UTILIZATION OF SUPPORT VECTOR MACHINE FOR FAULT DETECTION AND CLASSIFICATION IN POWER TRANSMISSION LINE SYSTEMS

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A Thesis

Submitted to the Faculty of Western Michigan University in partial fulfillment of the requirements for the Degree of [name of degree here]

[Name of department or unit here]

Advisor: [First and Last Name, Ph.D. or Ed.D. here]

Western Michigan University

Kalamazoo, Michigan

[Month and year of graduation, no comma separating]UTILIZATION OF SUPPORT VECTOR MACHINE FOR FAULT DETECTION AND CLASSIFICATION IN POWER TRANSMISSION LINE SYSTEMS

Western Michigan University, [year of graduation]

ABSTRACT

Electrical transmission lines are prone to faults and failures. When a fault occurs, it is impossible most of the times to fix it manually. Many methods have been adopted in the past in order to serve the purpose as fault diagnosing application. These methods mainly include; expert system, fuzzy theory, Artificial Neural Network, and Support Vector Machine (SVM). This thesis discusses the method Support Vector Machine for fault diagnosis. SVM has the edge of good generalization over other fault diagnosing applications because it is based on the principle of risk minimization principle. Due to this ability, SVM application has been widely used in fault diagnosis and classification in recent times. This thesis studies the utilization of support vector machine as tool for fault detection and classification in power transmission line systems. The aim is to identify the type of fault in the lines and to determine which segment of the line has experienced a fault. Furthermore, in this work, the current and voltage of each phase are sampled, calculated and then utilized as an optimal learning pattern. Using this method, experimental simulations will show that SVM can classify each class more accurately in comparison to previously used methods such as; Expert System, Artificial Neural Network, Petri Net, Fuzzy Theory. The results of simulation tests demonstrate the effectiveness of the proposed automatic fault diagnosis method.

ACKNOWLEDGMENT

I would like to take this chance for thanking my research facilitator, friends & family for support they provided and their belief in me as well as guidance they provided without which, I would have never been able to do this research.

DECLARATION

I, (type your full first names and surname here), would like to declare that the Project Description in the deliverable form is all my individual work without any aid and that this thesis has not been submitted for any examination at academic as well as professional level previously. I have acknowledged all quotations from the published or unpublished works of other people. It is also representing my very own views and not essentially which are associated with university.

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TABLE OF CONTENTS

ACKNOWLEDGMENTiii

DECLARATIONiv

LIST OF FIGURESviii

LIST OF TABLESix

CHAPTER 2: METHODOLOGY1

2.1 Research Design1

2.2 Plan of Work1

2.3 Research Method2

2.4 Data Analysis Method3

2.5 Secondary Data3

2.6 Qualitative Research4

2.7 Assumptions of Qualitative Research4

2.8 Literature Search5

2.9 Validity5

2.10 Time Scale6

2.11 Gantt chart for the Work Plan7

CHAPTER 3: PROTECTION OF POWER TRANSMISSION LINE SYSTEMS8

3.1 Power System Faults8

3.2 Background to Fault Diagnosis Technologies9

3.3 Fault Diagnosis Applications12

3.3.1 Expert System12

3.3.2 Fuzzy Theory14

3.3.3 Artificial Neural Network16

3.3.4 Wavelet Approach18

3.3.5 Support Vector Machine21

3.4 Protection Systems25

3.5 Classification of ...