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Comparative Sustainability Study of Energy Storage Technologies Using Data Envelopment Analysis

Abstract

The transition to energy systems with a high share of renewable energy depends on the availability of technologies that can connect the physical distances or bridge the time differences between the energy supply and demand points. This study focuses on energy storage technologies due to their expected role in liberating the energy sector from fossil fuels and facilitating the penetration of intermittent renewable sources. The performance of 27 energy storage alternatives is compared considering sustainability aspects by means of data envelopment analysis. To this end, storage alternatives are first classified into two clusters: fast-response and long-term. The levelized cost of energy, energy and water consumption, global warming potential, and employment are common indicators considered for both clusters, while energy density is used only for fast-response technologies, where it plays a key role in technology selection. Flywheel reveals the highest efficiency between all the fast-response technologies, while green ammonia powered with solar energy ranks first for long-term energy storage. An uncertainty analysis is incorporated to discuss the reliability of the results. Overall, results obtained, and guidelines provided can be helpful for both decision-making and research and development purposes. For the former, we identify the most appealing energy storage options to be promoted, while for the latter, we report quantitative improvement targets that would make inefficient technologies competitive if attained. This contribution paves the way for more comprehensive studies in the context of energy storage by presenting a powerful framework for comparing options according to multiple sustainability indicators.

Funding source: The authors would like to acknowledge financial support from the Spanish Ministry of 7 Economy and Competitiveness RTI2018-093849-BC33 and thank the Catalan 8 Government (2017-SGR-1409). This work was partially funded by the Ministerio de 9 Ciencia, Innovacón y Universidades - Agencia Estatal de Investigación (AEI) 10 (RED2018-102431-T).
Countries: Spain ; United Kingdom
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/content/journal3342
2022-03-17
2022-10-06
http://instance.metastore.ingenta.com/content/journal3342
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