A Fault Detection and Protection Scheme for a 200 MVA Transformer using Fuzzy Logic

ABSTRACT

Condition monitoring of Electrical power equipment has attracted considerable attention for years. The aim of this work is to use Fuzzy logic (FL) Tool Box in building a simulation system that will diagnose all kinds of incipient faults, phase to phase fault and overloading in a transformer and monitor its conditions. Current and rate of change of current with time have been identified as the input variables, duly represented in the programme as “Error” and “Error-Dot”. These variables have their universe of discourse from -1.5 to 1.5 and from -10 to 10 respectively. Fuzzy logic sensor is designed to monitor the current(i) conditions of the transformer at both ambient and full load. The results from the research show that whenever the output response is zero the current in transformer is normal. This is obtained when input values of [0] and [0] are injected into the system to produce a response of “6e-017” which is approximately zero. Whereas if the output response is greater than zero it implies that the transformer current is rising beyond normal and protection scheme should be alerted. This condition is achieved when input values of [-1.5] and [5] are used on the system to give a response of “+5”. However, if the response is less than zero then the transformer current is below normal, hence the protection scheme should be alerted. To investigate this, input values of [1.5] and [-5] give a response of “-5”. Fuzzy logic is used as an expert system that assesses all information keyed in at the front panel to analyze and predict the condition of the transformer at any time.

TABLE OF CONTENTS

Approval Page ----------------------------------------------------------------------------------------------- i

Dedication----------------------------------------------------------------------------------------------------- ii

Acknowledgement ------------------------------------------------------------------------------------------- iii

Abstract ------------------------------------------------------------------------------------------------------- iv

Table of Contents -------------------------------------------------------------------------------------------- v

List of Tables ------------------------------------------------------------------------------------------------ vii

List of Figures ----------------------------------------------------------------------------------------------- viii

List of Symbols ---------------------------------------------------------------------------------------------- ix

CHAPTER ONE: INTRODUCTION

1.1 Background of the Study------------------------------------------------------------------------------- 3

1.2 Statement of the Problem ------------------------------------------------------------------------------ 4

1.3 Objective of the Study --------------------------------------------------------------------------------- 4

1.4 Significance of the Study ------------------------------------------------------------------------------ 4

1.5 Scope of the Study ------------------------------------------------------------------------------------- 5

CHAPTER TWO: LITERATURE REVIEW

2.1.0 The Transformer -------------------------------------------------------------------------------------- 6

2.1.1 Information on name plate of the three phase Double wound transformer ------------------------------- 8

2.1.2 Transformer losses ------------------------------------------------------------------------------------ 9

2.1.3 Test on Transformer----------------------------------------------------------------------------------- 12

2.1.4 Faults in Transformer -------------------------------------------------------------------------------- 14

2.1.5 Constructional features to reduce faults and increase Efficiency --------------------------------- 16

2.1.6 Conventional fault detection and protection scheme ---------------------------------------------- 18

2.2.0 Fuzzy Logic -------------------------------------------------------------------------------------------- 24

2.2.1 Fuzzy sets----------------------------------------------------------------------------------------------- 29

2.2.2 Membership function --------------------------------------------------------------------------------- 30

2.2.3 Rule base ----------------------------------------------------------------------------------------------- 31

2.2.4 Inference------------------------------------------------------------------------------------------------ 32

2.2.5 De-fuzzification --------------------------------------------------------------------------------------- 32

CHAPTER THREE: METHODOLOGY

3.1 Identification of input and output variables----------------------------------------------------------- 38

3.2 Construction of control rules --------------------------------------------------------------------------- 39

3.3 Rules ------------------------------------------------------------------------------------------------------ 39

3.4 Membership functions ---------------------------------------------------------------------------------- 41

3.5 Fuzzification --------------------------------------------------------------------------------------------- 44

3.6 Selection of compositional Rule of Inference -------------------------------------------------------- 46

CHAPTER FOUR: SIMULATION AND RESULTS

4.1 Simulation software used ------------------------------------------------------------------------------ 49

4.2 Fuzzification---------------------------------------------------------------------------------------------- 50

4.3 Rule number determination----------------------------------------------------------------------------- 51

4.4 Rules ------------------------------------------------------------------------------------------------------ 54

4.5 Inference Engine ----------------------------------------------------------------------------------------- 54

4.6 Rule firing ------------------------------------------------------------------------------------------------ 54

4.7 Defuzzification------------------------------------------------------------------------------------------- 55

4.8 Result analysis ------------------------------------------------------------------------------------------- 61

CHAPTER FIVE: CONCLUSION

5.1 Summary-------------------------------------------------------------------------------------------------- 63

5.2 Conclusion------------------------------------------------------------------------------------------------ 64

5.3 Contribution to knowledge ----------------------------------------------------------------------------- 65

REFERENCES --------------------------------------------------------------------------------------------- 66

Appendix A: Input I (Error)--------------------------------------------------------------------------------- 68

Appendix B: Input II (Del-error) --------------------------------------------------------------------------- 69

Appendix C: Output I---------------------------------------------------------------------------------------- 70

Appendix D: Rules Structure ------------------------------------------------------------------------------- 71