Nuthalapati Power System Grid Operation Using Synchrophasor Technology

1. Auflage 2019
ISBN: 978-3-319-89378-5
Verlag: Springer Nature Switzerland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 508 Seiten

Reihe: Power Electronics and Power Systems

This book brings together successful stories of deployment of synchrophasor technology in managing the power grid. The authors discuss experiences with large scale deployment of Phasor Measurement Units (PMUs) in power systems across the world, enabling readers to take this technology into control center operations and develop good operational procedures to manage the grid better, with wide area visualization tools using PMU data.

Sarma Nuthalapati is currently working as Principal EMS Network Applications Engineer for Peak Reliability (Peak) in Vancouver, WA, USA. Peak's Reliability Coordinator Area includes all or parts of 14 western states, British Columbia, and the northern portion of Baja California, Mexico. Sarma supports Energy Management Systems (EMS) network applications such as State Estimation, Real-time Contingency Analysis, Remedial Action Schemes, Forced Outage Detection, and others that are critical to providing wide area situational awareness in control center operations. He is also an Adjunct Professor in the Department of Electrical Engineering at Texas A&M University, College Station, TX, USA. He has been with Electric Reliability Council of Texas, Inc. (ERCOT), USA, in the Advanced Network Applications Group of the Operations Support Department from August 2007 to March 2016 and was involved in the area of network applications and involved in a Synchrophasor Project funded by the US Department of Energy (DOE) under the Smart Grid Initiatives Grants. He is currently the Chair of the IEEE Task Force on Real Time Contingency Analysis. He also actively participates in the North American SynchroPhasor Initiative (NASPI) Working Group meetings and was given NASPI Control Room Solutions Task Team Most Valuable Player (MVP) Award for 'being a leading organizer and contributor to the Control Room Solutions Task Team (CRSTT) and the NERC Synchronized Measurement Subcommittee and a public champion for Synchrophasor Technology'. He is a senior member of IEEE and a member of IEEE Power and Energy Society (PES). He is also a distinguished lecturer in the IEEE PES Distinguished Lecturer Program. He received BTech (Electrical Engineering) and MTech (Power Systems Engineering) degrees from National Institute of Technology, Warangal, (formerly called as Regional Engineering College, Warangal), India, in 1983 and 1986 respectively. He obtained his PhD degree from Indian Institute of Technology, Delhi, India, in 1995. He carried out his PhD work in the area of 'Network Reconfiguration in Distribution Systems' under the supervision of the late Dr. K.S. Prakasa Rao. The research work involved developing new algorithms for various aspects of network reconfiguration such as reconfiguration for Service Restoration, Load Balancing and Loss Minimization in Distribution Systems. These methods are very useful in the context of Smart Grids and Distribution Automation.

Autoren/Hrsg.

Nuthalapati, Sarma (Ndr)

Inhaltsverzeichnis

1;Foreword;7
2;Preface;9
3;Contents;14
4;1 Importance of Synchrophasor Technology in Managing the Grid;16
4.1;1.1 The Value of High-Speed Time-Stamped Data;16
4.2;1.2 More About Time Synchronization;19
4.3;1.3 The Principal Applications and Benefits of Synchrophasor Technology;20
4.4;1.4 The Role of the US Department of Energy Promoting the Deployment of Synchrophasors in the North American Power System;21
5;2 Impact of Phasor Measurement Data Quality in Grid Operations;27
5.1;2.1 Introduction;27
5.2;2.2 Categories of Data Impairment;28
5.2.1;2.2.1 Data Loss;28
5.2.2;2.2.2 Data Corruption;30
5.2.3;2.2.3 Inaccurate Representation;31
5.2.4;2.2.4 Lack of Precision;33
5.2.5;2.2.5 Incorrect Identification of Data;35
5.2.6;2.2.6 Excessive or Inconsistent Latency;36
5.3;2.3 Data Error Control and Detection;37
5.3.1;2.3.1 Measurement System Planning and Design;37
5.3.2;2.3.2 Installation and Validation;39
5.3.3;2.3.3 Error Detection and Mitigation;40
5.4;2.4 Impacts of Data Impairments;43
5.4.1;2.4.1 Introduction;43
5.4.2;2.4.2 Lost Data;46
5.4.3;2.4.3 Data Corruption;47
5.4.4;2.4.4 Inaccurate Representation of Engineering Quantity;48
5.4.5;2.4.5 Lack of Precision;51
5.4.6;2.4.6 Incorrect Measurement Identification;52
5.4.7;2.4.7 Excessive or Inconsistent Latency;52
5.5;2.5 Summary;53
5.6;References;54
6;3 Testing and Validation of Synchrophasor Devices and Applications;55
6.1;3.1 Introduction;55
6.2;3.2 Review of Synchrophasor Technology and Phasor Measurement Unit (PMU);57
6.2.1;3.2.1 Synchrophasor Applications in Power System Operation;59
6.2.2;3.2.2 Need for Testing and Validation of Synchrophasors Devices and Applications;59
6.3;3.3 Testing of Synchrophasor Devices;60
6.3.1;3.3.1 Review of Synchrophasors Standards and Compliance Testing of PMU;60
6.3.2;3.3.2 Procedure and Hardware Requirement for PMU Testing;62
6.3.3;3.3.3 Testbed Architecture and PMU Performance Analyzer (PPA);64
6.3.4;3.3.4 Example Results for PMU Testing at South California Edison;66
6.4;3.4 Testing and Validation of Synchrophasors-Based Monitoring Application;68
6.4.1;3.4.1 PMU Data Quality and Impact on Applications;68
6.4.2;3.4.2 PARTF Framework for Analyzing Impact of PMU Data Quality on Applications;70
6.4.3;3.4.3 Preprocessing PMU Data for Event Detection;71
6.4.4;3.4.4 Synchrophasors-Based Event Detection;73
6.4.5;3.4.5 Testbed Architecture for Validation of Event Detection Application;73
6.4.6;3.4.6 Example Validation Results for PMU-Based Event Detection;76
6.5;3.5 Testing and Validation of Synchrophasors-Based Control Application;78
6.5.1;3.5.1 Synchrophasors-Based Remedial Action Schemes;80
6.5.2;3.5.2 Testbed Architecture for RAS Testing;81
6.5.3;3.5.3 Example RAS Testing Results;84
6.6;3.6 Summary;86
6.7;References;87
7;4 Synchrophasor Technology at BPA;90
7.1;4.1 History of the Synchrophasor Technology at BPA;91
7.2;4.2 BPA Synchrophasor Investment Project;92
7.3;4.3 Engineering Applications at BPA;94
7.3.1;4.3.1 Power Plant Model Validation;95
7.3.2;4.3.2 Power Plant Performance Monitoring and Analysis;98
7.3.3;4.3.3 System Model Validation and Event Analysis;99
7.3.4;4.3.4 Event Analysis;100
7.3.5;4.3.5 Frequency Response Analysis;102
7.3.6;4.3.6 Oscillation Event Analysis;103
7.3.7;4.3.7 Voltage Fluctuations due to Variable Transfers;105
7.3.8;4.3.8 State Estimation;106
7.3.9;4.3.9 Data Quality Monitoring;106
7.4;4.4 Control Room Applications at BPA;107
7.4.1;4.4.1 Oscillation Detection;107
7.4.2;4.4.2 Frequency Event Detection;110
7.4.3;4.4.3 Islanding Detection;112
7.4.4;4.4.4 Mode Meter or Low Oscillation Damping Detection;113
7.5;4.5 Synchrophasor-Based Controls;114
7.6;4.6 Value Realized from the BPA Synchrophasor Project;117
7.7;4.7 Technology Innovation Pipeline;122
7.7.1;4.7.1 Synchrophasor Infrastructure;122
7.7.2;4.7.2 Engineering Analysis;123
7.7.3;4.7.3 Control Room Applications;123
7.7.4;4.7.4 Wide-Area Controls;124
7.7.5;4.7.5 Collaboration and Technology Outreach;126
7.8;4.8 Synchrophasor Project Team;127
7.9;4.9 Relevant Technology Innovation Projects;128
7.10;Acknowledgements;128
7.11;Appendix A: July 2, 1996 Western Interconnection Outage;129
7.12;Appendix B: August 10, 1996 Western Interconnection Outage;130
7.13;Appendix C: June 14, 2004 Generation Outage in the West;130
7.14;Appendix D: Frequency Response Analysis at BPA;131
7.14.1;Event Detection;131
7.14.2;Notification;132
7.14.3;Visualization;132
7.14.4;Data Extract;134
7.14.5;Analysis;134
7.14.6;Baselining;135
7.14.7;Generating Fleet Performance Analysis;137
7.14.8;Power Pickup Analysis;138
8;5 Use of Synchrophasor Measurement Technology in China;141
8.1;5.1 Introduction;141
8.2;5.2 Development and Applications of PMUs in China;141
8.2.1;5.2.1 Status of PMU Deployment;141
8.2.2;5.2.2 PMU Supporting IEC 61850 Protocol;142
8.2.3;5.2.3 Data Transmission Network and Time Synchronization Networks in Chinese Power Grids;143
8.3;5.3 Development and Basic Applications of WAMS in China;144
8.3.1;5.3.1 Architecture of WAMS;144
8.3.2;5.3.2 Power System Model Parameter Identification and Validation;145
8.3.2.1;5.3.2.1 Load Model and Parameter Identification;145
8.3.2.2;5.3.2.2 Identification of Generator’s Moment of Inertia;147
8.3.3;5.3.3 Disturbance Recognition and Location;148
8.4;5.4 Estimation of Electromechanical Modes from Ambient PMU Data;151
8.4.1;5.4.1 Classification of PMU Data;151
8.4.2;5.4.2 ARMA-Based Identification Method;152
8.4.3;5.4.3 Application Case in CSG;153
8.4.4;5.4.4 Low-Frequency Oscillation Mechanism Analysis;156
8.5;5.5 Phasor Measurement-Based Wide-Area Protection (WAP) Application;160
8.5.1;5.5.1 Problems Faced by Conventional Protection;160
8.5.2;5.5.2 Architecture of WAP System;160
8.5.3;5.5.3 Proposed WAP Functions;162
8.5.3.1;5.5.3.1 Enhanced Current Differential Protection;162
8.5.3.2;5.5.3.2 Pilot Direction Protection;163
8.5.3.3;5.5.3.3 Protection for CB Failure;163
8.5.4;5.5.4 Application Case Study;164
8.5.4.1;5.5.4.1 Brief Description of Duyun WAP System;164
8.5.4.2;5.5.4.2 Recorded Event with Wide-Area Backup Protection in Operation;165
8.6;5.6 Wide-Area Damping Control Utilizing HVDC Modulation;166
8.6.1;5.6.1 Research Background;166
8.6.2;5.6.2 Structure of WADC System Utilizing HVDC Modulation;168
8.6.3;5.6.3 Time Delay in the Control Loop and Its Countermeasures;170
8.6.4;5.6.4 Operational Experience of WADC;171
8.7;5.7 Monitoring and Assessment on Integrated Wind Farm;173
8.7.1;5.7.1 Intelligent Alarm for the Cascading Tripping of Wind Turbines;173
8.7.2;5.7.2 Event Analysis for Subsynchronous Interaction Between Wind Farms and AC Networks;173
8.7.3;5.7.3 Online Wide-Area SSR Monitoring for Wind Farms Integrated with Weak AC Networks;177
8.7.3.1;5.7.3.1 Synchronous Wide Frequency Range Measurement Unit;177
8.7.3.2;5.7.3.2 Online SSR Monitoring and Alarming;178
8.8;References;179
9;6 Identification of Signature Oscillatory Modes in ERCOT by Mining of Synchrophasor Data;180
9.1;6.1 Introduction;180
9.2;6.2 Data Mining for Oscillations on the ERCOT System;181
9.2.1;6.2.1 Sustained, Poorly Damped Oscillations;181
9.2.2;6.2.2 Rapid, Un- or Negatively Damped Oscillations;181
9.2.3;6.2.3 Data Mining for Oscillations;182
9.2.4;6.2.4 Phasor Data Mining Tool;183
9.2.5;6.2.5 Post-processing;184
9.2.6;6.2.6 Mode Identification;184
9.3;6.3 Metrics for Classification of Oscillations;185
9.3.1;6.3.1 Monthly Highest Energy;185
9.3.2;6.3.2 Monthly Mode Occurrence;186
9.4;6.4 Generalized Approach for Identification of Signature Oscillations in a System;186
9.5;6.5 Illustration on the ERCOT System;187
9.5.1;6.5.1 0.9 Hz, 2.7 Hz—Related to Wind Production;189
9.5.2;6.5.2 3.2 Hz—Related to Control System Settings Changes;191
9.5.3;6.5.3 5.0, 5.4, and 6.0 Hz—Related to Control Systems;193
9.5.4;6.5.4 Summary;194
9.6;6.6 Conclusion;195
9.7;References;196
10;7 Oscillation Detection in Real-Time Operations at ERCOT;197
10.1;7.1 Introduction;197
10.2;7.2 The ERCOT Phasor Measurement Task Force [8];198
10.3;7.3 Detection of Oscillations in Real Time;199
10.3.1;7.3.1 Controller Parameter Degradation;199
10.3.2;7.3.2 Weak Grid Oscillations;201
10.3.3;7.3.3 Controller Parameter Settings;202
10.4;7.4 Conclusions;203
10.5;References;204
11;8 Oscillation Detection and Mitigation Using Synchrophasor Technology in the Indian Power Grid;205
11.1;8.1 Introduction;205
11.2;8.2 Cases of Low-Frequency Oscillation in the Indian Grid and Measures Taken/Required for Their Improved Damping;207
11.3;8.3 Conclusion;225
11.4;References;226
12;9 Experiences of Oscillation Detection and Mitigation in Grid Operations at PEAK Reliability;227
12.1;9.1 Introduction;227
12.2;9.2 Overview of Montana Tech MAS Tool;229
12.2.1;9.2.1 Mode Meter Functionality;229
12.3;9.3 Peak’s Experience with MAS Mode Meters (MMM);234
12.4;9.4 Forced Oscillation Detection and Analysis at PEAK;241
12.5;9.5 Conclusion;264
12.6;Acknowledgements;265
12.7;References;265
13;10 Online Oscillations Management at ISO New England;267
13.1;10.1 Introduction;267
13.2;10.2 Practically Observed Sustained Oscillations in Power Systems;267
13.3;10.3 Mitigation of Oscillations;270
13.4;10.4 Locating the Source of Sustained Oscillations;272
13.4.1;10.4.1 Methods for Locating the Source of Oscillations;273
13.4.2;10.4.2 Magnitude of Oscillations as an Indicator of the Source Location;275
13.4.3;10.4.3 The Dissipating Energy Flow Method;276
13.4.3.1;10.4.3.1 Original Energy-Based Method;276
13.4.3.2;10.4.3.2 Challenges in Actual Power Systems;277
13.4.3.3;10.4.3.3 Modification of the Method for Use with Actual PMU Data;277
13.4.4;10.4.4 Testing the Oscillation Source Locating Methods;280
13.5;10.5 Testing the Dissipation Energy Flow Method;281
13.5.1;10.5.1 Simulated Cases;281
13.5.2;10.5.2 Actual Events in ISO-NE System;283
13.5.3;10.5.3 Actual Events in WECC;285
13.5.4;10.5.4 Impact of the Energy-Based Method Assumptions;286
13.6;10.6 Installation of PMUs for Locating the Source of Forced Oscillations;288
13.7;10.7 Online Oscillation Management at ISO-NE;288
13.8;10.8 Online Monitoring of the Generator Damping Contribution;290
13.9;10.9 Conclusions;291
13.10;References;292
14;11 Operational Use of Synchrophasor Technology for Power System Oscillations Monitoring at California ISO;294
14.1;11.1 Introduction;294
14.2;11.2 Synchrophasor Data Gathering Architecture at Caiso;296
14.3;11.3 Oscillations Monitoring and Examples of Power System Oscillation Events Observed at Caiso;297
14.3.1;11.3.1 Voltage Oscillations at 500 KV Station March, 2016;299
14.3.2;11.3.2 High-Frequency Solar Plant Local Oscillation in SCE Area Near Devers on April 25, 2014;300
14.3.3;11.3.3 Local Oscillations at Pacific DC Intertie (PDCI) Station in Oregon in Jan, 2008—Operating Logs;301
14.4;11.4 Potential Future Work;304
14.5;Acknowledgements;305
14.6;References;305
15;12 Operational Use of Synchrophasor Technology for Wide-Area Power System Phase Angle Monitoring at California ISO;306
15.1;12.1 Introduction and Chapter Overview;306
15.2;12.2 Basic Principles of Phase Angle Monitoring and Implementation Overview at CAISO;307
15.3;12.3 Examples of Using Angle Monitoring in Operations;309
15.3.1;12.3.1 Validation of State Estimation Results in Certain Portions of the Network;309
15.3.2;12.3.2 Using Phasor Data for Situational Awareness to Allow for Safe Switching;311
15.3.3;12.3.3 Operator Displays;312
15.4;12.4 Potential Future Work;313
15.5;Acknowledgements;313
15.6;References;314
16;13 Synchrophasor-Based Linear State Estimation Techniques and Applications;315
16.1;13.1 Introduction to Synchrophasor-Based State Estimation Analytics;315
16.1.1;13.1.1 The Service that State Estimators Provide to the Analytics Pipeline;317
16.1.2;13.1.2 Considerations Regarding Network Observability with Synchrophasors;317
16.1.3;13.1.3 Considerations Regarding Topology Processing;320
16.2;13.2 Static Weighted Least Squares Linear State Estimation Techniques;321
16.2.1;13.2.1 Positive Sequence Linear WLS State Estimation;321
16.2.2;13.2.2 Three-Phase Linear WLS State Estimation;323
16.2.3;13.2.3 Implementation History;324
16.3;13.3 Dynamic State Estimation Techniques;325
16.3.1;13.3.1 Robust Linear Phasor-Assisted Dynamic State Estimation;326
16.3.2;13.3.2 Least Absolute Value Linear State Estimator;326
16.3.3;13.3.3 UKF-Based Dynamic State Estimation;327
16.3.4;13.3.4 Implementation of TRODSE;329
16.4;13.4 Applications;331
16.4.1;13.4.1 Load Modeling;331
16.4.1.1;13.4.1.1 Exponential Dynamic Load Model;332
16.4.1.2;13.4.1.2 Proposed Approach;332
16.4.1.3;13.4.1.3 Implementation of the Proposed Approach with Historical Field Measurements;333
16.4.2;13.4.2 Failure Detection of the Synchronous Generator Excitation Systems;335
16.4.2.1;13.4.2.1 Multiple Model Estimation Technique;337
16.4.2.2;13.4.2.2 Proposed Approach for the Detection of Exciter Failure in Dynamic State Estimation;337
16.4.3;13.4.3 Post-estimation Symmetrical Component Computation;339
16.5;13.5 Conclusion;340
16.6;References;341
17;14 Implementation of Synchrophasor-Based Linear State Estimator for Real-Time Operations;342
17.1;14.1 Introduction;342
17.2;14.2 Synchrophasor-Based Linear State Estimator: Theory;343
17.2.1;14.2.1 Traditional State Estimation Algorithm;343
17.2.2;14.2.2 Linear State Estimation Algorithm;345
17.3;14.3 Synchrophasor-Based Linear State Estimator: Implementation;346
17.3.1;14.3.1 LSE Integration;346
17.3.1.1;14.3.1.1 Network Model Integration;347
17.3.1.2;14.3.1.2 PMU Data Mapping;347
17.3.1.3;14.3.1.3 Real-Time Topology Update;348
17.3.2;14.3.2 LSE Application Components;348
17.3.2.1;14.3.2.1 Topology Process;348
17.3.2.2;14.3.2.2 Real-Time Observability Analysis;348
17.3.2.3;14.3.2.3 LSE Matrix Formulation;350
17.3.2.4;14.3.2.4 Bad Data Detection and Identification;351
17.3.3;14.3.3 LSE Operation Procedure;353
17.4;14.4 Linear State Estimator Use Cases at Utilities;355
17.4.1;14.4.1 Synchrophasor Data Validation and Conditioning;356
17.4.1.1;14.4.1.1 Validation and Conditioning Historical Event Field PMU Data;357
17.4.1.2;14.4.1.2 Validation and Conditioning Real-Time Field PMU Data;359
17.4.2;14.4.2 Independent Wide-Area Situational Awareness for Grid Resiliency and Synchrophasor Data Analytics;360
17.4.2.1;14.4.2.1 Wide-Area Situational Awareness;361
17.4.2.2;14.4.2.2 Phase Angle Difference for Grid Stress Monitoring;362
17.4.2.3;14.4.2.3 Oscillation Analysis and Monitoring;363
17.4.3;14.4.3 Extend Synchrophasor Measurement Coverage and Benefits for Potential Downstream Applications;364
17.4.3.1;14.4.3.1 Methodology and Deployment at SCE;364
17.4.3.2;14.4.3.2 Expanded Observability for Line Closing;366
17.4.3.3;14.4.3.3 Expanded Observability for Remedial Action Scheme (RAS) Testing;366
17.4.3.4;14.4.3.4 Expanded Observability for Operator Training;367
17.4.4;14.4.4 Performance Assessment;367
17.5;14.5 Conclusions;368
17.6;References;368
18;15 Post-event Analysis in the ERCOT System Using Synchrophasor Data;370
18.1;15.1 Introduction;370
18.2;15.2 Post-event Analysis;371
18.2.1;15.2.1 System Frequency;372
18.2.2;15.2.2 Voltage Magnitude Swings;373
18.2.3;15.2.3 Voltage Angle Swings;374
18.2.4;15.2.4 Oscillation Modes;376
18.3;15.3 Case Study 1—Loss of Generation Event;376
18.3.1;15.3.1 System Frequency;376
18.3.2;15.3.2 Voltage Magnitude Swings;377
18.3.3;15.3.3 Voltage Angle Swings;379
18.3.4;15.3.4 Oscillation Modes;380
18.4;15.4 Case Study 2—Compound Event Inducing a Loss of Generation Event;383
18.4.1;15.4.1 The Power Load Unbalance (PLU) Relay;384
18.4.2;15.4.2 System Frequency;385
18.4.3;15.4.3 System Phase-to-Ground Fault;385
18.4.4;15.4.4 Loss of Generation;386
18.5;15.5 Conclusions;389
18.6;References;389
19;16 Validation and Tuning of Remedial Action Schemes in Indian Grid Operations Using Synchrophasor Technology;391
19.1;16.1 Introduction;391
19.2;16.2 SPS Performance Evaluation;393
19.3;16.3 WAMS in Indian Grid;394
19.4;16.4 Monitoring of SPS Using Synchrophasors;395
19.5;16.5 Case Studies;396
19.6;16.6 Conclusion;405
19.7;References;406
20;17 Indian Power System Operation Utilizing Multiple HVDCs and WAMS;408
20.1;17.1 Introduction;408
20.2;17.2 Conclusions/Way Forward;436
20.3;References;437
21;18 Model Validation Using Synchrophasor Technology;438
21.1;18.1 Introduction;438
21.2;18.2 Plant Model Validation;439
21.2.1;18.2.1 System Model Validation;442
21.2.2;18.2.2 Benchmarking System Interface;445
21.2.3;18.2.3 Benchmarking Frequency Response of Interconnection;447
21.3;18.3 Conclusions;451
21.4;References;451
22;19 A Software Suite for Power System Stability Monitoring Based on Synchrophasor Measurements;453
22.1;19.1 Introduction;453
22.2;19.2 GSAS Architecture;454
22.2.1;19.2.1 Design Consideration;454
22.3;19.3 System Architecture;455
22.4;19.4 GSAS Stability Monitoring Modules;457
22.4.1;19.4.1 Oscillation Monitoring Tool;457
22.4.2;19.4.2 Voltage Stability Monitoring Tool;458
22.4.3;19.4.3 Transient Instability Monitoring Tool;459
22.4.4;19.4.4 Angle Difference Monitoring Tool;460
22.4.5;19.4.5 Event Detection Tool;460
22.5;19.5 GSAS Alarming;461
22.5.1;19.5.1 GSAS Alarming Mechanisms;461
22.5.2;19.5.2 GSAS Alarming Dashboard;461
22.5.3;19.5.3 GSAS Alarming Logs;463
22.6;19.6 Off-line Validation of GSAS Performance;463
22.6.1;19.6.1 Overview;463
22.6.2;19.6.2 Procedure and Methodology for Off-line Performance Validation;465
22.6.2.1;19.6.2.1 Validation Procedure;465
22.6.2.2;19.6.2.2 Validation Cases;465
22.6.2.3;19.6.2.3 Testing Approach;466
22.6.2.4;19.6.2.4 Six General Cases;467
22.6.3;19.6.3 Performance of Voltage Stability Monitoring Tool;467
22.6.3.1;19.6.3.1 Overview of Voltage Stability Analysis Method;467
22.6.3.2;19.6.3.2 Results of Validations Based on PSS/E Simulations;469
22.6.4;19.6.4 Performance of Oscillation Monitoring Tool;472
22.6.4.1;19.6.4.1 Overview of Oscillation Analysis Method;472
22.6.4.2;19.6.4.2 Results of Off-line Validation Based on PSS/E Simulations;473
22.6.5;19.6.5 Performance of Transient Stability Monitoring Tool;474
22.6.5.1;19.6.5.1 Overview of Transient Stability Monitoring Method;474
22.6.5.2;19.6.5.2 Results of Off-line Validation Based on Simulations;476
22.7;19.7 Conclusions;478
22.8;References;479
23;20 A Cloud-Hosted Synchrophasor Data Sharing Platform;481
23.1;20.1 Introduction;481
23.1.1;20.1.1 Synchrophasor System at ISO New England;482
23.1.2;20.1.2 PMU Data Exchange with External Regions;483
23.1.3;20.1.3 Problem Statement of the Existing Implementation of PMU Data Exchange;484
23.2;20.2 Why the Cloud?;486
23.2.1;20.2.1 Overview of Cloud Computing Technology;486
23.2.2;20.2.2 GridCloud Platform;489
23.2.2.1;20.2.2.1 The GridCloud Security Architecture;490
23.2.2.2;20.2.2.2 The GridCloud Data Collection Layer;490
23.2.2.3;20.2.2.3 The GridCloud Archival Data Storage Subsystem;490
23.2.2.4;20.2.2.4 Cloud Manager;491
23.3;20.3 Proof-of-Concept Cloud-Hosted Wide Area Monitoring System;491
23.3.1;20.3.1 Conceptual Overview of the Cloud-Hosted Synchrophasor Platform;492
23.3.2;20.3.2 Proof-of-Concept Experiment Setup;494
23.3.3;20.3.3 Experiment Findings;495
23.3.3.1;20.3.3.1 Security;495
23.3.3.2;20.3.3.2 Latency;496
23.3.3.3;20.3.3.3 Data Consistency and Fault Tolerance;497
23.3.3.4;20.3.3.4 Operational Cost;500
23.4;20.4 Challenges and Future Research Directions;500
23.5;References;501
24;Index;503