Otimização da manutenção centrada na confiabilidade em redes de distribuição de energia elétrica: uma abordagem orientada a regulação baseada em desempenho

Abstract

This study explores the Reliability-Centered Maintenance (RCM), supported by Predictive Reliability Analysis (PRA), focusing on optimizing maintenance frequency in power distribution networks, considering the strict regulatory context imposed by the National Electric Energy Agency (ANEEL). ANEEL oversees the distribution utilities by assessing individual and collective indicators related to the

continuity of electricity supply. Consequently, utilities face penalties for non- compliance with these indicator targets, and an effective approach to mitigate these

penalties involves careful planning of network equipment maintenance activities to maximize reliability indices and minimize maintenance costs. In this context, this research aims to optimize maintenance frequency to minimize costs and penalties associated with the System Average Interruption Duration Index (SAIDI). The proposed RCM model is based on chronological PRA, employing the State Enumeration Analytical Method (SEAM) and state aggregation techniques in Markov Chains. Additionally, it integrates the use of Optimal Power Flow (OPF) in electric distribution networks with meshed topology. The component degradation process is modeled using the Weibull distribution. The nonhomogeneous Markovian model resulting from this distribution is converted into a homogeneous model

through series stage modeling. A Particle Swarm Optimization is applied in a multi- criteria optimization model. The results indicate significant penalty reductions with

a high cost-benefit ratio, highlighting the economic efficacy of the proposed method for electric utilities, in alignment with ANEEL regulations.