Monitoring and controlling of large power systems is becoming more challenging as a consequence of the growth of their size, increasing demand for electricity, penetration of variable renewable energy sources, uncertainty in many operating parameters, and the growing number of interconnections. Therefore, system operators feel the need for a real-time wide area monitoring, protection and control system that provides more accurate information about the state of the power system and assists operators in the implementation of corrective actions to operate at high levels of security and reliability and to respond rapidly to disturbances. Synchronized measurement technology, which allow taking synchronized measurements from widely dispersed locations, has made possible the development of real-time wide area monitoring systems. At present, phasor measurements units (PMUs) are the devices most used for power system monitoring. When a PMU is placed at a bus, it can provide an accurate measurement of the voltage phasor (magnitude and angle), as well as the current phasors through the incident transmission lines.
- Cover
- Title page
- Copyright page
- Contents
- List of Figures
- List of Tables
- Preface
- Abstract
- Chapter one. Introduction
- 1.1 Phasor Measurement Unit
- 1.2 Phasor Measurement Unit Placement
- 1.3 Applications of Synchronized Measurement Technology
- 1.4 Objectives and Contributions
- 1.5 Chapter Overview
- 1.5.1 Chapter 2: ILP-based multistage placement of PMUs
- 1.5.2 Chapter 3: Reliability-based PMU placement in power systems considering transmission line outages
- 1.5.3 Chapter 4: Real-time identification of coherent groups based od graph theory
- 1.5.4 Chapter 5: A practical online monitoring system based on wide area measurements for power system islanding
- 1.5.5 Chapter 6: Contributions, limitations, and future research
- Part I. Phasor Measurement Unit Placement
- Chapter two. ILP-Based Multistage Placement of PMUs
- 2.1 ILP-based Model for Optimal Multistage Scheduling of PMU Placement
- 2.2 Modeling of Zero-Injections Buses
- 2.3 Numerical Examples
- 2.3.1 Optimal multistage placement
- 2.3.2 Optimal multistage placement considering the effect of zero-injection
- 2.3.3 Optimal multi-stage placement considering expansion
plans
- 2.4 Concluding Remarks
- Chapter three. Reliability-Based PMU Placement in Power Systems Considering Transmission Line Outages
- Chapter three. Reliability-Based PMU Placement in Power Systems Considering Transmission Line Outages
- 3.1 Substation Monitoring System
- 3.1.1 Monitoring system components
- 3.1.2 Branch PMU
- 3.1.3 Substation configuration
- 3.1.4 Substation communication system
- 3.2 Substation Monitoring System Reliability
- 3.2.1 Failure probability of voltage measurement
- 3.2.2 Failure probability of current measurement
- 3.3 SMS Placement Based on Bus Reliability
- 3.4 Reliability-Based Substation Monitoring System Placement Considering Transmission Line Outages
- 3.5 Evaluation of Reliability-Based SMS
Placement
- 3.6 Numerical Studies
- 3.6.1 Reliability-based PMU placement in the WSCC 3-machine, 9-bus system
- 3.6.2 Reliability-based PMU placement in the IEEE 57-bus test system
- 3.6.3 Reliability analysis of the monitoring systems in the IEEE 9-bus test system
- 3.6.4 Reliability analysis of the monitoring systems in the IEEE 57-bus test system
- 3.7 Concluding Remarks
- Part II. Phasor Measurement Unit Applications for Controlled Islanding
- Chapter four. Real Time Identification of Coherent Groups Based on Graph Theory
- Real Time Identification of Coherent Groups Based on Graph Theory
- 4.1 Graph Modeling of Power Systems
- 4.2 Recursive Spectral Bisection
- 4.3 Maximum Spanning Tree Clustering
- 4.3.1 Fukuyama-Sugeno partition 1
- 4.3.2 Fukuyama-Sugeno partition 2
- 4.4 Minimum Cut Tree Clustering
- 4.5 Community Detection
- 4.6 Test Systems and Results
- 4.6.1 Recursive spectral bisection
- 4.6.2 Maximum spanning tree
- 4.6.3 Minimum cut tree clustering
- 4.6.4 Community detection
- 4.6.5 Discussion about the implemented methodologies
- 4.6.6 On-line identification of coberent, generators for the 10-machine New-England power system
- 4.6.7 Online identification of coherent generators for the IEEE 118 bus test system by using community detection
- 4.7 Concluding Remarks
- Chapter five. A Practical Online Monitoring System Based on Wide Area Measurements for Power System Islanding
- 5.1 Stability Prediction Index (SPI )
- 5.1.1 Temporal window
- 5.1.2 Voltage magnitude
- 5.1.3 Phase angle
- 5.1.4 Thresholds values
- 5.1.5 Reference values, deviation percent and SPI
- 5.2 Prony Signal Analysis
- 5.2.1 Methods for the identification of electromechanical modes
- 5.2.2 Prony signal analysis
- 5.3 Monitoring Combined Scheme
- 5.4 Identification of the Island
- 5.5 Numerical Examples
- 5.5.1 SPI index and area definition for controlled islanding of the IEEE 39-bus test system
- 5.5.2 Monitoring combiened scheme and area definition for controlled islanding on the IEEE 118-bus test system
- 5.6 Concluding Remarks
- Chapter six. Contributions, Limitations, and Future Research
- 6.1 Contributions
- 6.2 Limitations and Future Research
- Appendices
- Appendix A. IEEE 9-Bus Test System
- Appendix B. IEEE 14-Bus Test System
- Appendix C. IEEE 39-Bus Test System
- Appendix D. IEEE 57-Bus Test System
- Appendix E. IEEE 118-Bus Test System
- Bibliography
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