Análise comparativa dos indicadores de serviço de uma distribuidora de energia elétrica nos alimentadores com e sem self-healing

Abstract

The growing demand for electrical energy and the need to ensure continuous and reliable supply have led the electrical industry to seek innovative solutions to improve the efficiency and reliability of distribution networks. In this context, Self-healing emerges as a promising technique along with the concept of Smart Grids. Self-healing involves the application of automation processes to quickly and autonomously detect and correct faults in the electrical distribution network without the need for human intervention. The rationale for implementing Self-healing is related to the need for electric utilities to maintain their performance indicators in compliance with the goals set by the National Electric Energy Agency (ANEEL), to avoid financial penalties and reparations to consumers. Self-healing contributes to reducing operational costs and minimizing interruptions in power supply. The study focuses on analyzing the impact of Self-healing implementation in an electrical distribution network. Specific objectives include investigating the improvements observed in network performance indicators after the adoption of Self-healing, comparing maneuvers performed by human operators and those executed by Selfhealing, and comprehensively understanding how Self-healing enhances the reliability, resilience, and operational efficiency of the electrical distribution infrastructure. The study’s conclusions highlight that the implementation of Self-healing has resulted in significant improvements in distribution network performance indicators, especially in feeders with a more pronounced history of defects, providing them with greater stability and homogeneity. The research reveals that, after the adoption of Self-healing, the average System Average Interruption Duration Index (SAIDI) of 63% of the feeders in the state of Ceará showed a notable improvement, with an average reduction of 11%. Additionally, it was observed that, from 2019 to 2022, the average SAIDI of feeders with Self-healing has been gradually approaching those without this technology, reducing the difference from 130% in 2019 to less than 20% in 2022. Another relevant result demonstrates that feeders equipped with Self-healing tend to experience a more significant reduction in SAIDI compared to their counterparts. Finally, when analyzing the specific feeder GRM01M5, it is noted that the implementation of Self-healing broke the increasing trend in the SAIDI of this feeder.