dc.contributor.authorSánchez-Lozano, Juan Miguel
dc.contributor.authorRamos Escudero, Adela
dc.contributor.authorGil García, Isabel Cristina
dc.contributor.authorGarcía-Cascales, M. Socorro
dc.contributor.authorMolina-García, Ángel
dc.date.accessioned2022-08-29T14:52:01Z
dc.date.available2022-08-29T14:52:01Z
dc.date.issued2022-08-08
dc.identifier.issn0957-4174
dc.identifier.urihttp://hdl.handle.net/20.500.12226/1231
dc.description.abstractIn the last decades, a considerable number of studies have been conducted to find the optimal locations for renewable energy facilities. The reviewed literature demonstrates how the combination of spatial representation computer tools, such as geographic information systems (GIS), with multi-criteria decision making (MCDM) methodologies, has successfully solved the problem of identifying optimal locations. Furthermore, since the appearance of fuzzy logic, the combination approaches have extended to the field of fuzzy sets to consider the imprecision and vagueness that some criteria may involve. In this paper, we propose a comparative analysis among fuzzy versions of MCDM methodologies, including GIS technologies, for the optimal site selection of offshore wind power plants. With this aim, we combined a classical pair-wise comparison method (AHP) with two distance-based approaches (TOPSIS and VIKOR), applying GIS software and comparing the two most extended fuzzy membership functions: triangular and linear. As a case study, this optimal location problem was applied to offshore wind site selection in the Gulf of Maine (USA). Initially, 56 alternatives for potential locations were identified from 22,331 km study area. After applying the AHP methodology, the weights of the criteria were obtained, turning out to be the wind speed and bathymetry the most important criteria. The results demonstrate the robustness of the fuzzy TOPSIS methodology against potential variations in the criteria weights, since the best alternatives (optimal locations) and almost 90% of the 25 top–ranked alternatives were matching. Likewise, the rankings of alternatives illustrate that the use of triangular or linear fuzzy membership functions does not cause significant differences after applying the fuzzy VIKOR methodology and ArcGIS software. In fact, the most appropriate alternative is the same for both cases, and there is only an exchange of positions among the top–ranked alternatives. The proposed solutions can be applied to other locations and both onshore and offshore installations.es
dc.language.isoenes
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleA GIS-based offshore wind site selection model using fuzzy multi-criteria decision-making with application to the case of the Gulf of Mainees
dc.typearticlees
dc.description.course2021-22es
dc.identifier.doi10.1016/j.eswa.2022.118371
dc.journal.titleExpert Systems with Applicationses
dc.publisher.departmentDepartamento de Ingeniería Industriales
dc.publisher.facultyEscuela de Ciencias Técnicas e Ingenieríaes
dc.rights.accessRightsopenAccesses
dc.subject.keywordWind offshorees
dc.subject.keywordOptimal selectiones
dc.subject.keywordAHPes
dc.subject.keywordFuzzy GISes
dc.subject.keywordMulti-criteria selectiones
dc.subject.keywordEnergy transitiones


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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