Otimização do intervalo de inspeção de linhas de transmissão considerando-se incertezas nos dados de falha

Abstract

The power transmission companies have the quality of the service assessed through indicators associated with the availability of their systems and equipment. The Brazilian Electricity Regulatory Agency (“ANEEL - Agência Nacional de Energia Elétrica”) defines the Variable Portion (VP) as a value to be deducted from the power transmission company revenue due to the inadequacy of the transmission service. In this sense, the aim of this work is to optimize the inspection interval of this equipment through the VP minimization under uncertainty. This optimization is carried out through a probabilistic methodology for the maintenance management of transmission lines of the ELETRONORTE (the local power transmission company) system. This probabilistic approach encompasses technical and economic aspects and usual and real life features of this equipment. A probabilistic approach based on continuous Markov chains is applied to model the transmission line, in order to evaluate the effect of the inspection interval on the VP. The transition rates of the model have uncertainties due to the execution of a stochastic process during a finite time interval, that is, sample variability. These uncertainties are propagated to VP using the techniques of Latin Hypercube Sampling, Fuzzy Sets and Point Estimate Method. These techniques are used to optimize the inspection interval of transmission lines considering the effect of these uncertainties. In addition, a comparative evaluation between the uncertainty propagation methods cited above and Monte Carlo Simulation is also carried out. The tests results with a transmission line from ELETRONORTE system demonstrated that the proposed method is able to determine in an efficient way the inspection interval that minimizes the value of the VP with the uncertainties effects. In addition, the proposed technique is very attractive for practical applications, in relation to traditional methods, that is, methods based on the minimization of unavailability with deterministic parameters.