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Open AccessFeature PaperArticle

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

1
Systems Analysis Unit, Instituto IMDEA Energía, Av. Ramón de la Sagra 3, Móstoles E-28935, Spain
2
Department of Chemical and Energy Technology, Rey Juan Carlos University, c/Tulipán s/n, Móstoles E-28933, Spain
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Witold-Roger Poganietz
Resources 2016, 5(4), 39; https://doi.org/10.3390/resources5040039
Received: 16 September 2016 / Revised: 28 October 2016 / Accepted: 8 November 2016 / Published: 12 November 2016
(This article belongs to the Special Issue Advanced Analysis of Energy Systems under Sustainability Aspects)
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. View Full-Text
Keywords: electricity; energy planning; energy system model; life cycle assessment; life-cycle indicator; scenario analysis; sustainability electricity; energy planning; energy system model; life cycle assessment; life-cycle indicator; scenario analysis; sustainability
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MDPI and ACS Style

García-Gusano, D.; Martín-Gamboa, M.; Iribarren, D.; Dufour, J. Prospective Analysis of Life-Cycle Indicators through Endogenous Integration into a National Power Generation Model. Resources 2016, 5, 39.

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