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Analysis of technology improvement opportunities for a 1.5 MW wind turbine using a hybrid stochastic approach in life cycle assessment

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  • Ozoemena, Matthew
  • Hasan, Reaz
  • Cheung, Wai Ming

Abstract

This paper presents an analysis of potential technological advancements for a 1.5 MW wind turbine using a hybrid stochastic method to improve uncertainty estimates of embodied energy and embodied carbon. The analysis is specifically aimed at these two quantities due to the fact that LCA based design decision making is of utmost importance at the concept design stage. In the presented case studies, better results for the baseline turbine were observed compared to turbines with the proposed technological advancements. Embodied carbon and embodied energy results for the baseline turbine show that there is about 85% probability that the turbine manufacturers may have lost the chance to reduce carbon emissions, and 50% probability that they may have lost the chance to reduce the primary energy consumed during its manufacture. The paper also highlights that the adopted methodology can be used to support design decision making and hence is more feasible for LCA studies.

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  • Ozoemena, Matthew & Hasan, Reaz & Cheung, Wai Ming, 2016. "Analysis of technology improvement opportunities for a 1.5 MW wind turbine using a hybrid stochastic approach in life cycle assessment," Renewable Energy, Elsevier, vol. 93(C), pages 369-382.
  • Handle: RePEc:eee:renene:v:93:y:2016:i:c:p:369-382
    DOI: 10.1016/j.renene.2016.03.012
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    1. Niklas Andersen & Ola Eriksson & Karl Hillman & Marita Wallhagen, 2016. "Wind Turbines’ End-of-Life: Quantification and Characterisation of Future Waste Materials on a National Level," Energies, MDPI, vol. 9(12), pages 1-24, November.
    2. He, Li & Zhang, Shiyue & Chen, Yizhong & Ren, Lixia & Li, Jing, 2018. "Techno-economic potential of a renewable energy-based microgrid system for a sustainable large-scale residential community in Beijing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 631-641.

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