Reconfiguração de Redes de Distribuição de Energia Elétrica Utilizando Aprendizado de Máquina

Reconfiguração de Redes de Distribuição de Energia Elétrica Utilizando Aprendizado de Máquina: Electrical networks are composed of stages of generation, transmission, and distribution of energy. Distribution networks (RD) are an important element of the electricity grid because it provides the effective delivery of energy to end users. The RD’s are subject to failure and their optimization is of fundamental importance in the context of Smart Grids, where it is sought a greater efficiency of the processes involved between the production and distribution of energy. The distribution networks (RD) have topologies and loads of various type. This dissertation proposes a method and algorithm for the reconfiguration of electrical network using machine learning with linear regression and branch exchange algorithm aiming the optimization of RD operation. The method and algorithm proposed do maneuvers in the RD as transfer and load balancing and aiming to increase its level of reliability. The proposal is validated in a test network of IEEE (IEEEbus14) using simulation and testing environment implemented in “R” language and using the Newton Raphson method to calculate the power flow. The solution developed show satisfactory in supporting the decision-making for three reconfigurations of distribution networks in the context of the Smart Grid.