IEEE 14-Baralı Güç Sisteminde Gerilim Kararlılığının Uç Öğrenme Makinesi İle Analizi
Gazi Üniversitesi Fen Bilimleri Dergisi
In this study, the voltage stability of the IEEE 14-bus power system has been investigated under the different load conditions with the help of the line stability index values by using extreme learning machine (ELM) algorithms. For this purpose, IEEE 14-bus power system model is built in Matlab environment. The load flow analysis of the model is performed by using Newton-Raphson method. Figure A. IEEE 14-Bus System Purpose: The voltage stability indices in IEEE 14-bus power system are estimated
... ystem are estimated using ELM. With the help of the superior properties of ELM, it is aimed to predict the voltage faults in the system. Theory and Methods: The parameters related to IEEE 14-bus system are obtained for load flow analysis. With the help of these values, the line stability index is calculated. Then, comparison is made using different activation functions. Results: From the obtained regression and estimation curves, it is observed that ELM is predicted the line stability index value with high accuracy. Conclusion: In this study, ELM is presented for stability analysis of IEEE 14-bus power system. To test the validity of the proposed method, simulation studies are realized using different activation functions. According to the realized studies, it has been shown that ELM has very successful results in determination of voltage stability.