J.M. Johnson

Bio: J.M. Johnson is an academic researcher from Pacific Northwest National Laboratory. The author has contributed to research in topics: Electric power system & Noise. The author has an hindex of 3, co-authored 4 publications receiving 415 citations.

Making Prony analysis more accurate using multiple signals

Abstract: Prony analysis has proven to be a valuable tool in estimating the modal content of power oscillations from measured ringdowns. The accuracy of the mode estimates is limited by the noise content always found in field measured signals. Current Prony analysis methods assume the system to be single output, and individual signals are analyzed independently often resulting in conflicting frequency and damping estimates (due to noise effects). This paper considers a simple extension to Prony analysis that allows multiple signals to be analyzed simultaneously resulting in one set of mode estimates. Examples are used to show that this extension improves the accuracy of modal estimates and simplifies the analysis steps. The first example uses a Monte Carlo type simulation model and the second analyzes field measured data from the western North American power system.

Keeping an eye on power system dynamics

Abstract: The authors describe how the Bonneville Power Authority (USA) began to develop integrated monitoring and analysis tools to meet the need for accurate and coordinated dynamic power system information in 1990. They detail how the Dynamic Information Technology Package (DITPak) has evolved and how it now includes virtual instrumentation using LabVIEW software, modular and readily networked measurement hardware, streamlined analysis software in a MATLAB working environment and optional use of familiar workstation tools for display and report generation.

SIMO system identification from measured ringdowns

Abstract: Recent variations of Prony analysis and similar methods have proven to be valuable tools in identifying transfer functions and estimating the modal content from measured ringdowns. Such tools are becoming a standard in power system dynamic analysis. Current analysis methods assume the system to be single-input single-output (SISO) with distinct eigenvalues. Individual signals are analyzed independently often resulting in conflicting frequency and damping estimates (due to noise effects). Also, one cannot apply Prony analysis to systems with repeated or very closely-spaced poles such as in power system subsynchronous resonance problems. This paper presents a variation of Prony analysis that allows identification of a single-input multi-output (SIMO) proper model with possible repeated poles. Prony analysis as a signal analysis method is first generalized to handle multiple signals with poles that may be repeated. Expressions are then derived for the transfer function terms assuming the input is a series of square-wave pulses. Advantages of the SIMO analysis method are demonstrated on a power system Monte Carlo type simulation model. The example shows that the SIMO formulation allows for more accurate estimation of electromechanical oscillation modes under noisy conditions (such as field measured data).

aking Prony Analysis More Accurate using Multiple Si

Abstract: Prony analysis has proven to be a valuable tool in estimating the iiiodal content of power oscillationb from ineasuled ringdowns The accuiacy of the inode estimates is 1,iiiited by !hc noise content alwaya found in field measured signals Lurrent Prony analysis methods assume the systein to be ?ingle output, and iiidividual signals are analyzed independently often resulting in conflicting frequency and damping estimates (due to noise effects) This paper considers a simple extension to Prony analysis that allows multiple signals to be analyzed simultaneously resulting in one set of mode estimates Examples are used to show that this extension improves the accuracy of modal estimates and simplifies the analysis steps The first example uses a Monte Carlo type siinulation model and the second analyzes field measured data from the western North American power system

Power System Dynamics and Stability

Abstract: 1 Introduction 2 Electromagnetic Transients 3 Synchronous Machine Modeling 4 Synchronous Machine Control Models 5 Single-Machine Dynamic Models 6 Multimachine Dynamic Models 7 Multimachine Simulation 8 Small-Signal Stability 9 Energy Function Methods Appendix A: Integral Manifolds for Model Bibliography Index

Thyristor-Based Facts Controllers for Electrical Transmission Systems

Abstract: 1. Introduction. 1.1 Background. 1.2 Electrical Transmission Networks. 1.3 Conventional Control Mechanisms. 1.4 Flexible ac Transmission Systems (FACTS). 1.5 Emerging Transmission Networks. 2. Reactor--Power Control in Electrical Power Transmission Systems. 2.1 Reacrive Power. 2.2 Uncompensated Transmission Lines. 2.3 Passive Compensation. 2.4 Summary. 3. Principles of Conventional Reactive--Power Compensators. 3.1 Introduction. 3.2 Synchronous Condensers. 3.3 The Saturated Reactor (SR). 3.4 The Thyristor--Controlled Reactor (TCR). 3.5 The Thyristor--Controlled Transformer (TCT). 3.6 The Fixed Capacitor--Thyristor--Controlled Reactor (FC--TCR). 3.7 The Mechanically Switched Capacitor--Thristor--Controlled Reactor (MSC--TCR). 3.8 The Thyristor--Switched capacitor and Reactor. 3.9 The Thyristor--Switched capacitor--Thyristor--Controlled Reactor (TSC--TCR). 3.10 A Comparison of Different SVCs. 3.11 Summary. 4. SVC Control Components and Models. 4.1 Introduction 4.2 Measurement Systems. 4.3 The Voltage Regulator. 4.4 Gate--Pulse Generation. 4.5 The Synchronizing System. 4.6 Additional Control and Protection Functions. 4.7 Modeling of SVC for Power--System Studies. 4.8 Summary. 5. Conceepts of SVC Voltage Control. 5.1 Introduction 5.2 Voltage Control. 5.3 Effect of Network Resonances on the Controller Response. 5.4 The 2nd Harmonic Interaction Between the SVC and ac Network. 5.5 Application of the SVC to Series--Compensated ac Systems. 5.6 3rd Harmonic Distortion. 5.7 Voltage--Controlled Design Studies. 5.8 Summary. 6. Applications. 6.1 Introduction. 6.2 Increase in Steady--State Power--Transfer Capacity. 6.3 Enhancement of Transient Stability. 6.4 Augmentation of Power--System Damping. 6.5 SVC Mitigation of Subsychronous Resonance (SSR). 6.6 Prevention of Voltage Instability. 6.7 Improvement of HVDC Link Performance. 6.8 Summary. 7. The Thyristor--Controlled SeriesCapacitor (TCSC). 7.1 Series Compensation. 7.2 The TCSC Controller. 7.3 Operation of the TCSC. 7.4 The TSSC. 7.5 Analysis of the TCSC. 7.6 Capability Characteristics. 7.7 Harmonic Performance. 7.8 Losses. 7.9 Response of the TCSC. 7.10 Modeling of the TCSC. 7.11 Summary. 8. TCSC Applications. 8.1 Introduction. 8.2 Open--Loop Control. 8.3 Closed--Loop Control. 8.4 Improvement of the System--Stability Limit. 8.5 Enhancement of System Damping. 8.6 Subsynchronous Resonanace (SSR) Mitigation. 8.7 Voltage--Collapse Prevention. 8.8 TCSC Installations. 8.9 Summary. 9. Coordination of FACTS Controllers. 9.1 Introduction 9.2 Controller Interactions. 9.3 SVC--SVC Interaction. 9.4 SVC--HVDC Interaction. 9.5 SVC--TCSC Interaction. 9.6 TCSC--TCSC Interaction. 9.7 Performance Criteria for Damping--Controller Design. 9.8 Coordination of Multiple Controllers Using Linear--Control Techniques. 9.9 Coordination of Multiple Controllers using Nonlinear--Control Techniques. 9.10 Summary. 10. Emerging FACTS Controllers. 10.1 Introduction. 10.2 The STATCOM. 10.3 THE SSSC. 10.4 The UPFC. 10.5 Comparative Evaluation of Different FACTS Controllers. 10.6 Future Direction of FACTS Technology. 10.7 Summary. Appendix A. Design of an SVC Voltage Regulator. A.1 Study System. A.2 Method of System Gain. A.3 Elgen Value Analysis. A.4 Simulator Studies. A.5 A Comparison of Physical Simulator results With Analytical and Digital Simulator Results Using Linearized Models. Appendix B. Transient--Stability Enhancement in a Midpoint SVC--Compensated SMIB System. Appendix C. Approximate Multimodal decomposition Method for the Design of FACTS Controllers. C.1 Introduction. C.2 Modal Analysis of the ith Swing Mode, C.3 Implications of Different Transfer Functions. C.4 Design of the Damping Controller. Appendix D. FACTS Terms and Definitions. Index.

WACS-Wide-Area Stability and Voltage Control System: R&D and Online Demonstration

Abstract: As background, we describe frequently used feedforward wide-area discontinuous power system stability controls. Then we describe online demonstration of a new response-based (feedback) Wide-Area stability and voltage Control System (WACS). The control system uses powerful discontinuous actions for power system stabilization. The control system comprises phasor measurements at many substations, fiber-optic communications, real-time deterministic computers, and transfer trip output signals to circuit breakers at many other substations and power plants. Finally, we describe future development of WACS. WACS is developed as a flexible platform to prevent blackouts and facilitate electrical commerce.

Modern Power Systems Analysis

Abstract: Mathematical Model and Solution of Electric Network.- Load Flow Analysis.- Stochastic Security Analysis of Electrical Power Systems.- Power Flow Analysis in Market Environment.- HVDC and FACTS.- Mathematical Model of Synchronous Generator and Load.- Power System Transient Stability Analysis.- Small-Signal Stability Analysis of Power Systems.

Performance comparison of three identification methods for the analysis of electromechanical oscillations

Abstract: This paper describes the results of a study to evaluate the performance of three identification methods for the study of low frequency electromechanical oscillations. The three identification methods considered are: the Steiglitz-McBride algorithm; the eigensystem realization algorithm; and the Prony method. The identification methods are used to identify low order linear systems of power systems modeled in standard transient stability programs. This is accomplished by processing the system response to a simple probing pulse. The frequency domain characteristics of several identified systems are compared using three power systems with lightly damped electromechanical modes.