Technological learning in bioenergy systems

Martin Junginger, Erika de Visser, Kurt Hjort-Gregersen, Joris Koornneef, Rob Raven, André Faaij, Wim Turkenburg

Research output: Contribution to journalArticleResearchpeer-review

105 Citations (Scopus)

Abstract

The main goal of this article is to determine whether cost reductions in different bioenergy systems can be quantified using the experience curve approach, and how specific issues (arising from the complexity of biomass energy systems) can be addressed. This is pursued by case studies on biofuelled combined heat and power (CHP) plants in Sweden, global development of fluidized bed boilers and Danish biogas plants. As secondary goal, the aim is to identify learning mechanisms behind technology development and cost reduction for the biomass energy systems investigated. The case studies reveal large difficulties to devise empirical experience curves for investment costs of biomass-fuelled power plants. To some extent, this is due to lack of (detailed) data. The main reason, however, are varying plant costs due to differences in scale, fuel type, plant layout, region etc. For fluidized bed boiler plants built on a global level, progress ratios (PRs) for the price of entire plants lies approximately between 90-93% (which is typical for large plant-like technologies). The costs for the boiler section alone was found to decline much faster. The experience curve approach delivers better results, when the production costs of the final energy carrier are analyzed. Electricity from biofuelled CHP-plants yields PRs of 91-92%, i.e. an 8-9% reduction of electricity production costs with each cumulative doubling of electricity production. The experience curve for biogas production displays a PR of 85% from 1984 to the beginning of 1990, and then levels to approximately 100% until 2002. For technologies developed on a local level (e.g. biogas plants), learning-by-using and learning-by-interacting are important learning mechanism, while for CHP plants utilizing fluidized bed boilers, upscaling is probably one of the main mechanisms behind cost reductions.

Original languageEnglish
Pages (from-to)4024-4041
Number of pages18
JournalEnergy Policy
Volume34
Issue number18
DOIs
Publication statusPublished - 1 Dec 2006
Externally publishedYes

Keywords

  • Biomass
  • Experience curve
  • Technological learning

Cite this

Junginger, M., de Visser, E., Hjort-Gregersen, K., Koornneef, J., Raven, R., Faaij, A., & Turkenburg, W. (2006). Technological learning in bioenergy systems. Energy Policy, 34(18), 4024-4041. https://doi.org/10.1016/j.enpol.2005.09.012
Junginger, Martin ; de Visser, Erika ; Hjort-Gregersen, Kurt ; Koornneef, Joris ; Raven, Rob ; Faaij, André ; Turkenburg, Wim. / Technological learning in bioenergy systems. In: Energy Policy. 2006 ; Vol. 34, No. 18. pp. 4024-4041.
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Junginger, M, de Visser, E, Hjort-Gregersen, K, Koornneef, J, Raven, R, Faaij, A & Turkenburg, W 2006, 'Technological learning in bioenergy systems', Energy Policy, vol. 34, no. 18, pp. 4024-4041. https://doi.org/10.1016/j.enpol.2005.09.012

Technological learning in bioenergy systems. / Junginger, Martin; de Visser, Erika; Hjort-Gregersen, Kurt; Koornneef, Joris; Raven, Rob; Faaij, André; Turkenburg, Wim.

In: Energy Policy, Vol. 34, No. 18, 01.12.2006, p. 4024-4041.

Research output: Contribution to journalArticleResearchpeer-review

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Junginger M, de Visser E, Hjort-Gregersen K, Koornneef J, Raven R, Faaij A et al. Technological learning in bioenergy systems. Energy Policy. 2006 Dec 1;34(18):4024-4041. https://doi.org/10.1016/j.enpol.2005.09.012