E. V. Larsen

Bio: E. V. Larsen is an academic researcher from General Electric. The author has contributed to research in topics: Stabilizer (chemistry) & Root locus. The author has an hindex of 5, co-authored 5 publications receiving 1408 citations.

Applying Power System Stabilizers Part I: General Concepts

Abstract: The general concepts associated with applying power system stabilizers utilizing shaft speed, ac bus frequency, and electrical power inputs are developed in this first part of a three-part paper. This lays the foundation for discussion of the tuning concepts and practical aspects of stabilizer application in Parts II and III. The characteristics of the "plant" through which the power system stabilizer must operate are discussed and the implications upon stabilizer tuning and performance are noted. A general approach for analyzing stabilizers utilizing an arbitrary input signal is described and applied to the frequency and electrical power input signals.

Applying Power System Stabilizers Part II: Performance Objectives and Tuning Concepts

Abstract: This part of a three-part paper deals first with the performance objectives of power system stabilizers in terms of the type of oscillations for which they are intended to provide damping, the operating conditions for which the requirement for stabilization is greatest, the need to accommodate multiple modes of oscillation, and the significance of interplant modes of oscillation. It next treats stabilizer tuning. General tuning guidelines are developed as well as variations required for different input signals. The operating conditions under which each type of stabilizer should be tuned are identified. The relationship between phase compensation tuning and root locus analysis is presented. Finally, the relative performance characteristics of the three types of stabilizers are examined for both small perturbations and large disturbances.

Applying Power System Stabilizers Part III: Practical Considerations

Abstract: The practical considerations associated with applying power system stabilizers are addressed in this final part of the paper. Procedures are described whereby the tuning concepts developed in Part II may be implemented in the field. An approach is described for determining the "plant" characteristics for which a stabilizer must compensate. Guidelines are presented for adjustment of stabilizer parameters, inclduing frequency-response, gain, and output limits. Techniques are described for verification of proper stabilizer set-up.

HVDC System Control for Damping of Subsynchronous Oscillations

Abstract: A method for designing a supplemental subsynchronous damping control (SSDC) for an HVDC transmission system is described. The SSDC eliminates torsional instabilities caused by interaction between conventional HVDC controls and turbine-generator rotor torsional modes of vibration. Results of digital simulation used in the design process are compared with measurements made on an HVDC simulator. Results of both digital simulations and HVDC simulator tests which demonstrate SSDC performance are shown. This research and development effort was sponsored by EPRI under RP1425-1.

HVDC system control for damping of subsynchronous oscillations

Abstract: A method for designing a supplemental subsynchronous damping control (SSDC) for an HVDC transmission system is described. The SSDC eliminates torsional instabilities caused by interaction between conventional HVDC controls and turbine-generator rotor torsional modes of vibration. Results of digital simulation used in the design process are compared with measurements made on an HVDC simulator. Results of both digital simulations and HVDC simulator tests which demonstrate SSDC performance are shown. This research and development effort was sponsored by EPRI under RP1425-1.

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.

Application of power system stabilizers for enhancement of overall system stability

Abstract: This paper provides a detailed account of analytical work carried out to determine the parameters of power system stabilizers (PSS) for the Darlington nuclear generating station presently under construction in eastern Ontario. The results presented are, however, of general interest and provide a comprehensive analysis of the effects of the different stabilizer parameters on the overall dynamic performance of the power system. They show how stabilizer settings may be selected so as to enhance the steady-state and transient stability of local plant modes as well as inter-area modes in large interconnected systems. In addition, it is shown that the selected parameters result in satisfactory performance during system islanding conditions, when large frequency excursions are experienced. Darlington GS, when completed by 1992, will comprise four 1100 MVA, 0.85 p.f., 1800 RPM turbine generators with "CANDU-PHW" reactors, moderated and cooled by heavy water. The station will be incorporated into the 500 kV network through three double-circuit lines. The units will be equipped with transformer-fed thyristor excitation systems and Delta-P-Omega type PSS [1, 2].

Optimal des'ign of Power System Stabilizers Using Particle Swarm Opt'imization

Abstract: In this paper, a novel evolutionary algorithm-based approach to optimal design of multimachine power system stabilizers (PSSs) is proposed. The proposed approach employs the particle swarm optimization (PSO) technique to search for optimal settings of PSS parameters. Two elgenvalue-based objective functions to enhance system damping of electromechanical modes are considered. The robustness of the proposed approach to the initial guess is demonstrated. The performance of the proposed PSO-based PSS (PSOPSS) under different disturbances, loading conditions, and system configurations is tested and examined for different multimachine power systems. Eigenvalue analysis and nonlinear simulation results show the effectiveness of the proposed PSOPSSs to damp out the local as well as the interarea modes of oscillations and work effectively over a wide range of loading conditions and system configurations. In addition, the potential and superiority of the proposed approach over the conventional approaches are demonstrated.

A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain

Abstract: Magnetic resonance (MR) brain section images are segmented and then synthetically colored to give visual representations of the original data with three approaches: the literal and approximate fuzzy c-means unsupervised clustering algorithms, and a supervised computational neural network. Initial clinical results are presented on normal volunteers and selected patients with brain tumors surrounded by edema. Supervised and unsupervised segmentation techniques provide broadly similar results. Unsupervised fuzzy algorithms were visually observed to show better segmentation when compared with raw image data for volunteer studies. For a more complex segmentation problem with tumor/edema or cerebrospinal fluid boundary, where the tissues have similar MR relaxation behavior, inconsistency in rating among experts was observed, with fuzz-c-means approaches being slightly preferred over feedforward cascade correlation results. Various facets of both approaches, such as supervised versus unsupervised learning, time complexity, and utility for the diagnostic process, are compared. >