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Technology learning for fuel cells: An assessment of past and potential cost reductions

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  • Schoots, K.
  • Kramer, G.J.
  • van der Zwaan, B.C.C.

Abstract

Fuel cells have gained considerable interest as a means to efficiently convert the energy stored in gases like hydrogen and methane into electricity. Further developing fuel cells in order to reach cost, safety and reliability levels at which their widespread use becomes feasible is an essential prerequisite for the potential establishment of a 'hydrogen economy'. A major factor currently obviating the extensive use of fuel cells is their relatively high costs. At present we estimate these at about 1100 [euro](2005)/kW for an 80Â kW fuel cell system but notice that specific costs vary markedly with fuel cell system power capacity. We analyze past fuel cell cost reductions for both individual manufacturers and the global market. We determine learning curves, with fairly high uncertainty ranges, for three different types of fuel cell technology - AFC, PAFC and PEMFC - each manufactured by a different producer. For PEMFC technology we also calculate a global learning curve, characterised by a learning rate of 21% with an error margin of 4%. Given their respective uncertainties, this global learning rate value is in agreement with those we find for different manufacturers. In contrast to some other new energy technologies, R&D still plays a major role in today's fuel cell improvement process and hence probably explains a substantial part of our observed cost reductions. The remaining share of these cost reductions derives from learning-by-doing proper. Since learning-by-doing usually involves a learning rate of typically 20%, the residual value for pure learning we find for fuel cells is relatively low. In an ideal scenario for fuel cell technology we estimate a bottom-line for specific (80Â kW system) manufacturing costs of 95 [euro](2005)/kW. Although learning curves observed in the past constitute no guarantee for sustained cost reductions in the future, when we assume global total learning at the pace calculated here as the only cost reduction mechanism, this ultimate cost figure is reached after a large-scale deployment about 10 times doubled with respect to the cumulative installed fuel cell capacity to date.

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Bibliographic Info

Article provided by Elsevier in its journal Energy Policy.

Volume (Year): 38 (2010)
Issue (Month): 6 (June)
Pages: 2887-2897

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Handle: RePEc:eee:enepol:v:38:y:2010:i:6:p:2887-2897

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Web page: http://www.elsevier.com/locate/enpol

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Keywords: Technology innovation Learning curve Fuel cell;

References

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  1. Tribe, M. A. & Alpine, R. L. W., 1986. "Scale economies and the "0.6 rule"," Engineering Costs and Production Economics, Elsevier, vol. 10(4), pages 271-278, 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. Argote, L. & Epple, D., 1990. "Learning Curves In Manufacturing," GSIA Working Papers 89-90-02, Carnegie Mellon University, Tepper School of Business.
  4. Lipman, Timothy E. & Edwards, Jennifer L. & Kammen, Daniel M., 2004. "Fuel cell system economics: comparing the costs of generating power with stationary and motor vehicle PEM fuel cell systems," Energy Policy, Elsevier, vol. 32(1), pages 101-125, January.
  5. 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.
  6. 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.
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  8. John F. Muth, 1986. "Search Theory and the Manufacturing Progress Function," Management Science, INFORMS, vol. 32(8), pages 948-962, August.
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Cited by:
  1. Ye Li & Peter Jan Engelen & Clemens Kool, 2012. "A Barrier Options Approach to Modeling Project Failure: The Case of Hydrogen Fuel Infrastructure," Working Papers 13-01, Utrecht School of Economics.
  2. Niko Jaakkola, 2013. "Green Technologies and the Protracted End to the Age of Oil: A strategic analysis," OxCarre Working Papers 099, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
  3. van der Zwaan, Bob & Keppo, Ilkka & Johnsson, Filip, 2013. "How to decarbonize the transport sector?," Energy Policy, Elsevier, vol. 61(C), pages 562-573.

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