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  A stochastic fuzzy multicriteria methodology for energy planning decision support: Case study of the electrification of the Greek road transport sector

Koutsandreas, D., Keppo, I. (2025 online): A stochastic fuzzy multicriteria methodology for energy planning decision support: Case study of the electrification of the Greek road transport sector. - Technological Forecasting and Social Change, 222, 124404.
https://doi.org/10.1016/j.techfore.2025.124404

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 Urheber:
Koutsandreas, Diamantis1, Autor                 
Keppo, Ilkka2, Autor
Affiliations:
1Potsdam Institute for Climate Impact Research, Potsdam, ou_persistent13              
2External Organizations, ou_persistent22              

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 Zusammenfassung: Providing robust planning insights requires transitioning from single-criterion, definitive frameworks to approaches that handle trade-offs and communicate result conditionality. This paper introduces an integrated methodology for energy planning, combining life-cycle impact assessment with decision support. Our framework incorporates often-overlooked aspects in energy planning (e.g., resource depletion and biodiversity) and allows us to reflect stakeholder risk profiles, preferences, and uncertainties about future energy and economic states. Scenarios are handled with the fuzzy group utility and maximum regret measures, while strategies are evaluated with the fuzzy VIKOR and TOPSIS methods. The framework advances existing multicriteria approaches by innovatively combining and contextually adapting existing methods, embedding them within a robust modelling framework. It provides comprehensive decision support by identifying optimal strategies across decision-maker profiles and explicitly communicating result contingency and diversity linked to uncertainties and policy preferences. The methodology is demonstrated for Greece's road transport sector, evaluating three fleet electrification strategies for 2040. Results revealed that aggressive electrification may induce significant negative repercussions on resources, human health, and ecosystems. Conversely, moderate electrification emerged as the most effective strategy in 79 % of cases across risk profiles and policy objective portfolios, suggesting the combination of technological shifts with resource-neutral lifestyle changes for road transport decarbonization.

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Sprache(n): eng - English
 Datum: 2023-06-222025-10-192025-10-30
 Publikationsstatus: Online veröffentlicht
 Seiten: 17
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.techfore.2025.124404
PIKDOMAIN: RD3 - Transformation Pathways
Organisational keyword: RD3 - Transformation Pathways
Regional keyword: Europe
Research topic keyword: Energy
Model / method: Decision Theory
Research topic keyword: Decarbonization
Research topic keyword: Economics
Research topic keyword: Climate Policy
Research topic keyword: Biodiversity
Model / method: Open Source Software
Model / method: Quantitative Methods
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Land use
Research topic keyword: Health
MDB-ID: pending
OATYPE: Hybrid Open Access
Working Group: Integrated Assessment Modelling
 Art des Abschluß: -

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Titel: Technological Forecasting and Social Change
Genre der Quelle: Zeitschrift, SCI, Scopus
 Urheber:
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 222 Artikelnummer: 124404 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/technological-forecasting-social-change
Publisher: Elsevier