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A distance-to-sustainability-target approach for indicator aggregation and its application for the comparison of wind energy alternatives
Buchmayr, A.; Taelman, S.E.; Thomassen, G.; Verhofstadt, E.; Van Ootegem, L.; Dewulf, J. (2023). A distance-to-sustainability-target approach for indicator aggregation and its application for the comparison of wind energy alternatives. Renew. Sust. Energ. Rev. 185: 113608. https://dx.doi.org/10.1016/j.rser.2023.113608
In: Renewable & Sustainable Energy Reviews. Elsevier/Elsevier Science: Oxford. ISSN 1364-0321; e-ISSN 1879-0690, meer
Peer reviewed article  

Beschikbaar in  Auteurs 

Author keywords
    Sustainability assessment; Multi-criteria decision analysis; Sustainability boundary; Indicator aggregation; Single score; Wind energy

Auteurs  Top 
  • Buchmayr, A., meer
  • Taelman, S.E., meer
  • Thomassen, G., meer
  • Verhofstadt, E., meer
  • Van Ootegem, L., meer
  • Dewulf, J., meer

Abstract
    Sustainability impact assessments studies combine several indicators to cover environmental, economic and social impacts. These indicators describe different impact pathways and are expressed in different units, which makes comparing alternatives challenging. An aggregated metric is required to facilitate the presentation and communication of sustainability. The presented aggregation framework is based on the distance-to-target method NR-TOPSIS and adapted to a distance-to-sustainability-target approach. A procedure is given for aggregating 12 sustainability indicators into a single score sustainability indicator. Reference points for normalization of diverse impact indicators and weighting factors are investigated. The framework was applied to a wind energy case study comparing one offshore and two onshore alternatives. The case study results were compared using both a dashboard of 12 endpoint indicators and an aggregated sustainability indicator. The indicator was presented on a sustainability scale that indicated the distance of the investigated cases to an ideal (sustainable) solution. A sensitivity analysis of the weighting factors showed that the distribution of weights influenced the ranking of alternatives, especially when the alternatives are positioned close to each other on the sustainability scale, as it is the case for the wind energy scenarios. For most of the weighting scenarios, the onshore wind energy project using permanent magnet synchronous generators appeared to be the most sustainable solution.

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