages 4163-4172, August.
  • Handle: RePEc:eee:enepol:v:38:y:2010:i:8:p:4163-4172
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301-4215(10)00207-7
    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. 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.
    2. Buen, Jorund, 2006. "Danish and Norwegian wind industry: The relationship between policy instruments, innovation and diffusion," Energy Policy, Elsevier, vol. 34(18), pages 3887-3897, December.
    3. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
    4. Ekins, Paul & Lees, Eoin, 2008. "The impact of EU policies on energy use in and the evolution of the UK built environment," Energy Policy, Elsevier, vol. 36(12), pages 4580-4583, December.
    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. Seljom, Pernille & Rosenberg, Eva & Fidje, Audun & Haugen, Jan Erik & Meir, Michaela & Rekstad, John & Jarlset, Thore, 2011. "Modelling the effects of climate change on the energy system—A case study of Norway," Energy Policy, Elsevier, vol. 39(11), pages 7310-7321.
    2. Martinsen, Thomas, 2011. "Technology learning in a small open economy--The systems, modelling and exploiting the learning effect," Energy Policy, Elsevier, vol. 39(5), pages 2361-2372, May.
    3. Liu, Xi & Du, Huibin & Brown, Marilyn A. & Zuo, Jian & Zhang, Ning & Rong, Qian & Mao, Guozhu, 2018. "Low-carbon technology diffusion in the decarbonization of the power sector: Policy implications," Energy Policy, Elsevier, vol. 116(C), pages 344-356.
    4. Martinsen, Thomas, 2011. "Introducing technology learning for energy technologies in a national CGE model through soft links to global and national energy models," Energy Policy, Elsevier, vol. 39(6), pages 3327-3336, June.

    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. 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.
    2. 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.
    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. del Río, Pablo, 2012. "The dynamic efficiency of feed-in tariffs: The impact of different design elements," Energy Policy, Elsevier, vol. 41(C), pages 139-151.
    5. Elia, A. & Taylor, M. & Ó Gallachóir, B. & Rogan, F., 2020. "Wind turbine cost reduction: A detailed bottom-up analysis of innovation drivers," Energy Policy, Elsevier, vol. 147(C).
    6. 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.
    7. del Río, Pablo & Calvo Silvosa, Anxo & Iglesias Gómez, Guillermo, 2011. "Policies and design elements for the repowering of wind farms: A qualitative analysis of different options," Energy Policy, Elsevier, vol. 39(4), pages 1897-1908, April.
    8. Dalton, Gordon & Allan, Grant & Beaumont, Nicola & Georgakaki, Aliki & Hacking, Nick & Hooper, Tara & Kerr, Sandy & O’Hagan, Anne Marie & Reilly, Kieran & Ricci, Pierpaolo & Sheng, Wanan & Stallard, T, 2015. "Economic and socio-economic assessment methods for ocean renewable energy: Public and private perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 850-878.
    9. Lehmann, Paul, 2013. "Supplementing an emissions tax by a feed-in tariff for renewable electricity to address learning spillovers," Energy Policy, Elsevier, vol. 61(C), pages 635-641.
    10. Mauleón, Ignacio, 2016. "Photovoltaic learning rate estimation: Issues and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 507-524.
    11. Weiss, Martin & Patel, Martin K. & Junginger, Martin & Blok, Kornelis, 2010. "Analyzing price and efficiency dynamics of large appliances with the experience curve approach," Energy Policy, Elsevier, vol. 38(2), pages 770-783, February.
    12. Hong, Sungjun & Chung, Yanghon & Woo, Chungwon, 2015. "Scenario analysis for estimating the learning rate of photovoltaic power generation based on learning curve theory in South Korea," Energy, Elsevier, vol. 79(C), pages 80-89.
    13. 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.
    14. 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.
    15. Philipp Beiter & Aubryn Cooperman & Eric Lantz & Tyler Stehly & Matt Shields & Ryan Wiser & Thomas Telsnig & Lena Kitzing & Volker Berkhout & Yuka Kikuchi, 2021. "Wind power costs driven by innovation and experience with further reductions on the horizon," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 10(5), September.
    16. Komendantova, Nadejda & Patt, Anthony & Williges, Keith, 2011. "Solar power investment in North Africa: Reducing perceived risks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4829-4835.
    17. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
    18. Beck, Marisa & Rivers, Nicholas & Wigle, Randall, 2018. "How do learning externalities influence the evaluation of Ontario's renewables support policies?," Energy Policy, Elsevier, vol. 117(C), pages 86-99.
    19. Gunther Glenk & Rebecca Meier & Stefan Reichelstein, 2021. "Cost Dynamics of Clean Energy Technologies," Schmalenbach Journal of Business Research, Springer, vol. 73(2), pages 179-206, June.
    20. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.

    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:38:y:2010:i:8:p:4163-4172. 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.