A Fuzzy Approach to Assess the Perception of a Rural Community Concerning the Impact of Distributed Power Generation on Local Sustainability

• Autor(a) principal: Silva,Eduardo Teixeira da
• Data de Publicação: 2021
• Outros Autores: Martins,Márcio André Fernandes, Ferreira,Adonias Magdiel Silva, Rodriguez,Jorge Laureano Moya
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Brazilian Archives of Biology and Technology
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132021000100620
• topic: Distributed Generation; sustainability; Fuzzy logic; rural communities

Abstract This paper aims to evaluate the perception of residents of a rural quilombola community, about the impacts of distributed energy generation (DG) on the social, economic and environmental dimensions. The main challenge of the proposed model was to quantify the main perceptions of the target population of the research, as well as maintain the coherence of the specifications of the sustainability parameters. Diffuse modeling allows the transformation of linguistic variables into numerical values, the disadvantage is the dependence of the specialist to construct the rules. The methodology used was the application of a semi-structured questionnaire, and the results were used as a reference to build the discourse domain of the input variables of the Fuzzy inference system, which generated an index of 54.1% classified in the category partially sustainable. Specifically, the economic and social dimensions obtained an index of 46.7% and the environmental dimension of 69%. From the perspective of the perception of the respondents, the variables with the greatest impact were: landscape change (LCH) 92%, environmental awareness (EA) and reduction of global warming (GW) with values of both 69%. The variable of the most prominent economic dimension was: cost of the system with a value of 69%. In the social dimension, the variables with the greatest impact were: Community Acceptability (AC), Expansion of the support network (ESN) with values of 69%. The proposed model allowed us to interpret the respondents' perception, and can be used to generate effective actions that solve the identified demands.