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


A hybrid stochastic method for analysing uncertainty for wind turbine design.

Analysing embodied energy and embodied carbon for wind turbine at design stage.

Uncertainty estimate for potential technological advancement of wind turbine.

Methodology to support LCA in wind turbine design decision making.


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.


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

List of symbols and abbreviations

  • LCA, life cycle assessment;
  • EEC, embodied energy coefficient;
  • EF, emission factor;
  • DQI, data quality indicator;
  • HDS, hybrid data quality INDICATOR and Statistical;
  • MCS, Monte Carlo simulation;
  • K–S, Kolmogorov–Smirnov;
  • MRE, mean magnitude of relative error;
  • MHDS, mean of HDS result;
  • MDQI, mean of DQI result;
  • CV, coefficient of variation;
  • σ, standard deviation;
  • μ, mean;
  • NM, least number of data points required;
  • NMD, least number of required data points for individual parameter distribution estimation;
  • NP, number of parameters involved;
  • NREL, National Renewable Energy Laboratory;
  • MW, megawatt;
  • TIO, technology improvement opportunities;
  • CFRP, carbon fibre reinforced plastic;
  • PDF, probability distribution function;
  • CDF, cumulative distribution function

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