الفهرس 
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Abstract
In this research, two generator protection functions are discussed and treated using the Adaptive Neuro Fuzzy Inference System (ANFIS). These protection functions are the Loss of Excitation function Relay and the phase backup protection function Relay The Loss of Excitation function is chosen as it is found that the performance of the conventional impedance relays and most of the recently suggested schemes for Loss of Excitation protection are depending on the generator loading conditions and the generator percentage Loss of Excitation values. In addition, the fault detection time for these schemes is found to be long. Also, many Loss of Excitation conditions are not detected by the conventional relays. On the other hand, the phase backup function Relay is chosen as some researchers have confirmed the existence of a problem due to the current setting of the Relay.This problem arises when it is set according to the present standards for generator thermal backup protection against system phase faults and a sudden application of large system loads. The problem is that the current setting of the Relay ( ) for generator thermal backup protection restricts the over excitation thermal capability of the generator.
In this research, the Adaptive Neuro Fuzzy Inference System (ANFIS) is utilized to these generator protection functions. The ANFIS suggests superior solutions and enhances the performance of both generator protection functions.
The proposed Loss of Excitation ANFIS based relay for hydro generators protection is professional. It has a promising performance through detecting all Loss of Excitation conditions in a very short time regardless the generator loading conditions and the generator percentage Loss of Excitation values. Moreover, the proposed phase backup ANFIS based relay is found to be secure for the generator thermal backup protection. It suggests a solution for the problem due to the current setting of the Relay ( ). In addition, this proposed relay has the capability of locating the system phase faults in order to minimize the outage time. In this research work, four different types of inputs are tested and used with the ANFIS for the two protection functions. These inputs are: the generator terminal impedance measurements (R and X), the generator terminal voltages and stator currents (V and I), the positive sequence components (magnitudes and angles) and the third harmonic components. More discussion for the obtained results is given in this research work.
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List of Publications
This Thesis is based on the work reported in the following papers:
Loss of Excitation Protection Study Publications:
M. S. Abdel Aziz, M. Elsamahy, M. A. Moustafa Hassan, Fahmy M. A. Bandary, “A Novel Study for Hydro-Generators Loss of Excitation Faults Detection Using ANFIS”, International Journal of Modelling and Simulation, Vol. , No. , pp. - , .
M.S. Abdel Aziz, M. Elsamahy, M. A. Moustafa Hassan, Fahmy M. A. Bandary, “Loss of Excitation Faults Detection in Hydro-Generators Using an Adaptive Neuro Fuzzy Inference System”, Indonesian Journal of Electrical Engineering and Computer Science, Vol. , No. , pp. - , February .
M. S. Abdel Aziz, M. Elsamahy, M. A. Moustafa Hassan, Fahmy M. A. Bandary, “Applications of ANFIS in Loss of Excitation Faults Detection in Hydro-Generators”, International Journal of System Dynamics Applications (IJSDA), Vol. , No. , pp - , .
M. S. Abdel Aziz, M. Elsamahy, M. A. Moustafa Hassan, Fahmy M. A. Bandary, “Loss of Excitation Detection in Hydro-Generators Based on ANFIS Approach Using Positive Sequence Components”, the XIX IEEE International Conference on Soft Computing and Measurements SCM’ , St. Petersburg, Russia, pp. - . IEEE, - May, .
M. S. Abdel Aziz, M. Elsamahy, M. A. Moustafa Hassan, Fahmy M. A. Bandary, “Detecting the Loss of Excitation in Hydro Generators Using a Neuro-Fuzzy Technique”, The Annals of “Dunarea De Jos” University of Galati, Vol. , No. , pp. - , .
Phase Backup Protection Study Publications:
M. S. Abdel Aziz, M. Elsamahy, M. A. Moustafa Hassan, Fahmy M. A. Bandary, “Enhancement of Turbo-Generators Phase Backup Protection Using Adaptive Neuro Fuzzy Inference System”, International Journal of System Dynamics Applications (IJSDA), Vol. , No. , pp - ,. M.S. Abdel Aziz, M. Elsamahy, M. A. Moustafa Hassan, Fahmy M. A. Bandary, “A Secure ANFIS based Relay for Turbo-Generators Phase Backup Protection”, Indonesian Journal of Electrical Engineering and Computer Science, Vol. , No. , pp.