POWER QUALITY MEASUREMENT AND ANALYSIS USING HIGHER-ORDER STATISTICS 1 -- Understanding HOS contribution on the Smart(er) Grid 1 -- POWER QUALITY MEASUREMENT AND ANALYSIS USING HIGHER-ORDER STATISTICS 3 -- Understanding HOS contribution on the Smart(er) Grid 3 -- LOGO 3 -- Contents 11 -- Contributors 14 -- Foreword 17 -- Acronyms 21 -- Acknowledgments 24 -- Chapter 1. Power quality monitoring and higher-order statistics. State of the Art 26 -- 1.1 Introduction 27 -- 1.2 Background on power quality 27 -- 1.3 PQ Practices at the Industrial Level 33 -- 1.4 A new PQ monitoring Framework 33 -- 1.4.1 The Smart Grid 35 -- 1.4.2 The Smart Grid and the Power Quality 35 -- 1.4.3 Performance Indicators 36 -- 1.4.4 Existing measurement and instrumentation solutions 37 -- 1.4.5 New approach in Measurement and Instrumentation solutions in the SG 38 -- 1.4.6 Economic Issues for PQ 39 -- 1.4.7 Power Quality and Big Data 39 -- 1.4.8 Signal Processing for PQ 40 -- 1.4.9 HOS for PQ analysis 43 -- Chapter 2. HOS Measurements in the time domain 47 -- HOS Measurements in the time domain 48 -- 2.1 Introduction 48 -- 2.2 Background on power quality 48 -- 2.3 Traditional theories of electrical time domain 49 -- 2.4 HOS contribution in the PQ field 51 -- 2.4.1 HOS indices definitions 51 -- 2.4.2 HOS performance in signal processing 52 -- 2.4.3 HOS versus electrical time domain indices 53 -- 2.5 Regulations 55 -- 2.6 The Sliding Window Method for HOS feature extraction 56 -- 2.6.1 Amplitude Changes 57 -- 2.6.2 Phase Angle Jumps 58 -- 2.6.3 Fundamental Frequency 60 -- 2.6.4 Waveform shape deviation 62 -- 2.7 PQ index based on HOS 64 -- 2.8 Representations used by the time-domain 67 -- Chapter 3. Event Detection Strategies based on HOS feature extraction 72 -- 3.1 Introduction 73 -- 3.2 Detection methods based in HOS 73 -- 3.3 Experiment description 73 -- 3.3.1 Computational Strategy 73 -- 3.3.2 HOS for Sag Detection under Symmetrical and Sinusoidal Conditions 74 -- 3.3.2 HOS for Sag Detection including Phase-Angle Jump based on Non-Symmetrical & Non-Sinusoidal conditions 75 -- 3.3.2.1 HOS range for Transient detection including Phase-Angle Jump based on Non-Symmetrical & Non- Sinusoidal conditions 87 -- 3.3 Flow Diagram of HOS monitoring strategy focus on detecting short duration events: detecting amplitude, symmetry, and sinusoidal states 87 -- 3.4 Continuous event's characterization fundamental frequency 90 -- 3.4.1 Frequency deviation regions in the HOS planes 92 -- 3.4.2 Frequency deviation regions in the HOS planes 94 -- 3.5 Detection of Harmonics with HOS in the time domain 95 -- 3.6 Conclusions 97 -- Chapter 4. Measurements in the Frequency domain 100 -- 4.1 Introduction 101 -- 4.2 Frequency-domain 101 -- 4.3 HOS in Frequency-domain 102 -- 4.3.1 Spectral Kurtosis in Power Quality 103 -- 4.4 Harmonic distortion 103 -- 4.4.1 Types of Harmonic distortion 104 -- 4.4.2 Sources of Harmonic distortion 105 -- 4.4.3 Impact of harmonic distortion over power system 105 -- 4.5 Traditional theories of electrical frequency-domain indicators 105 -- 4.5.1 Harmonic measure 105 -- 4.5.2 DFT derived measures 107 -- 4.6 HOS contribution in PQ in the frequency-domain 107 -- 4.6.1 Spectral Kurtosis 108 -- 4.6.2 Spectral Kurtosis basic usage 115 -- 4.6.3 Spectral Kurtosis and Power quality 118 -- Chapter 5 Measurement Campaigns and Virtual Instruments 124 -- 5.1 Introduction 125 -- 5.2 Virtual Instrument 126 -- 5.2.1 Measurement Analysis Framework 126 -- 5.2.2 Experimental Strategy for PQM through a Virtual Instrument 128 -- 5.2.3 Configuration of the Virtual Instrument 128 -- 5.2.4 Results 131 -- 5.3 PQ continuous monitoring based on HOS for consumers characterization, public networks and household 132 -- 5.3.1 Measurement and Analysis Framework 132 -- 5.3.2 Evolution of the individual statistics histograms during several weeks 133 -- References 149 -- Annex A. Voltage Waveform 1 -- Theoretical power system waveform 1 -- Annex. B. Time-domain cumulants 1 -- Annex. C. HOS Range for Sag Detection, one cycle 3 -- Annex. D. HOS Range for Sag Detection, 10 cycles 7.