Prediction of Voltage Dip Frequency in Turkish Energy Transmission Lines Based on Artificial Neural Networks

International Journal of Electrical and Electronics Engineering
© 2015 by SSRG - IJEEE Journal
Volume 2 Issue 2
Year of Publication : 2015
Authors : Mehlika Sengul, Elif Inan, Bora Alboyaci
How to Cite?

Mehlika Sengul, Elif Inan, Bora Alboyaci, "Prediction of Voltage Dip Frequency in Turkish Energy Transmission Lines Based on Artificial Neural Networks," SSRG International Journal of Electrical and Electronics Engineering, vol. 2,  no. 2, pp. 6-12, 2015. Crossref,


Increasing usage of sensitive loads in industry due to rapid growth of power electronic equipment, give rise to focusing on power quality (PQ) phenomena. Voltage sag (voltage dip) is one of the most important PQ problems that utilities and customers are faced. Voltage dips may cause disoperation at sensitive loads of the power utility which could result not only loss of process but also economical damages, especially in paper, ironsteel and rubber industries. Therefore; elimination or reduction of this problem is significant. This paper presents a new approach for predicting the voltage dip frequency due to line fault of per km per month for rehabilitation of Turkish Transmission System. A neural network with feed forward structure has chosen as the prediction method and monitored data sets belonging to Turkish 380 kV voltage level transmission system have been used. It was seen that the approach can predict voltage dip frequency per km per month accurately.


  Artificial neural networks, pattern recognition, power quality, transmission lines.


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