Math Bollen

Bio: Math Bollen is an academic researcher from Luleå University of Technology. The author has contributed to research in topics: Electric power system & Harmonic. The author has an hindex of 59, co-authored 519 publications receiving 17496 citations. Previous affiliations of Math Bollen include Eindhoven University of Technology & Ocean University of China.

Understanding Power Quality Problems: Voltage Sags and Interruptions

Abstract: "Power quality problems have increasingly become a substantial concern over the last decade, but surprisingly few analytical techniques have been developed to overcome these disturbances in system-equipment interactions. Now in this comprehensive book, power engineers and students can find the theoretical background necessary for understanding how to analyze, predict, and mitigate the two most severe power disturbances: voltage sags and interruptions.This is the first book to offer in-depth analysis of voltage sags and interruptions and to show how to apply mathematical techniques for practical solutions to these disturbances. From UNDERSTANDING AND SOLVING POWER QUALITY PROBLEMS you will gain important insights intoVarious types of power quality phenomena and power quality standardsCurrent methods for power system reliability evaluationOrigins of voltage sags and interruptionsEssential analysis of voltage sags for characterization and prediction of equipment behavior and stochastic predictionMitigation methods against voltage sags and interruptions"Sponsored by:IEEE Power Electronics Society, IEEE Industry Applications Society, IEEE Power Engineering Society.

Signal processing of power quality disturbances

Abstract: 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.

Integration of Distributed Generation in the Power System

Abstract: Distributed Generation (DG) reduces the amount of energy lost in transmitting electricity because the electricity is generated very near where it is used. This book introduces systematic and transparent methods for quantifying the impact of DG on the power grid. It emphasizes systematic and transparent calculation methods, allowing for a quantification of the amount of DG that can be integrated at a certain location of the grid or in the grid as a whole. It also provides an overview of the different energy sources, with emphasis on wind power, solar power and combined heat and power in the power grid.

Feasibility of a DC network for commercial facilities

Abstract: This paper analyzes the feasibility of direct current for the supply of offices and commercial facilities. This is done by analyzing a case study, i.e. the supply to the Department of Electric Power Engineering, Chalmers University of Technology, Gothenburg, Sweden. Voltage drop calculations have been carried out for different voltage levels. A backup system for reliable power supply is designed based on commercially available batteries. Finally, an economic evaluation of AC versus DC is performed and protection of the proposed system is briefly addressed.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Overview of Control and Grid Synchronization for Distributed Power Generation Systems

Abstract: Renewable energy sources like wind, sun, and hydro are seen as a reliable alternative to the traditional energy sources such as oil, natural gas, or coal. Distributed power generation systems (DPGSs) based on renewable energy sources experience a large development worldwide, with Germany, Denmark, Japan, and USA as leaders in the development in this field. Due to the increasing number of DPGSs connected to the utility network, new and stricter standards in respect to power quality, safe running, and islanding protection are issued. As a consequence, the control of distributed generation systems should be improved to meet the requirements for grid interconnection. This paper gives an overview of the structures for the DPGS based on fuel cell, photovoltaic, and wind turbines. In addition, control structures of the grid-side converter are presented, and the possibility of compensation for low-order harmonics is also discussed. Moreover, control strategies when running on grid faults are treated. This paper ends up with an overview of synchronization methods and a discussion about their importance in the control

VSC-Based HVDC Power Transmission Systems: An Overview

Abstract: The ever increasing progress of high-voltage high-power fully controlled semiconductor technology continues to have a significant impact on the development of advanced power electronic apparatus used to support optimized operations and efficient management of electrical grids, which, in many cases, are fully or partially deregulated networks. Developments advance both the HVDC power transmission and the flexible ac transmission system technologies. In this paper, an overview of the recent advances in the area of voltage-source converter (VSC) HVdc technology is provided. Selected key multilevel converter topologies are presented. Control and modeling methods are discussed. A list of VSC-based HVdc installations worldwide is included. It is confirmed that the continuous development of power electronics presents cost-effective opportunities for the utilities to exploit, and HVdc remains a key technology. In particular, VSC-HVdc can address not only conventional network issues such as bulk power transmission, asynchronous network interconnections, back-to-back ac system linking, and voltage/stability support to mention a few, but also niche markets such as the integration of large-scale renewable energy sources with the grid and most recently large onshore/offshore wind farms.