Agba / Sacuto / Au Wireless Communications for Power Substations: RF Characterization and Modeling

1. Auflage 2018
ISBN: 978-3-319-91328-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 203 Seiten

Reihe: Wireless Networks

This book consists of the identification, characterization, and modeling of electromagnetic interferences in substations for the deployment of wireless sensor networks. The authors present in chapter 3 the measurement setup to record sequences of impulsive noise samples in the ISM band of interest. The setup can measure substation impulsive noise, in wide band, with enough samples per time window and enough precision to allow a statistical study of the noise. During the measurement campaign, the authors recorded around 120 noise sequences in different substations and for four ranges of equipment voltage, which are 25 kV, 230 kV, 315 kV and 735 kV. A characterization process is proposed, by which physical characteristics of partial discharge can be measured in terms of first- and second-order statistics. From the measurement campaign, the authors infer the characteristics of substation impulsive noise as a function of the substation equipment voltage, and can provide representative parameters for the four voltage ranges and for several existing impulsive noise models.The authors investigate in chapters 4 and 5 the modeling of electromagnetic interferences caused by partial discharge sources. First, the authors propose a complete and coherent approach model that links physical characteristics of high-voltage installations to the induced radio-interference spectra of partial discharge sources. The goodness-of-fit of the proposed physical model has been measured based on some interesting statistical metrics. This allows one to assess the effectiveness of the authors' approach in terms of first- and second-order statistics. Chapter 6 proposes a model based on statistical approach. Indeed, substation impulsive noise is composed of correlated impulses, which would require models with memory in order to replicate a similar correlation. Among different models, we have configured a Partitioned Markov Chain (PMC) with 19 states (one state for the background noise and 18 states for the impulse); this Markov-Gaussian model is able to generate impulsive noise with correlated impulse samples. The correlation is observable on the impulse duration and the power spectrum of the impulses. Our PMC model provides characteristics that are more similar to the characteristics of substation impulsive noise in comparison with other models, in terms of time and frequency response, as well as Probability Density Functions (PDF). Although PMC represents reliably substation impulsive noise, the model remains complex in terms of parameter estimation due to a large number of Markov states, which can be an obstacle for future wireless system design. In order to simplify the model, the authors decrease the number of states to 7 by assigning one state to the background noise and 6 states to the impulse and we call this model PMC-6. PMC-6 can generate realistic impulses and can be easily implemented in a receiver in order to mitigate substation impulsive noise. Representative parameters are provided in order to replicate substation impulsive noise for different voltage ranges (25-735 kV). Chapter 7, a generalized radio-noise model for substations is proposed, in which there are many discharges sources that are randomly distributed over space and time according to the Poisson field of interferers approach. This allows for the identification of some interesting statistical properties of moments, cumulants and probability distributions. These can, in turn, be utilized in signal processing algorithms for rapid partial discharge's identification, localization, and impulsive noise mitigation techniques in wireless communications in substations.The primary audience for this book is the electrical and power engineering industry, electricity providers and companies who are interested in substation automation systems using wireless communication technologies for smart grid applications. Researchers, engineers and students studying and working in wireless communication will also want to buy this book as a reference.

Autoren/Hrsg.

Agba, Basile L.

Sacuto, Fabien

Au, Minh

Labeau, Fabrice

Gagnon, François

Inhaltsverzeichnis

1;Foreword;7
2;Preface;9
3;Acknowledgments;12
4;About the Authors;13
5;Contents;16
6;1 Introduction;20
6.1;1.1 Motivation;20
6.2;1.2 Monograph Organization;22
6.3;1.3 Contributions;23
7;2 EMI and Wireless Communications in Power Substations;26
7.1;2.1 Introduction;26
7.2;2.2 Concept of EMI and Classification;26
7.2.1;2.2.1 Definition of EMI Sources;27
7.2.2;2.2.2 Natural Noise Sources;27
7.2.3;2.2.3 Man-Made Noise Sources;28
7.3;2.3 Electromagnetic Interference in Substations;28
7.3.1;2.3.1 Functions of Power Substations;28
7.3.2;2.3.2 Pieces of Equipment and Electrical Operations;29
7.3.2.1;2.3.2.1 Corona Effect;30
7.3.2.2;2.3.2.2 Partial Discharges;31
7.3.3;2.3.3 Early Impulsive Noise Measurements;32
7.3.4;2.3.4 Ionization Process and Electrical Discharge in Gases;32
7.3.5;2.3.5 Partial Discharges Mechanism;33
7.3.6;2.3.6 Measurements and Characterization of Partial Discharge Sources;35
7.3.6.1;2.3.6.1 Measurement Techniques;35
7.3.6.2;2.3.6.2 PD Currents Impulses;35
7.3.6.3;2.3.6.3 PD Electromagnetic Radiations;36
7.3.6.4;2.3.6.4 Characterization of PD Impulses;37
7.3.7;2.3.7 Partial Discharge Modeling;37
7.3.7.1;2.3.7.1 Physical PD Models;38
7.3.7.2;2.3.7.2 Statistical PD Models for Wireless Channels;38
7.4;2.4 Characterization and Impulsive Noise Models;40
7.4.1;2.4.1 A Statistical Characterization of Impulsive Noise;40
7.4.2;2.4.2 Impulsive Noise Models;41
7.4.3;2.4.3 Probability Models of Impulsive Noise;42
7.4.3.1;2.4.3.1 Memoryless Models;43
7.4.3.2;2.4.3.2 Impulsive Noise with Memory: Burst Noise;46
7.5;2.5 Wireless Communications in Substations;49
7.5.1;2.5.1 Communication Channels in Presence of Impulsive Noise;49
7.5.2;2.5.2 Wireless Technologies;50
7.5.3;2.5.3 Existing Systems for Wireless Communications in High Voltage Environment;50
7.6;2.6 Summary;52
8;3 Impulsive Noise Measurements;53
8.1;3.1 Objectives of the Measurement Campaign;54
8.2;3.2 Measurement Setup;54
8.2.1;3.2.1 Design of the Setup;55
8.2.2;3.2.2 Tests in Laboratory;56
8.2.3;3.2.3 Impulse Detection Method;58
8.3;3.3 Measurements in Substation 1;61
8.3.1;3.3.1 Substation Presentation;61
8.3.2;3.3.2 Locations of the Antenna;63
8.3.3;3.3.3 Results;64
8.4;3.4 Measurements in Substation 2;65
8.4.1;3.4.1 Substation Presentation;65
8.4.2;3.4.2 Locations of the Antenna;66
8.4.3;3.4.3 Results;66
8.5;3.5 Classification of Impulsive Noise Characteristics;67
8.5.1;3.5.1 Amplitude;67
8.5.2;3.5.2 Impulse Duration;68
8.5.3;3.5.3 Repetition Rate;70
8.5.4;3.5.4 Sample Value;70
8.5.5;3.5.5 Representative Characteristics;71
8.6;3.6 An Experimental Characterization of the Discharge Sources;71
8.6.1;3.6.1 Amplitude of Measured Signals;72
8.6.2;3.6.2 Signal Processing Tools for Impulsive Noise Measurement;72
8.6.2.1;3.6.2.1 The Denoising Process;72
8.6.2.2;3.6.2.2 Short-Time Analysis for Impulsive Signals;73
8.6.2.3;3.6.2.3 Temporal Location of an Impulse;74
8.6.3;3.6.3 Characterization Based on First-Order Statistics;75
8.6.3.1;3.6.3.1 PRPD Representation;76
8.6.3.2;3.6.3.2 Statistical Distribution of PD Characteristics;77
8.6.4;3.6.4 Characterization Based on Second-Order Statistics;77
8.6.4.1;3.6.4.1 Typical Waveform and Spectrogram;79
8.6.4.2;3.6.4.2 Power Spectral Density;81
8.6.4.3;3.6.4.3 Power Spectral Density of an Impulse;81
8.6.4.4;3.6.4.4 Average Power Spectral Density;81
8.7;3.7 Representative Parameters for Classic Impulsive Noise Models;83
8.7.1;3.7.1 Bernoulli-Gaussian Model;83
8.7.2;3.7.2 Middleton Class-A Model;83
8.8;3.8 Conclusion;85
9;4 A Physical Model of EMI Induced by a Partial Discharge Source;87
9.1;4.1 Introduction;87
9.2;4.2 The Partial Discharge Phenomenon;88
9.3;4.3 The Physical Model of Partial Discharge Source;89
9.3.1;4.3.1 Electric Field Stress;89
9.3.2;4.3.2 Discharge Process;91
9.3.3;4.3.3 Current and Charge Density;93
9.4;4.4 The Electromagnetic Radiation of the Interference Source Induced by Partial Discharge;93
9.4.1;4.4.1 Electric Dipole formulation;94
9.4.2;4.4.2 Power Radiation of the Interference Source Received at the Antenna;95
9.4.3;4.4.3 Modeling Impulsive Waveforms and PSD;96
9.4.4;4.4.4 Brief Summary of Interference Induced by DischargeSource;96
9.5;4.5 Experimental Characterization Process of the Interference Source;98
9.5.1;4.5.1 Definition of Characterization Metrics;98
9.5.2;4.5.2 Denoising Process;98
9.5.3;4.5.3 Short-Time Analysis Process;98
9.6;4.6 Experimental Validation;99
9.6.1;4.6.1 Brief Description of Measurement Setup;99
9.6.1.1;4.6.1.1 The Measurement Setup;99
9.6.1.2;4.6.1.2 PD Sources from Stator Bar;99
9.6.2;4.6.2 Simulation Setup;100
9.6.2.1;4.6.2.1 Calculation of the Electric Field Along the Surface;100
9.6.2.2;4.6.2.2 Discharge Process in Air Cavity Parameters;101
9.6.2.3;4.6.2.3 Stochastic Property of the Emitted Radiations of PD Sources;103
9.6.3;4.6.3 Simulation-Measurement Comparison;103
9.6.3.1;4.6.3.1 PRPD Comparison;103
9.6.3.2;4.6.3.2 Statistical Distributions Comparison;104
9.6.3.3;4.6.3.3 PSD and Waveforms of Impulses;107
9.7;4.7 Conclusion;108
10;5 Analysis and Modeling of Wideband RF Signals Induced by PD Using Second-Order Statistics;110
10.1;5.1 Introduction;110
10.1.1;5.1.1 Main Contribution and Organization;111
10.2;5.2 Measurement Setup;112
10.3;5.3 Conjectures and Mathematical Formulation of EM Waves;112
10.3.1;5.3.1 Second-Order Statistics;112
10.3.1.1;5.3.1.1 Time-Frequency Analysis;112
10.3.1.2;5.3.1.2 Autocorrelation Function;113
10.3.1.3;5.3.1.3 Results from the Measurement Campaigns;113
10.3.2;5.3.2 A Physical Interpretation;114
10.4;5.4 The Proposed Model;115
10.4.1;5.4.1 Theory of Filters and Its Relationship with Time Series Models;115
10.4.2;5.4.2 Definition of the Time Series Model;116
10.4.3;5.4.3 Tests for Unit Roots;117
10.4.4;5.4.4 Estimation and Selection;119
10.5;5.5 The Goodness-of-Fit;120
10.5.1;5.5.1 Analysis of the Residuals;120
10.5.1.1;5.5.1.1 Residuals of Fitted ARMA(7,2);121
10.5.1.2;5.5.1.2 Residuals of Fitted ARMA(4,1);122
10.5.2;5.5.2 Tests for Heteroskedasticity;123
10.5.3;5.5.3 Analysis of the Residuals of the Improved Models;125
10.5.4;5.5.4 Summary;129
10.6;5.6 Simulation and Results;130
10.6.1;5.6.1 Simulation Parameters;130
10.6.2;5.6.2 A Comparison of Measurement vs. Simulation Results;130
10.6.3;5.6.3 Analysis of Simulated Impulsive Waveforms;131
10.6.4;5.6.4 Advantages and Limitations of the Proposed Model;132
10.7;5.7 Conclusion;133
11;6 Wideband Statistical Model for Substation Impulsive Noise;136
11.1;6.1 Introduction to PMC Model;136
11.2;6.2 Impulsive System and Oscillations;139
11.3;6.3 Damping Effect;143
11.4;6.4 Transition Matrix;143
11.5;6.5 Parameter Estimation;147
11.5.1;6.5.1 Fuzzy C-Means Algorithm;147
11.6;6.6 Results;149
11.6.1;6.6.1 Divergence Between Measurements and Models;150
11.6.2;6.6.2 Spectrum Analysis;153
11.7;6.7 Representative Parameters for PMC Model in Wide Band;154
11.8;6.8 Conclusions;155
12;7 Impulsive Noise in a Poisson Field of Interferers in Substations;158
12.1;7.1 Introduction;158
12.2;7.2 A Mathematical Formulation of Multiple PD Interference Sources;159
12.2.1;7.2.1 Electromagnetic Radiations of Multiple PD Sources;159
12.2.1.1;7.2.1.1 The Emission of the PD Impulses;159
12.2.1.2;7.2.1.2 Basic Assumptions of Spatial and Temporal PD Events;160
12.2.2;7.2.2 Propagation of EM Waves Induced by PD Sources;160
12.2.2.1;7.2.2.1 The Noise Process Observed by the Receiver;161
12.2.2.2;7.2.2.2 A Generic Temporal Impulsive Waveform from PD;161
12.2.2.3;7.2.2.3 The Attenuation Factor;162
12.2.3;7.2.3 Spatial and Temporal Distribution of PD Sources;162
12.3;7.3 Statistical Analysis;164
12.3.1;7.3.1 Probability Density Function;164
12.3.2;7.3.2 Probability Distribution;168
12.3.3;7.3.3 Tails and Moments;168
12.3.3.1;7.3.3.1 Moments of ?-Stable Distributions;169
12.3.3.2;7.3.3.2 Moments of Shot-Noise Processes;169
12.3.4;7.3.4 A Summary of Important Findings;170
12.4;7.4 Experimental and Simulation Results;171
12.4.1;7.4.1 Measurements in Substations;171
12.4.2;7.4.2 A Procedure for Estimation;172
12.4.3;7.4.3 Measurement-Simulation Comparison;173
12.4.3.1;7.4.3.1 First-Order Statistics;173
12.4.3.2;7.4.3.2 Second-Order Statistics;175
12.5;7.5 A Rapid Identification of PD Sources Using Blind Source Separation;177
12.5.1;7.5.1 Motivation;178
12.5.2;7.5.2 System Model;178
12.5.3;7.5.3 Blind Source Separation via Generalized Eigenvalue Decomposition;180
12.5.4;7.5.4 Simulation and Results;181
12.6;7.6 Conclusion;183
13;8 Conclusions;185
13.1;8.1 Monograph Summary;185
13.2;8.2 On the Practical Use of the EMI Models;188
14;References;191
15;Index;201