A semantic multi-criteria approach to evaluate different types of energy generation technologies. (December 2018)

• Record Type: Journal Article
• Authors: Martínez-García, Miriam; Valls, Aida; Moreno, Antonio; Aldea, Arantza
• Is Part Of: Environmental modelling & software. Volume 110(2018)
• Page Start: 129
• Page End: 138
• Publication Date: 2018-12
• Subjects: Decision support systems -- Semantic data -- Ontology -- ELECTRE -- Electricity generation plants; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.04.003
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Multi-Criteria Decision Aid methods are used to find the best option from a set of alternatives when multiple and conflicting criteria have to be optimized simultaneously. The evaluation of the suitability or risk of each alternative is usually performed by assigning a numerical value. However, sometimes the data required to measure a criterion may be found in the form of semantic values such as tags. This paper proposes a methodology to calculate the strength of an outranking relation for a pair of alternatives using semantic criteria following the principles of ELECTRE-III (i.e. by means of concordance and discordance indices). The preferences about semantic data are represented in an ontology by means of objective and subjective functions. The paper explains how this new methodology was applied to analyse different electricity generation technologies using environmental and economic criteria. Two scenarios are tested to show how semantic criteria may influence the final decision. Highlights: Decision support system for the selection of the best electricity generation plant. Semantic data is combined with numerical indicators using ELECTRE-III-SEM. Ontologies define the possible tags for Waste and Environmental pollutants. ELECTRE-III-SEM is a tool for qualitative criteria that can be used in many domains. Wind and Biomass are the best alternatives in the several tests done.