(1990). ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY. Electric Machines & Power Systems: Vol. 18, No. 2, pp. 209-210.

Energy function analysis for power system stability

An analytical approach for dg allocation in primary distribution network

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.

Thyristor-Based Facts Controllers for Electrical Transmission Systems

A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems

As wind energy reaches higher penetration levels, there is a greater need to manage intermittency associated with the individual wind turbine generators. This paper considers the integration of a short-term energy storage device in a doubly fed induction generator design in order to smooth the fast wind-induced power variations. This storage device can also be used to reinforce the dc bus during transients, thereby enhancing its low-voltage ride through (LVRT) capability. The topology is evaluated in terms of its ability to improve the performance both during normal operation and during transients. Results show that when storage is sized based upon the LVRT requirement, it can effectively damp short-term power oscillations, and it provides superior transient performance when compared with conventional topologies

Supercapacitor Energy Storage for Wind Energy Applications

Optimal distributed generation allocation for reliability, losses, and voltage improvement

This paper presents a method that simultaneously tune multiple power system damping controllers using genetic algorithms (GAs). Damping controller structures are assumed to be fixed consisting basically of lead-lag filters. The tuning method takes robustness into consideration as it guarantees system stabilization over a prespecified set of operating conditions. Modified GA operators are used in the simultaneous optimization of both phase compensations and gain settings for the stabilizers. The method is applied for global PSS tuning to the well-known New England system and to the coordinated tuning of 22 PSSs in a 1762-bus modified equivalent South-Southeastern Brazilian system.

Simultaneous tuning of power system damping controllers using genetic algorithms

The need for higher frequency in state estimation execution covering larger supervised networks has led to the investigation of faster and numerically more stable state estimation algorithms. However, technical developments in distributed Energy Management Systems, based on fast data communication networks, open up the possibility of parallel or distributed state estimation implementation. In this paper, this possibility is exploited to derive a solution methodology based on conventional state estimation algorithms and a coupling constraints optimization technique. Numerical experiments show suitable performance of the proposed method with regard to estimation accuracy, convergence robustness and computational efficiency. The results of these experiments also indicate the decoupled nature of the state estimation problem. >

/pdf/parallel-and-distributed-state-estimation-4x1rvlyrwh.pdf

Parallel and distributed state estimation

This work presents a methodology for evaluating the impact of DG units installation on electric losses, reliability and voltage profile of distribution networks. The losses and voltage profile evaluation is based on a power flow method with the representation of generators as PV buses. The reliability indices evaluation is based on analytic methods modified to handle multiple generations. The methodology may be used to evaluate the influence of the local of installation and the capacity of DG on these system performance characteristics for different generation expansion planning alternatives. The results obtained with the proposed methodology for systems extracted from the literature demonstrates its applicability.

Impact of distributed generation allocation and sizing on reliability, losses and voltage profile

This paper presents a computer model for the probabilistic representation of wind farms generation for reliability studies, which can provide an annual estimation of energy production and calculate several performance indexes. The model combines the stochastic characteristics of wind speed with the operational information of the turbines, such as the failure and repair rates, representing the wind farm by a Markov process. The simulations are made with real time series of wind speed of several Brazilian regions and actual turbine models. The influence of some wind farm and installation site characteristics on the results are evaluated, such as the wind speed statistical clustering technique, the number and type of the turbines, and the failure and repair rates. The results obtained reproduce successfully the behavior of the components considered in the model

Djalma M. Falcão

Papers

Optimal distributed generation allocation for reliability, losses, and voltage improvement

Simultaneous tuning of power system damping controllers using genetic algorithms

Parallel and distributed state estimation

Impact of distributed generation allocation and sizing on reliability, losses and voltage profile

Probabilistic Wind Farms Generation Model for Reliability Studies Applied to Brazilian Sites