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Prospective Analysis of Life-Cycle Indicators through Endogenous Integration into a National Power Generation Model

Author

Listed:
  • Diego García-Gusano

    (Systems Analysis Unit, Instituto IMDEA Energía, Av. Ramón de la Sagra 3, Móstoles E-28935, Spain
    These authors contributed equally to this work.)

  • Mario Martín-Gamboa

    (Systems Analysis Unit, Instituto IMDEA Energía, Av. Ramón de la Sagra 3, Móstoles E-28935, Spain
    These authors contributed equally to this work.)

  • Diego Iribarren

    (Systems Analysis Unit, Instituto IMDEA Energía, Av. Ramón de la Sagra 3, Móstoles E-28935, Spain)

  • Javier Dufour

    (Systems Analysis Unit, Instituto IMDEA Energía, Av. Ramón de la Sagra 3, Móstoles E-28935, Spain
    Department of Chemical and Energy Technology, Rey Juan Carlos University, c/Tulipán s/n, Móstoles E-28933, Spain)

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 CO 2 capture is forbidden by 2030, both renewable technologies and—to a lesser extent—fossil technologies with CO 2 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.

Suggested Citation

  • Diego García-Gusano & Mario Martín-Gamboa & Diego Iribarren & Javier Dufour, 2016. "Prospective Analysis of Life-Cycle Indicators through Endogenous Integration into a National Power Generation Model," Resources, MDPI, vol. 5(4), pages 1-17, November.
    • Handle: RePEc:gam:jresou:v:5:y:2016:i:4:p:39-:d:82716
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    References listed on IDEAS

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