Análise de Fatores Socioeconômicos em Relação ao Crescimento da Geração Distribuída no Brasil

  • Guilherme Rezende Pereira Camargo Instituto Federal de Educação, Ciência e Tecnologia de Goiás – IFG–Câmpus Itumbiara, Goiás Núcleo de Pesquisas em Sistemas de Energia – NuPSE
  • Renan Moreira Soares Instituto Federal de Educação, Ciência e Tecnologia de Goiás – IFG–Câmpus Itumbiara, Goiás Núcleo de Pesquisas em Sistemas de Energia – NuPSE
  • Lucas da Mata Santana Borges Instituto Federal de Educação, Ciência e Tecnologia de Goiás – IFG–Câmpus Itumbiara, Goiás Núcleo de Pesquisas em Sistemas de Energia – NuPSE
  • Leonardo Garcia Marques Instituto Federal de Educação, Ciência e Tecnologia de Goiás – IFG–Câmpus Itumbiara, Goiás Núcleo de Pesquisas em Sistemas de Energia – NuPSE
  • Marcelo Escobar de Oliveira Instituto Federal de Educação, Ciência e Tecnologia de Goiás – IFG–Câmpus Itumbiara, Goiás Núcleo de Pesquisas em Sistemas de Energia – NuPSE
Keywords: Correlation Coefficient, Socioeconomic Indices, Python Programming, Solar Photovoltaic Modules

Abstract

Over the past few years, the issue of using renewable sources to generate electricity has been highlighted, after all, conventional means degrade the environment, in addition to requiring a high generation cost. This perspective takes us to the photovoltaic scenario, with the first solar plant being installed in Brazil in 2011, from that onwards, a strong generation model is evidenced to address the issues of sustainable economic development. Currently, the energy generated through photovoltaic solar modules has grown exponentially and still has a great generation potential, after all has an excellent rate of solar irradiation, but when analyzing this potential, which has not yet been reached, questions are raised about variables that can leverage this growth or that are somehow correlated. Thus, the current work aims to raise studies on photovoltaic systems, the influence of socioeconomic factors in relation to the growth of photovoltaic generation, using statistical techniques to analyze the level of correlation between these variables. To carry out this analysis, it was necessary to obtain data from certain regions, such as the socioeconomic indices being taken from the website of the Brazilian Institute of Geography and Statistics and the installed power, obtained through the website of the National Agency of Electricity. Thus, it is possible to apply mathematical techniques and develop graphics through the Python programming language, finally generating results where it is possible to quantify the correlation and state that a certain socioeconomic factor is responsible for such a generation index in that particular analyzed location.
Published
2022-11-30
Section
Articles