Spatial distribution estimation of residential photovoltaic systems diffusion using binary logistic regression

Abstract

The increase in the use of emerging technologies, such as photovoltaic systems (SFV), highlights the importance of identifying areas with better conditions for their diffusion, thus promoting the adoption of renewable energy sources. Therefore, this work seeks to estimate the spatial distribution of household SFV using Binary Logistic Regression and the socioeconomic characteristics of the inhabitants. The values of the probabilities of installing SFVs, calculated using binary logistic regression, correspond to the response of the inhabitants regarding their decision to install an SFV. Thus, probability values close to one were found when the inhabitant's response was affirmative and close to zero when that response was negative. The diffusion results are shown using heat maps that facilitate the identification of areas with better conditions for the diffusion of SFVs. Therefore, the application of the methodology by renewable energy development entities can help them better direct their resources, in order to promote the dissemination of photovoltaic systems