Electrical and Mechanical Fault Diagnosis in Wind Energy Conversion Systems

Monia Ben Khader Bouzid is Associate Professor at École Nationale d'Ingénieurs de Carthage and a researcher at the Laboratoire des Systèmes Electriques, ENIT, Tunisia. Her research interests focus on modeling and fault diagnosis of electrical machines and renewable energy systems. Gérard Champenois is Emeritus Professor at the University of Poitiers and a researcher at the Laboratoire d'Automatique et d'Informatique pour les Systèmes, France. His research interests focus on electrical machines and renewable energies with multi-source systems; control, modeling and diagnosis.

Introduction ix
Monia BEN KHADER BOUZID and Gérard CHAMPENOIS

Chapter 1 Accurate Electrical Fault Detection in the Permanent Magnet Synchronous Generator and in the Diode Bridge Rectifier of a Wind Energy Conversion System 1
Monia BEN KHADER BOUZID and Gérard CHAMPENOIS

1.1 Introduction 1

1.2 Description of the system under study and the used fault detection method 2

1.3 Fundamental notions of the symmetrical components 5

1.4 Development of the analytical expressions of the NSV in the case of the different considered faults 7

1.4.1 Analytical expression of 2 V in the case of simultaneous faults 7

1.4.2 Analytical expression of 2 V in the case of ITSCF in the PMSG 12

1.4.3 Analytical expression of 2 V in the case of OCDF in the rectifier 14

1.5 Analytical study of the indicators of the different faults 15

1.5.1 Analytical study in the case of ITSCF 16

1.5.2 Analytical study in the case of OCDF in the rectifier 19

1.5.3 Analytical study in the case of SF 24

1.6 Experimental validation of the proposed fault indicators 25

1.6.1 Description of the tests process 25

1.6.2 Experimental results in the case of healthy operation 26

1.6.3 Experimental results in the case of ITSCF in the PMSG 27

1.6.4 Experimental results in the case of an OCDF fault in the rectifier 29

1.6.5 Experimental results in the case of SF in the system considered 31

1.7 Description of the method proposed 32

1.8 Conclusion 37

1.9 References 37

Chapter 2 Control and Diagnosis of Faults in Multiphase Permanent Magnet Synchronous Generators for High-Power Wind Turbines 39
Sérgio CRUZ and Pedro GONÇALVES

2.1 Introduction 39

2.2 Wind energy conversion systems 40

2.3 Multiphase electric drives on WECS 41

2.4 Model of a six-phase PMSG drive 43

2.4.1 Natural reference frame 44

2.4.2 Synchronous reference frame 48

2.5 Control strategies 51

2.5.1 Introduction 51

2.5.2 Field-oriented control 51

2.5.3 Direct torque control 52

2.5.4 Finite control set model predictive control 54

2.6 Fault diagnosis in multiphase drives 71

2.6.1 Introduction 71

2.6.2 Interturn short-circuit faults 73

2.6.3 High-resistance connections and open-phase faults 76

2.6.4 Permanent magnet faults 78

2.6.5 Current sensor faults 79

2.6.6 Speed sensor faults 80

2.7 Conclusion 81

2.8 References 82

Chapter 3 Gearbox Fault Monitoring Using Induction Machine Electrical Signals 89
Khmais BACHA and Walid TOUTI

3.1 Introduction 89

3.2 Motor stator current signature approach 90

3.2.1 Air gap magnetic flux density-based approach 90

3.2.2 Magnetizing current approach 97

3.3 Wound rotor current signature approach 99

3.4 Experimental results 101

3.4.1 MCSA for geared motor fault diagnosis 101

3.4.2 MCSA for WT gearbox 103

3.4.3 WT generator current processing 104

3.4.4 Current transformations for geared motor fault diagnosis 106

3.5 Conclusion 116

3.6 Acknowledgments 116

3.7 References 117

Chapter 4 Control of a Wind Distributed Generator for Auxiliary Services Under Grid Faults 119
Youssef KRAIEM and Dhaker ABBES

4.1 Introduction 119

4.2 Description of the renewable distributed generator 123

4.3 Control of the distributed generator 124

4.3.1 Control of the wind generator 124

4.3.2 Control of the hybrid storage system 128

4.3.3 Control of the DC bus voltage 130

4.4 Power management algorithm 132

4.4.1 Specifications 132

4.4.2 Determination of inputs/outputs 133

4.4.3 Determination of membership functions 133

4.4.4 Inference engine for energy management 136

4.5 Detection and control of the grid faults 138

4.5.1 Fuzzy logic islanding detection 141

4.5.2 Fuzzy droop control technique for the adjustment of the grid frequency and voltage 144

4.6 Simulation results 146

4.6.1 Control and power management of the distributed generator 147

4.6.2 Detection and correction of the grid voltage and frequency variations at the PCC 150

4.7 Conclusion 154

4.8 References 154

Chapter 5 Fault-Tolerant Control of Sensors and Actuators Applied to Wind Energy Systems 159
Elkhatib KAMAL and Abdel AITOUCHE

5.1 Introduction 159

5.2 Objective 161

5.3 RFFTC of WES with DFIG 163

5.3.1 TS fuzzy model with parameter uncertainties and fuzzy observer 164

5.3.2 Proposed RFFTC based on FPIEO and FDOS 167

5.3.3 Proposed RFFTC stability and robustness analysis 170

5.3.4 WES with DFIG application 171

5.3.5 Simulations and results 174

5.4 RFSFTC of WES with DFIG subject to sensor and actuator faults 178

5.4.1 TS fuzzy plant model with actuator faults, sensor faults and parameter uncertainties 179

5.4.2 Proposed RFSFTC algorithm based on FPIEO and FDOS 180

5.4.3 Derivation of the stability and robustness conditions 181

5.4.4 WES with DFIG application and simulations and results 183

5.5 RDFFTC of hybrid wind-diesel storage system subject to actuator and sensor faults 186

5.5.1 Fuzzy observer scheme for the uncertain system with sensor and actuator faults 187

5.5.2 Proposed RDFFTC, reference model and stability analysis 188

5.5.3 HWDSS application and simulations and results 191

5.6 Conclusion 197

5.7 References 198

List of Authors 203

Index 205