Literature DB >> 31351295

Assessing the sustainability of renewable energy: An empirical analysis of selected 18 European countries.

Qiang Wang1, Lina Zhan2.   

Abstract

There are many studies on the sustainability of renewable energy, mainly focusing on energy supply, economic, social, environmental and technological aspects, but there are few studies on the sustainability of renewable energy itself. This work focuses on the systematic and quantitative assessment of the sustainability of renewable energy itself by analyzing the sustainability of renewable energy in selected 18 European countries from 2007 to 2016. The consumption of renewable energy in these selected 18 countries accounts for ~95% of the consumption of renewable energy in the European Union. To scientifically evaluate the sustainability of renewable energy, 17 indicators are selected based on the energy-economy-environment theory. In order to deal with the high-dimensional, non-normal, and nonlinear complex data, and to assess the sustainability of renewable energy without standards, the projection pursuit algorithm and the real-coded accelerating genetic algorithm are combined to establish a comprehensive model to assess the sustainability of renewable energy. The results show that (i) the sustainability of renewable energy in Germany, the UK, France, and Italy is better than that in the other investigated countries; (ii) in the 17 indicators selected by the energy-economy-environment model, the factors of total energy demand, energy taxes, carbon dioxide emissions, sulfur oxides emissions, and nitrous oxides emissions exert a stronger impact on the sustainability of renewable energy; (iii) time-series analysis show that the general sustainable level is a wave of growth. Moreover, the proposed comprehensive model can effectively deal with the high-dimensional, non-normal, and nonlinear complex data, thus providing a feasible method for the quantitative analysis and evaluation of the sustainability of renewable energy.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Energy-economy-environment theory; Projection pursuit; Real-coded accelerating genetic algorithm; Renewable energy; Sustainability

Year:  2019        PMID: 31351295     DOI: 10.1016/j.scitotenv.2019.07.170

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


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