CLASSIFICATION OF RELIABILITY OF ELECTRIC POWER DISTRIBUTION SYSTEMS AT PT. PLN (PERSERO) UP3 SOUTH SURABAYA USING THE SINGLE PERCEPTRON METHOD

Giovanni Dimas Prenata

Abstract

The reliability of the electricity distribution system is very important for PLN. With a high level of reliability, PLN can ensure that electrical energy is distributed properly to customers. A high level of reliability is a guarantee for customers to get electrical energy. Some researchers measure reliability using the SAIDI (System Average Interruption Duration Index) and SAIFI (System Average Interruption Frequency Index) values. Apart from that, there are also those who use the FMEA (Failure Modes and Effects Analysis) method. In this study, researchers carried out reliability classification based on the SPLN 59-1985 standard using the artificial neuron network single perceptron method. Researchers used 3 neurons as input, namely the SAIDI value, SAIFI value and bias. The training data used is SAIDI value data and SAIFI value data for 10 months in 2021. The single perceptron neuron network application was created using C++ language with a learning rate of 0.1, and a sigmoid signal as the activation. So the weighting values obtained for 3 neurons, namely -3.95772 (W[0]), 1.15408 (W[1]) and 1.45799 (W[2]) in 6 training times to classify the level of reliability.

Keywords

SAIDI, SAIFI dan artificial neuron network single perceptron.

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References

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DOI: https://doi.org/10.1593/jreec.v3i2.5091
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