Math H.J. Bollen grew up in Geulle, The Netherlands, and received the PhD degree in 1989. Currently, he is manager of EMC and Power Quality at STRI, Ludvika, Sweden, and a guest professor at Luleå University of Technology. Math is known for his contributions to power quality analysis through numerous papers, working-group activities, and an earlier textbook, Understanding Power Quality Problems: Voltage Sags and Interruptions, (Wiley-IEEE Press). In 2005, he became an IEEE Fellow for his contributions to methods for reliability and power quality analysis. Irene Y.H. Gu grew up in Shanghai, China. She moved to The Netherlands in 1988 and received the PhD degree in 1992. Since 1996 she has been with the Department of Signals and Systems, Chalmers University of Technology (Gothenburg, Sweden) and has been a professor in signal processing there since 2004. She is also a guest professor at Shanghai Jiao Tong University (China). Irene Gu and Math Bollen were married in Eindhoven in 1992.

"This book provides an excellent description of power quality issues and the methods used to measure these signals. It is an excellent resources for learning about the latest signal processing methods used for power quality monitoring as well as power quality in general." (IEEE Electrical Insulation Magazine, January/February 2008)

• PREFACE. ACKNOWLEDGMENTS.1 INTRODUCTION.1.1 Modern View of Power Systems.1.2 Power Quality.1.3 Signal Processing and Power Quality.1.4 Electromagnetic Compatibility Standards.1.5 Overview of Power Quality Standards.1.6 Compatibility Between Equipment and Supply.1.7 Distributed Generation.1.8 Conclusions.1.9 About This Book.2 ORIGIN OF POWER QUALITY VARIATIONS.2.1 Voltage Frequency Variations.2.2 Voltage Magnitude Variations.2.3 Voltage Unbalance.2.4 Voltage Fluctuations and Light Flicker.2.5 Waveform Distortion. 2.6 Summary and Conclusions.3 PROCESSING OF STATIONARY SIGNALS.3.1 Overview of Methods.3.2 Parameters That Characterize Variations.3.3 Power Quality Indices.3.4 Frequency-Domain Analysis and Signal Transformation.3.5 Estimation of Harmonics and Interharmonics.3.6 Estimation of Broadband Spectrum.3.7 Summary and Conclusions. 3.8 Further Reading.4 PROCESSING OF NONSTATIONARY SIGNALS.4.1 Overview of Some Nonstationary Power Quality Data Analysis  Methods.4.2 Discrete STFT for Analyzing Time-Evolving Signal Components.4.3 Discrete Wavelet Transforms for Time–Scale Analysis of Disturbances.4.4 Block-Based Modeling.4.5 Models Directly Applicable to Nonstationary Data.4.6 Summary and Conclusion.4.7 Further Reading.5 STATISTICS OF VARIATIONS.5.1 From Features to System Indices.5.2 Time Aggregation.5.3 Characteristics Versus Time.5.4 Site Indices. 5.5 System Indices.5.6 Power Quality Objectives.5.7 Summary and Conclusions.6 ORIGIN OF POWER QUALITY EVENTS.6.1 Interruptions.6.2 Voltage Dips. 6.3 Transients.6.4 Summary and Conclusions. 7 TRIGGERING AND SEGMENTATION.7.1 Overview of Existing Methods.7.2 Basic Concepts of Triggering and Segmentation. 7.3 Triggering Methods.7.4 Segmentation. 7.5 Summary and Conclusions.8 CHARACTERIZATION OF POWER QUALITY EVENTS.8.1 Voltage Magnitude Versus Time.8.2 Phase Angle Versus Time. 8.3 Three-Phase Characteristics Versus Time.8.4 Distortion During Event.8.5 Single-Event Indices: Interruptions.8.6 Single-Event Indices: Voltage Dips.8.7 Single-Event Indices: Voltage Swells. 8.8 Single-Event Indices Based on Three-Phase Characteristics.8.9 Additional Information from Dips and Interruptions.8.10 Transients.8.11 Summary and Conclusions.9 EVENT CLASSIFICATION.9.1 Overview of Machine Data Learning Methods for Event Classification.9.2 Typical Steps Used in Classification System.9.3 Learning Machines Using Linear Discriminants.9.4 Learning and Classification Using Probability Distributions.9.5 Learning and Classification Using Artificial Neural Networks. 9.6 Learning and Classification Using Support Vector Machines.9.7 Rule-Based Expert Systems for Classification of Power System Events.9.8 Summary and Conclusions. 10 EVENT STATISTICS.10.1 Interruptions.10.2 Voltage Dips: Site Indices.10.3 Voltage Dips: Time Aggregation.10.4 Voltage Dips: System Indices.10.5 Summary and Conclusions. 11 CONCLUSIONS.11.1 Events and Variations.11.2 Power Quality Variations.11.3 Power Quality Events.11.4 Itemization of Power Quality.11.5 Signal-Processing Needs.APPENDIX A IEC STANDARDS ON POWER QUALITY.APPENDIX B IEEE STANDARDS ON POWER QUALITY.BIBLIOGRAPHY.INDEX.

Math H.J. Bollen grew up in Geulle, The Netherlands, and received the PhD degree in 1989. Currently, he is manager of EMC and Power Quality at STRI, Ludvika, Sweden, and a guest professor at Luleå University of Technology. Math is known for his contributions to power quality analysis through numerous papers, working-group activities, and an earlier textbook, Understanding Power Quality Problems: Voltage Sags and Interruptions, (Wiley-IEEE Press). In 2005, he became an IEEE Fellow for his contributions to methods for reliability and power quality analysis. Irene Y.H. Gu grew up in Shanghai, China. She moved to The Netherlands in 1988 and received the PhD degree in 1992. Since 1996 she has been with the Department of Signals and Systems, Chalmers University of Technology (Gothenburg, Sweden) and has been a professor in signal processing there since 2004. She is also a guest professor at Shanghai Jiao Tong University (China). Irene Gu and Math Bollen were married in Eindhoven in 1992.

"This book provides an excellent description of power quality issues and the methods used to measure these signals. It is an excellent resources for learning about the latest signal processing methods used for power quality monitoring as well as power quality in general." (IEEE Electrical Insulation Magazine, January/February 2008)

• PREFACE. ACKNOWLEDGMENTS.1 INTRODUCTION.1.1 Modern View of Power Systems.1.2 Power Quality.1.3 Signal Processing and Power Quality.1.4 Electromagnetic Compatibility Standards.1.5 Overview of Power Quality Standards.1.6 Compatibility Between Equipment and Supply.1.7 Distributed Generation.1.8 Conclusions.1.9 About This Book.2 ORIGIN OF POWER QUALITY VARIATIONS.2.1 Voltage Frequency Variations.2.2 Voltage Magnitude Variations.2.3 Voltage Unbalance.2.4 Voltage Fluctuations and Light Flicker.2.5 Waveform Distortion. 2.6 Summary and Conclusions.3 PROCESSING OF STATIONARY SIGNALS.3.1 Overview of Methods.3.2 Parameters That Characterize Variations.3.3 Power Quality Indices.3.4 Frequency-Domain Analysis and Signal Transformation.3.5 Estimation of Harmonics and Interharmonics.3.6 Estimation of Broadband Spectrum.3.7 Summary and Conclusions. 3.8 Further Reading.4 PROCESSING OF NONSTATIONARY SIGNALS.4.1 Overview of Some Nonstationary Power Quality Data Analysis  Methods.4.2 Discrete STFT for Analyzing Time-Evolving Signal Components.4.3 Discrete Wavelet Transforms for Time–Scale Analysis of Disturbances.4.4 Block-Based Modeling.4.5 Models Directly Applicable to Nonstationary Data.4.6 Summary and Conclusion.4.7 Further Reading.5 STATISTICS OF VARIATIONS.5.1 From Features to System Indices.5.2 Time Aggregation.5.3 Characteristics Versus Time.5.4 Site Indices. 5.5 System Indices.5.6 Power Quality Objectives.5.7 Summary and Conclusions.6 ORIGIN OF POWER QUALITY EVENTS.6.1 Interruptions.6.2 Voltage Dips. 6.3 Transients.6.4 Summary and Conclusions. 7 TRIGGERING AND SEGMENTATION.7.1 Overview of Existing Methods.7.2 Basic Concepts of Triggering and Segmentation. 7.3 Triggering Methods.7.4 Segmentation. 7.5 Summary and Conclusions.8 CHARACTERIZATION OF POWER QUALITY EVENTS.8.1 Voltage Magnitude Versus Time.8.2 Phase Angle Versus Time. 8.3 Three-Phase Characteristics Versus Time.8.4 Distortion During Event.8.5 Single-Event Indices: Interruptions.8.6 Single-Event Indices: Voltage Dips.8.7 Single-Event Indices: Voltage Swells. 8.8 Single-Event Indices Based on Three-Phase Characteristics.8.9 Additional Information from Dips and Interruptions.8.10 Transients.8.11 Summary and Conclusions.9 EVENT CLASSIFICATION.9.1 Overview of Machine Data Learning Methods for Event Classification.9.2 Typical Steps Used in Classification System.9.3 Learning Machines Using Linear Discriminants.9.4 Learning and Classification Using Probability Distributions.9.5 Learning and Classification Using Artificial Neural Networks. 9.6 Learning and Classification Using Support Vector Machines.9.7 Rule-Based Expert Systems for Classification of Power System Events.9.8 Summary and Conclusions. 10 EVENT STATISTICS.10.1 Interruptions.10.2 Voltage Dips: Site Indices.10.3 Voltage Dips: Time Aggregation.10.4 Voltage Dips: System Indices.10.5 Summary and Conclusions. 11 CONCLUSIONS.11.1 Events and Variations.11.2 Power Quality Variations.11.3 Power Quality Events.11.4 Itemization of Power Quality.11.5 Signal-Processing Needs.APPENDIX A IEC STANDARDS ON POWER QUALITY.APPENDIX B IEEE STANDARDS ON POWER QUALITY.BIBLIOGRAPHY.INDEX.

Math H.J. Bollen grew up in Geulle, The Netherlands, and received the PhD degree in 1989. Currently, he is manager of EMC and Power Quality at STRI, Ludvika, Sweden, and a guest professor at Luleå University of Technology. Math is known for his contributions to power quality analysis through numerous papers, working-group activities, and an earlier textbook, Understanding Power Quality Problems: Voltage Sags and Interruptions, (Wiley-IEEE Press). In 2005, he became an IEEE Fellow for his contributions to methods for reliability and power quality analysis. Irene Y.H. Gu grew up in Shanghai, China. She moved to The Netherlands in 1988 and received the PhD degree in 1992. Since 1996 she has been with the Department of Signals and Systems, Chalmers University of Technology (Gothenburg, Sweden) and has been a professor in signal processing there since 2004. She is also a guest professor at Shanghai Jiao Tong University (China). Irene Gu and Math Bollen were married in Eindhoven in 1992.

"This book provides an excellent description of power quality issues and the methods used to measure these signals. It is an excellent resources for learning about the latest signal processing methods used for power quality monitoring as well as power quality in general." (IEEE Electrical Insulation Magazine, January/February 2008)

• PREFACE. ACKNOWLEDGMENTS.1 INTRODUCTION.1.1 Modern View of Power Systems.1.2 Power Quality.1.3 Signal Processing and Power Quality.1.4 Electromagnetic Compatibility Standards.1.5 Overview of Power Quality Standards.1.6 Compatibility Between Equipment and Supply.1.7 Distributed Generation.1.8 Conclusions.1.9 About This Book.2 ORIGIN OF POWER QUALITY VARIATIONS.2.1 Voltage Frequency Variations.2.2 Voltage Magnitude Variations.2.3 Voltage Unbalance.2.4 Voltage Fluctuations and Light Flicker.2.5 Waveform Distortion. 2.6 Summary and Conclusions.3 PROCESSING OF STATIONARY SIGNALS.3.1 Overview of Methods.3.2 Parameters That Characterize Variations.3.3 Power Quality Indices.3.4 Frequency-Domain Analysis and Signal Transformation.3.5 Estimation of Harmonics and Interharmonics.3.6 Estimation of Broadband Spectrum.3.7 Summary and Conclusions. 3.8 Further Reading.4 PROCESSING OF NONSTATIONARY SIGNALS.4.1 Overview of Some Nonstationary Power Quality Data Analysis  Methods.4.2 Discrete STFT for Analyzing Time-Evolving Signal Components.4.3 Discrete Wavelet Transforms for Time–Scale Analysis of Disturbances.4.4 Block-Based Modeling.4.5 Models Directly Applicable to Nonstationary Data.4.6 Summary and Conclusion.4.7 Further Reading.5 STATISTICS OF VARIATIONS.5.1 From Features to System Indices.5.2 Time Aggregation.5.3 Characteristics Versus Time.5.4 Site Indices. 5.5 System Indices.5.6 Power Quality Objectives.5.7 Summary and Conclusions.6 ORIGIN OF POWER QUALITY EVENTS.6.1 Interruptions.6.2 Voltage Dips. 6.3 Transients.6.4 Summary and Conclusions. 7 TRIGGERING AND SEGMENTATION.7.1 Overview of Existing Methods.7.2 Basic Concepts of Triggering and Segmentation. 7.3 Triggering Methods.7.4 Segmentation. 7.5 Summary and Conclusions.8 CHARACTERIZATION OF POWER QUALITY EVENTS.8.1 Voltage Magnitude Versus Time.8.2 Phase Angle Versus Time. 8.3 Three-Phase Characteristics Versus Time.8.4 Distortion During Event.8.5 Single-Event Indices: Interruptions.8.6 Single-Event Indices: Voltage Dips.8.7 Single-Event Indices: Voltage Swells. 8.8 Single-Event Indices Based on Three-Phase Characteristics.8.9 Additional Information from Dips and Interruptions.8.10 Transients.8.11 Summary and Conclusions.9 EVENT CLASSIFICATION.9.1 Overview of Machine Data Learning Methods for Event Classification.9.2 Typical Steps Used in Classification System.9.3 Learning Machines Using Linear Discriminants.9.4 Learning and Classification Using Probability Distributions.9.5 Learning and Classification Using Artificial Neural Networks. 9.6 Learning and Classification Using Support Vector Machines.9.7 Rule-Based Expert Systems for Classification of Power System Events.9.8 Summary and Conclusions. 10 EVENT STATISTICS.10.1 Interruptions.10.2 Voltage Dips: Site Indices.10.3 Voltage Dips: Time Aggregation.10.4 Voltage Dips: System Indices.10.5 Summary and Conclusions. 11 CONCLUSIONS.11.1 Events and Variations.11.2 Power Quality Variations.11.3 Power Quality Events.11.4 Itemization of Power Quality.11.5 Signal-Processing Needs.APPENDIX A IEC STANDARDS ON POWER QUALITY.APPENDIX B IEEE STANDARDS ON POWER QUALITY.BIBLIOGRAPHY.INDEX.