Reliability Evaluation of 220 kV Substation Using Fault Tree Method and Its Prediction Using Neural Networks

J. Abdul Jaleel; M. Fathima Sadina

doi:10.15866/irena.v1i3.6637

Reliability Evaluation of 220 kV Substation Using Fault Tree Method and Its Prediction Using Neural Networks

J. Abdul Jaleel^(1*), M. Fathima Sadina⁽²⁾

^(*) Corresponding author

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Abstract

An electric power system is a network of electrical components used to supply, transmit and distribute electric power. It is an interconnected and complex system. It consist of many components like buses, substations, transformers, generators etc. The main function of the power system is to provide energy to the customers adequately and efficiently. In the normal situation, the power system is demanded to be highly efficient and safe. If any part within the system has failed, the amount of delivered power can be affected and huge economic losses can be induced. Consequently, reliability evaluation of the power system is of significant importance. Here reliability evaluation is done using fault tree method and it is done for 220 kV Kerala Power System. The numerical probability of failure is found from Open FTA software. Single line diagram of the 220 kV substation in Kerala is simulated using ETAP software. Reliability indices are determined using this software. Reliability prediction is done using neural networks. Neural lab is used for the reliability prediction
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Keywords

ETAP; Fault Tree; Neural Networks; OpenFTA; Reliability

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