Forest Bioelectricity in Brazil: Distribution and Spatial-Time Dependence

Abstract

This study was to present a methodology for analyzing the distribution and spatial-time dependence of the supply of forest bioelectricity in Brazil, from 2000 to 2019. The data for the granting of forest biomass thermoelectric plants were obtained from the National Electric Energy Agency (in Portuguese Agência Nacional de Energia Elétrica –ANEEL). It used the exploratory analysis of spatial data, and as neighborhood criteria the spatial weighting matrices of k-neighbors closest and based on distance, as well as the global and local Moran indices to detect the presence of spatial dependence. The analysis of the situation, by quartile, showed the states of the central-southern portion of Brazil as the main locations of forest thermals. <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{I}_{\mathrm {Moran\_{}Global}}$ </tex-math></inline-formula> highlighted the decrease in spatial autocorrelation between the years 2000 and 2019, associated with the implementation of new thermoelectric plants by the large groups Fibria, Klabin and Suzano Celulose throughout the national territory. The local index ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{I}_{\mathrm {Moran\_{}Local}}$ </tex-math></inline-formula> ) pointed out high-powered clusters, especially in the early years, highlighting: the Bahia, Espírito Santo and Minas Gerais axis, the Paraná thermal plants and Mato Grosso do Sul thermal plants. The local index also pointed outliers, which indicated possibility of associating thermoelectric plants with other activities, such as wood production and industries in the steel and paper and cellulose segment. The knowledge of the spatial pattern of the forest bioelectricity sector presented can help new feasibility studies for the implementation in bioelectricity and/or stimulate the development of public policies, focused on cluster regions and adjacent areas, which results in the growth of forest generation.