Prospective analysis of life-cycle indicators through endogenous integration into a national power generation model

  • Diego García-Gusano
  • , Mario Martín-Gamboa
  • , Diego Iribarren*
  • , Javier Dufour
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    44 Citations (Scopus)

    Abstract

    Given the increasing importance of sustainability aspects in national energy plans, this article deals with the prospective analysis of life-cycle indicators of the power generation sector through the case study of Spain. A technology-rich, optimisation-based model for power generation in Spain is developed and provided with endogenous life-cycle indicators (climate change, resources, and human health) to assess their evolution to 2050. Prospective performance indicators are analysed under two energy scenarios: a business-as-usual one, and an alternative scenario favouring the role of carbon dioxide capture in the electricity production mix by 2050. Life-cycle impacts are found to decrease substantially when existing fossil technologies disappear in the mix (especially coal thermal power plants). In the long term, the relatively high presence of natural gas arises as the main source of impact. When the installation of new fossil options without CO2 capture is forbidden by 2030, both renewable technologies and-to a lesser extent-fossil technologies with CO2 capture are found to increase their contribution to electricity production. The endogenous integration of life-cycle indicators into energy models proves to boost the usefulness of both life cycle assessment and energy systems modelling in order to support decision- and policy-making.

    Original languageEnglish
    Article number39
    JournalResources
    Volume5
    Issue number4
    DOIs
    Publication statusPublished - 1 Dec 2016

    Keywords

    • Electricity
    • Energy planning
    • Energy system model
    • Life cycle assessment
    • Life-cycle indicator
    • Scenario analysis
    • Sustainability

    Fingerprint

    Dive into the research topics of 'Prospective analysis of life-cycle indicators through endogenous integration into a national power generation model'. Together they form a unique fingerprint.

    Cite this