Lógica Fuzzy e Geoprocessamento para Instalação de Usinas Eólicas Offshore nas Regoões Sul e Sudeste do Brasil

  • Karen F. Paula Universidade Federal do ABC, Santo André - SP
  • Renata Sander Universidade Federal do ABC, Santo André - SP
  • André T. S. Melo Associação Brasileira de Energia Eólica, ABEEólica, S˜ao Paulo
  • Djalma M. Falcão Universidade Federal do Rio de Janeiro, Rio de Janeiro
  • Patricia T. L. Asano Universidade Federal do ABC, Santo André - SP
  • Joel D. Melo Universidade Federal do ABC, Santo André - SP
Keywords: Fuzzy Logic, Geographic Information System, Offshore Wind Energy


The search for renewable and efficient energy solutions has become a global trend due to the current climate change scenario and the increased demand for electricity. Thus, in several countries, the share of renewable sources in the electricity matrix has grown with the insertion of new energy sources, such as wind. This energy source has significantly contributed to the global energy transition and the trend is for the growth of wind energy to migrate to the sea. Brazil has good conditions for offshore wind farms as it has an extensive coastline and extensive experience in offshore operations in oil and gas. This paper presents a methodology that seeks better use of the wind resource available in the areas with the highest electricity consumption in Brazil to help planners and agents interested in new projects for the construction of offshore wind farms in Brazil’s South and Southeast regions. First, the proposed method evaluates the available wind resource considering technical, environmental, and social constraints, to identify the best offshore wind farms on the Brazilian coast. Considering that these restrictions present a high spatial dispersion in the study area, the proposal performs the information processing within a geographic information system. Then, a fuzzy logic model makes the joint evaluation of the constraints. As a result of the study, there are the 25 most favorable locations for the deployment of offshore wind farms.