Resumo:
This study focuses on the Brazilian energy scenario and highlights the progressive increase
in the use of renewable sources in the country's electrical energy matrix. The main objective of
this study is to contribute to the search for solutions and encourage debates and reflections on the
future actions necessary for energy planning. To achieve this, the research employs computational
tools based on machine learning and data mining, using government and energy market data
sources. The research methodology begins with the analysis of historical data related to the
electricity market in Brazil, including policies, national guidelines and regulatory mechanisms.
The research then uses machine learning and data mining tools to forecast the electricity market
in the country. These forecasts are then compared with the horizon predicted by the Ten-Year
Energy Expansion Plan 2030. The methodology used includes the execution of forecast models,
highlighting the behavior of the energy market over time, using three different methods:
Multilayer Neural Networks Perceptron (MLP), Gaussian Process Regression (GPR) and Linear
Regression to project electrical generation by source in Brazil. The results indicate considerable
growth in renewable sources in the national energy market until 2030, approaching the objective
of the Ten-Year Energy Expansion Plan of reaching 90% renewability, covering sources such as
hydroelectric, biomass, wind and solar. The Linear Regression method achieves 86%
renewability, while the Gaussian Process Regression method achieves 90%, and the Multilayer
Perceptron Neural Networks method reaches 88%. Likewise, the scenarios proposed for the
Brazilian energy market intended to gradually increase the use of renewable sources in the
electrical energy matrix and its growth potential. The projection of the electricity market forecast
made it possible to identify market behavior patterns, allowing trends and changes in the market
to be anticipated. These forecasts are intended to provide information to support the development
of actions in the energy planning process, contributing to the transition to more sustainable and
renewable sources of energy in Brazil.
