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Considering Life Cycle Greenhouse Gas Emissions in Power System Expansion Planning for Europe and North Africa Using Multi-Objective Optimization

Junne, Tobias; Cao, Karl-Kiên; Miskiw, Kim Kira ORCID iD icon 1; Hottenroth, Heidi; Naegler, Tobias
1 Institut für Industriebetriebslehre und Industrielle Produktion (IIP), Karlsruher Institut für Technologie (KIT)

Abstract:

We integrate life cycle indicators for various technologies of an energy system model with high spatiotemporal detail and a focus on Europe and North Africa. Using multi-objective optimization, we calculate a pareto front that allows us to assess the trade-offs between system costs and life cycle greenhouse gas (GHG) emissions of future power systems. Furthermore, we perform environmental ex-post assessments of selected solutions using a broad set of life cycle impact categories. In a system with the least life cycle GHG emissions, the costs would increase by ~63%, thereby reducing life cycle GHG emissions by ~82% compared to the cost-optimal solution. Power systems mitigating a substantial part of life cycle GHG emissions with small increases in system costs show a trend towards a deployment of wind onshore, electricity grid and a decline in photovoltaic plants and Li-ion storage. Further reductions are achieved by the deployment of concentrated solar power, wind offshore and nuclear power but lead to considerably higher costs compared to the cost-optimal solution. Power systems that mitigate life cycle GHG emissions also perform better for most impact categories but have higher ionizing radiation, water use and increased fossil fuel demand driven by nuclear power. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000133069
Originalveröffentlichung
DOI: 10.3390/en14051301
Scopus
Zitationen: 11
Web of Science
Zitationen: 8
Dimensions
Zitationen: 11
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Industriebetriebslehre und Industrielle Produktion (IIP)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 03.2021
Sprache Englisch
Identifikator ISSN: 1996-1073
KITopen-ID: 1000133069
Erschienen in Energies
Verlag MDPI
Band 14
Heft 5
Seiten Art. Nr.: 1301
Vorab online veröffentlicht am 27.02.2021
Schlagwörter energy system modeling; life cycle assessment; multi-objective optimization
Nachgewiesen in Web of Science
Scopus
Dimensions
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