IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v50y2012icp81-94.html
   My bibliography  Save this article

Up-scaling, formative phases, and learning in the historical diffusion of energy technologies

Author

Listed:
  • Wilson, Charlie

Abstract

The 20th century has witnessed wholesale transformation in the energy system marked by the pervasive diffusion of both energy supply and end-use technologies. Just as whole industries have grown, so too have unit sizes or capacities. Analysed in combination, these unit level and industry level growth patterns reveal some consistencies across very different energy technologies. First, the up-scaling or increase in unit size of an energy technology comes after an often prolonged period of experimentation with many smaller-scale units. Second, the peak growth phase of an industry can lag these increases in unit size by up to 20 years. Third, the rate and timing of up-scaling at the unit level is subject to countervailing influences of scale economies and heterogeneous market demand. These observed patterns have important implications for experience curve analyses based on time series data covering the up-scaling phases of energy technologies, as these are likely to conflate industry level learning effects with unit level scale effects. The historical diffusion of energy technologies also suggests that low carbon technology policies pushing for significant jumps in unit size before a ‘formative phase’ of experimentation with smaller-scale units are risky.

Suggested Citation

  • Wilson, Charlie, 2012. "Up-scaling, formative phases, and learning in the historical diffusion of energy technologies," Energy Policy, Elsevier, vol. 50(C), pages 81-94.
  • Handle: RePEc:eee:enepol:v:50:y:2012:i:c:p:81-94
    DOI: 10.1016/j.enpol.2012.04.077
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030142151200393X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2012.04.077?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Hendry, Chris & Harborne, Paul & Brown, James, 2010. "So what do innovating companies really get from publicly funded demonstration projects and trials? innovation lessons from solar photovoltaics and wind," Energy Policy, Elsevier, vol. 38(8), pages 4507-4519, August.
    2. Anonymous, 1991. "The Automobile Industry," Business History Review, Cambridge University Press, vol. 65(4), pages 1-1, January.
    3. Kalkuhl, Matthias & Edenhofer, Ottmar & Lessmann, Kai, 2012. "Learning or lock-in: Optimal technology policies to support mitigation," Resource and Energy Economics, Elsevier, vol. 34(1), pages 1-23.
    4. Raff, Daniel M. G., 1991. "Making Cars and Making Money in the Interwar Automobile Industry: Economies of Scale and Scope and the Manufacturing behind the Marketing," Business History Review, Cambridge University Press, vol. 65(4), pages 721-753, January.
    5. Jacobsson, Staffan & Lauber, Volkmar, 2006. "The politics and policy of energy system transformation--explaining the German diffusion of renewable energy technology," Energy Policy, Elsevier, vol. 34(3), pages 256-276, February.
    6. Argote, L. & Epple, D., 1990. "Learning Curves In Manufacturing," GSIA Working Papers 89-90-02, Carnegie Mellon University, Tepper School of Business.
    7. Sidney G. Winter, 2008. "Scaling heuristics shape technology! Should economic theory take notice?," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 17(3), pages 513-531, June.
    8. Patrik Söderholm & Ger Klaassen, 2007. "Wind Power in Europe: A Simultaneous Innovation–Diffusion Model," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(2), pages 163-190, February.
    9. Garud, Raghu & Karnoe, Peter, 2003. "Bricolage versus breakthrough: distributed and embedded agency in technology entrepreneurship," Research Policy, Elsevier, vol. 32(2), pages 277-300, February.
    10. Coulomb, L. & Neuhoff, K., 2006. "Learning curves and changing product attributes: the case of wind turbines," Cambridge Working Papers in Economics 0618, Faculty of Economics, University of Cambridge.
    11. Fouquet, Roger, 2010. "The slow search for solutions: Lessons from historical energy transitions by sector and service," Energy Policy, Elsevier, vol. 38(11), pages 6586-6596, November.
    12. 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.
    13. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
    14. de Coninck, Heleen & Stephens, Jennie C. & Metz, Bert, 2009. "Global learning on carbon capture and storage: A call for strong international cooperation on CCS demonstration," Energy Policy, Elsevier, vol. 37(6), pages 2161-2165, June.
    15. Paul Joskow & Nancy L. Rose, 1985. "The Effects of Technological Change, Experience, and Environmental Regulation on the Construction Cost of Coal-Burning Generating Units," RAND Journal of Economics, The RAND Corporation, vol. 16(1), pages 1-17, Spring.
    16. Ek, Kristina & Söderholm, Patrik, 2010. "Technology learning in the presence of public R&D: The case of European wind power," Ecological Economics, Elsevier, vol. 69(12), pages 2356-2362, October.
    17. Murmann, Johann Peter & Frenken, Koen, 2006. "Toward a systematic framework for research on dominant designs, technological innovations, and industrial change," Research Policy, Elsevier, vol. 35(7), pages 925-952, September.
    18. Nemet, Gregory F., 2009. "Interim monitoring of cost dynamics for publicly supported energy technologies," Energy Policy, Elsevier, vol. 37(3), pages 825-835, March.
    19. Paul Windrum & Cecilia Diaz & Despoina Filiou, 2009. "Exploring the relationship between technical and service characteristics," Journal of Evolutionary Economics, Springer, vol. 19(4), pages 567-588, August.
    20. Grubler, Arnulf, 2010. "The costs of the French nuclear scale-up: A case of negative learning by doing," Energy Policy, Elsevier, vol. 38(9), pages 5174-5188, September.
    21. McNerney, James & Doyne Farmer, J. & Trancik, Jessika E., 2011. "Historical costs of coal-fired electricity and implications for the future," Energy Policy, Elsevier, vol. 39(6), pages 3042-3054, June.
    22. Dosi, Giovanni, 1993. "Technological paradigms and technological trajectories : A suggested interpretation of the determinants and directions of technical change," Research Policy, Elsevier, vol. 22(2), pages 102-103, April.
    23. Nelson, Richard R. & Winter, Sidney G., 1993. "In search of useful theory of innovation," Research Policy, Elsevier, vol. 22(2), pages 108-108, April.
    24. Ferioli, F. & Schoots, K. & van der Zwaan, B.C.C., 2009. "Use and limitations of learning curves for energy technology policy: A component-learning hypothesis," Energy Policy, Elsevier, vol. 37(7), pages 2525-2535, July.
    25. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    26. 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.
    27. Global Energy Assessment Writing Team,, 2012. "Global Energy Assessment," Cambridge Books, Cambridge University Press, number 9781107005198.
    28. Clarke, Leon & Weyant, John & Edmonds, Jae, 2008. "On the sources of technological change: What do the models assume," Energy Economics, Elsevier, vol. 30(2), pages 409-424, March.
    29. Charlie Wilson & Arnulf Grubler, 2011. "Lessons from the history of technological change for clean energy scenarios and policies," Natural Resources Forum, Blackwell Publishing, vol. 35(3), pages 165-184, August.
    30. Harborne, Paul & Hendry, Chris, 2009. "Pathways to commercial wind power in the US, Europe and Japan: The role of demonstration projects and field trials in the innovation process," Energy Policy, Elsevier, vol. 37(9), pages 3580-3595, September.
    31. Luiten, Esther E. M. & Blok, Kornelis, 2003. "Stimulating R&D of industrial energy-efficient technology; the effect of government intervention on the development of strip casting technology," Energy Policy, Elsevier, vol. 31(13), pages 1339-1356, October.
    32. McCabe, Mark J, 1996. "Principals, Agents, and the Learning Curve: The Case of Steam-Electric Power Plant Design and Construction," Journal of Industrial Economics, Wiley Blackwell, vol. 44(4), pages 357-375, December.
    33. 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.
    34. Yeh, Sonia & Rubin, Edward S., 2012. "A review of uncertainties in technology experience curves," Energy Economics, Elsevier, vol. 34(3), pages 762-771.
    35. Astrand, K. & Neij, L., 2006. "An assessment of governmental wind power programmes in Sweden--using a systems approach," Energy Policy, Elsevier, vol. 34(3), pages 277-296, February.
    36. Global Energy Assessment Writing Team,, 2012. "Global Energy Assessment," Cambridge Books, Cambridge University Press, number 9780521182935.
    37. Sahal, Devendra, 1985. "Technological guideposts and innovation avenues," Research Policy, Elsevier, vol. 14(2), pages 61-82, April.
    38. Sagar, Ambuj D. & van der Zwaan, Bob, 2006. "Technological innovation in the energy sector: R&D, deployment, and learning-by-doing," Energy Policy, Elsevier, vol. 34(17), pages 2601-2608, November.
    39. Saviotti, P. P. & Metcalfe, J. S., 1984. "A theoretical approach to the construction of technological output indicators," Research Policy, Elsevier, vol. 13(3), pages 141-151, June.
    40. Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
    41. William D. Nordhaus, 2014. "The Perils of the Learning Model for Modeling Endogenous Technological Change," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    42. Rosenberg,Nathan, 1994. "Exploring the Black Box," Cambridge Books, Cambridge University Press, number 9780521459556, January.
    43. Frenken, Koen & Leydesdorff, Loet, 2000. "Scaling trajectories in civil aircraft (1913-1997)," Research Policy, Elsevier, vol. 29(3), pages 331-348, March.
    44. Koen Frenken & Alessandro Nuvolari, 2004. "The early development of the steam engine: an evolutionary interpretation using complexity theory," Industrial and Corporate Change, Oxford University Press, vol. 13(2), pages 419-450, April.
    45. Staffan Jacobsson & Anna Bergek, 2004. "Transforming the energy sector: the evolution of technological systems in renewable energy technology," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 13(5), pages 815-849, October.
    46. Shinnar, Reuel & Citro, Francesco, 2008. "Decarbonization: Achieving near-total energy independence and near-total elimination of greenhouse emissions with available technologies," Technology in Society, Elsevier, vol. 30(1), pages 1-16.
    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. 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).
    2. 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.
    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. Elia, A. & Kamidelivand, M. & Rogan, F. & Ó Gallachóir, B., 2021. "Impacts of innovation on renewable energy technology cost reductions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    5. 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.
    6. Charlie Wilson & Arnulf Grubler, 2011. "Lessons from the history of technological change for clean energy scenarios and policies," Natural Resources Forum, Blackwell Publishing, vol. 35(3), pages 165-184, August.
    7. Dosi, Giovanni & Nelson, Richard R., 2010. "Technical Change and Industrial Dynamics as Evolutionary Processes," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 51-127, Elsevier.
    8. 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).
    9. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2021. "Improving the analytical framework for quantifying technological progress in energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    10. Paul Lehmann & Patrik Söderholm, 2018. "Can Technology-Specific Deployment Policies Be Cost-Effective? The Case of Renewable Energy Support Schemes," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(2), pages 475-505, October.
    11. Schauf, Magnus & Schwenen, Sebastian, 2021. "Mills of progress grind slowly? Estimating learning rates for onshore wind energy," Energy Economics, Elsevier, vol. 104(C).
    12. Brown, James & Hendry, Chris, 2009. "Public demonstration projects and field trials: Accelerating commercialisation of sustainable technology in solar photovoltaics," Energy Policy, Elsevier, vol. 37(7), pages 2560-2573, July.
    13. Mauleón, Ignacio, 2016. "Photovoltaic learning rate estimation: Issues and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 507-524.
    14. Bento, Nuno & Fontes, Margarida, 2015. "The construction of a new technological innovation system in a follower country: Wind energy in Portugal," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 197-210.
    15. Nemet, Gregory F., 2009. "Demand-pull, technology-push, and government-led incentives for non-incremental technical change," Research Policy, Elsevier, vol. 38(5), pages 700-709, June.
    16. Giovanni Dosi & Richard Nelson, 2013. "The Evolution of Technologies: An Assessment of the State-of-the-Art," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 3(1), pages 3-46, June.
    17. Yeh, Sonia & Rubin, Edward S., 2012. "A review of uncertainties in technology experience curves," Energy Economics, Elsevier, vol. 34(3), pages 762-771.
    18. 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.
    19. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
    20. Bento, Nuno & Gianfrate, Gianfranco & Groppo, Sara Virginia, 2019. "Do crowdfunding returns reward risk? Evidences from clean-tech projects," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 107-116.

    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:50:y:2012:i:c:p:81-94. 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.