Implementação da técnica de self-healing em alimentadores de rede de distribuição de energia elétrica: estudo de caso

Abstract

With the regulation of the sector and the requirement of quality standards, distributors have invested in digital technologies and automation, such as Self-Healing, or self-recomposition capacity, the concept of Smart Grids, or intelligent networks, which enables the automatic recomposition of the energy supply. Self-Healing stands out as an automated system capable of detecting faults, isolating affected sections and restoring the energy supply quickly and effectively, reducing human intervention and impacts on consumers. This study addresses the challenge faced by distributors in increasing the reliability and efficiency of electrical networks in the face of failures, through automation to improve service quality. This work aims to analyze, in a practical and quantitative way, the impacts of Self-Healing on distribution networks, focusing on operational gains and improving quality indicators required by the distributor and the National Electric Energy Agency (ANEEL). The methodology is based on the creation of a simulation prototype of a real distribution network model, using georeferenced data from the concessionaire and open tools for creating diagrams. Quantitative analysis compares network performance with and without Self-Healing, considering interruption time and number of customers affected in real occurrences. In the case study analyzed, a significant reduction in DEC was observed, with gains of up to 69.91% in the first occurrence and 8.84% in the second. Given the results obtained, it is concluded that the implementation of the Self-Healing system brings significant benefits to the continuity of the electricity supply.