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AHP algorithm used to select suitable abandoned underground mines for energy storage infrastructure – iCAES technology. A specific case study for León (Spain)

In the energy transition, the promotion of renewable sources entails the development of storage technologies to manage the mismatch between energy production and demand. In this scenario, the use of CAES (Compressed Air Energy Storage) technology enables the efficient and cost-effective storage of l...

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Autores principales: Pous de la Flor, Juan, Castañeda, M. Cruz, Arlandi, Manuel, Ordás, Fernando, Pous Cabello, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10559770/
https://www.ncbi.nlm.nih.gov/pubmed/37809878
http://dx.doi.org/10.1016/j.heliyon.2023.e20045
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author Pous de la Flor, Juan
Castañeda, M. Cruz
Arlandi, Manuel
Ordás, Fernando
Pous Cabello, Juan
author_facet Pous de la Flor, Juan
Castañeda, M. Cruz
Arlandi, Manuel
Ordás, Fernando
Pous Cabello, Juan
author_sort Pous de la Flor, Juan
collection PubMed
description In the energy transition, the promotion of renewable sources entails the development of storage technologies to manage the mismatch between energy production and demand. In this scenario, the use of CAES (Compressed Air Energy Storage) technology enables the efficient and cost-effective storage of large amounts of energy. However, this technology is developed in salt domes who have an inherent risk associated of underground exploration phase. To address this, we propose to develop an infrastructure (iCAES) in abandoned underground mines, where the exploration phase is completed and well known. For its implementation, this paper defines a structure hierarchization method gathers the technical and socio-economic criteria. It involves a multi-criteria problem, and the correct selection of the location must be based on specific mathematical algorithms. For this case the Analytic Hierarchy Process (AHP) from multi-criteria decision making (MCDM) methods allows quantified by means of a scientific and mathematical scale and the assignment of weights, so that it is possible to evaluate different alternatives. This is possible thanks to the application of the AHP model in absolute terms. The information gathering has been based on the specific case study of coal basins in the north of Spain, in the region of León. Considering the proposed methodology, the most suitable alternative locations to implement iCAES in the region of León were identified.
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spelling pubmed-105597702023-10-08 AHP algorithm used to select suitable abandoned underground mines for energy storage infrastructure – iCAES technology. A specific case study for León (Spain) Pous de la Flor, Juan Castañeda, M. Cruz Arlandi, Manuel Ordás, Fernando Pous Cabello, Juan Heliyon Research Article In the energy transition, the promotion of renewable sources entails the development of storage technologies to manage the mismatch between energy production and demand. In this scenario, the use of CAES (Compressed Air Energy Storage) technology enables the efficient and cost-effective storage of large amounts of energy. However, this technology is developed in salt domes who have an inherent risk associated of underground exploration phase. To address this, we propose to develop an infrastructure (iCAES) in abandoned underground mines, where the exploration phase is completed and well known. For its implementation, this paper defines a structure hierarchization method gathers the technical and socio-economic criteria. It involves a multi-criteria problem, and the correct selection of the location must be based on specific mathematical algorithms. For this case the Analytic Hierarchy Process (AHP) from multi-criteria decision making (MCDM) methods allows quantified by means of a scientific and mathematical scale and the assignment of weights, so that it is possible to evaluate different alternatives. This is possible thanks to the application of the AHP model in absolute terms. The information gathering has been based on the specific case study of coal basins in the north of Spain, in the region of León. Considering the proposed methodology, the most suitable alternative locations to implement iCAES in the region of León were identified. Elsevier 2023-09-12 /pmc/articles/PMC10559770/ /pubmed/37809878 http://dx.doi.org/10.1016/j.heliyon.2023.e20045 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Pous de la Flor, Juan
Castañeda, M. Cruz
Arlandi, Manuel
Ordás, Fernando
Pous Cabello, Juan
AHP algorithm used to select suitable abandoned underground mines for energy storage infrastructure – iCAES technology. A specific case study for León (Spain)
title AHP algorithm used to select suitable abandoned underground mines for energy storage infrastructure – iCAES technology. A specific case study for León (Spain)
title_full AHP algorithm used to select suitable abandoned underground mines for energy storage infrastructure – iCAES technology. A specific case study for León (Spain)
title_fullStr AHP algorithm used to select suitable abandoned underground mines for energy storage infrastructure – iCAES technology. A specific case study for León (Spain)
title_full_unstemmed AHP algorithm used to select suitable abandoned underground mines for energy storage infrastructure – iCAES technology. A specific case study for León (Spain)
title_short AHP algorithm used to select suitable abandoned underground mines for energy storage infrastructure – iCAES technology. A specific case study for León (Spain)
title_sort ahp algorithm used to select suitable abandoned underground mines for energy storage infrastructure – icaes technology. a specific case study for león (spain)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10559770/
https://www.ncbi.nlm.nih.gov/pubmed/37809878
http://dx.doi.org/10.1016/j.heliyon.2023.e20045
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