Improving uncertainty analysis of embodied energy and embodied carbon in wind turbine design

Matthew Ozoemena, Wai Ming Cheung, Reaz Hasan

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
40 Downloads (Pure)

Abstract

In this paper, a method for improving uncertainty estimates of embodied carbon and embodied energy is presented and discussed. Embodied energy and embodied carbon results are the focus of this analysis due to the fact that, at the conceptual design stage, these two are the most important quantities for decision making in life cycle assessment (LCA) studies. The use of renewable and new energy sources and the development of cleaner and more efficient energy technologies will play a major role in the sustainable development of a future energy strategy. Environmental protection,economic and social cohesion and diversification and security of energy supply are highlighted by the International Energy Agency as a high priority for the development of cleaner and more efficient energy systems and promotion of renewable energy sources. In the case studies presented,better results for the baseline turbine were observed compared to turbines with the proposed technology improvement opportunities. Embodied energy and embodied carbon results for the baseline turbine show an about 50 % probability that the turbine manufacturer may have lost the chance to reduce carbon emissions and 85 % probability that the turbine manufacturer may have lost the chance to reduce the primary energy consumed during its manufacture. The proposed approach is therefore a feasible alternative when more reliable results are desired for LCA-based design decision making.
Original languageEnglish
Pages (from-to)1565-1577
Number of pages13
JournalInternational Journal of Advanced Manufacturing Technology
Volume94
Issue number5-8
Early online date18 Jan 2017
DOIs
Publication statusPublished - 1 Feb 2018

Keywords

  • Embodied energy
  • Embodied carbon
  • Technology improvement opportunities
  • Uncertainty
  • 1.5 MW wind turbine

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