Ciência de dados aplicada a dados abertos do operador nacional do sistema elétrico brasileiro.

Abstract

This paper aims to analyze the main concepts and techniques of data science, applying them to open data from the National Electric System Operator (ONS), with a special focus on Micro and Mini Distributed Generation (MMGD). To this end, interactive reports were developed that allow an in-depth analysis of the ONS data, in addition to the creation of models that aim to predict energy consumption in different regions of the country during specific days, especially in situations of abrupt variations in consumption and generation that can impact the stability of the electrical system. Machine learning techniques were used to build these models, with the aim of providing support for strategic decision-making, improving the response of the electrical system and contributing to a more sustainable future in energy management.