46 resultados para Small-signal stability

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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While load flow conditions vary with different loads, the small-signal stability of the entire system is closely related with to the locations, capacities and models of loads. In this paper, load impacts with different capacities and models on the small-signal stability are analysed. In the real large-scale power system case, the load sensitivity which denotes the sensitivity of the eigenvalue with respect to the load active power is introduced and applied to rank the loads. The loads with high sensitivity are also considered.

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This paper proposes a method to assess the small signal stability of a power system network by selective determination of the modal eigenvalues. This uses an accelerating polynomial transform, designed using approximate eigenvalues
obtained from a wavelet approximation. Application to the IEEE 14 bus network model produced computational savings of 20%,over the QR algorithm.

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The small signal stability of interconnected power systems is one of the important aspects that need to be investigated since the oscillations caused by this kind of instability have caused many incidents. With the increasing penetration of wind power in the power system, particularly doubly fed induction generator (DFIG), the impact on the power system small signal stability performance should be fully investigated. Because the DFIG wind turbine integration is through a fast action converter and associated control, it does not inherently participate in the electromechanical small signal oscillation. However, it influences the small signal stability by impacting active power flow paths in the network and replacing synchronous generators that have power system stabilizer (PSS). In this paper, the IEEE 39 bus test system has been used in the analysis. Furthermore, four study cases and several operation scenarios have been conducted and analysed. The selective eigenvalue Arnoldi/lanczos's method is used to obtain the system eigenvalue in the range of frequency from 0.2 Hz to 2 Hz which is related to electromechanical oscillations. Results show that the integration of DFIG wind turbines in a system during several study cases and operation scenarios give different influence on small signal stability performance.

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This paper presents the practical use of Prony Analysis to identify small signal oscillation mode parameters from simulated and actual phasor measurement unit (PMU) ringdown data. A well-known two-area four-machine power system was considered as a study case while the latest PMU ringdown data were collected from a double circuit 275 kV main interconnector on the Irish power system. The eigenvalue analysis and power spectral density were also conducted for the purpose of comparison. The capability of Prony Analysis to identify the mode parameters from three different types of simulated PMU ringdown data has been shown successfully. Furthermore, the results indicate that the Irish power system has dominant frequency modes at different frequencies. However, each mode has good system damping.

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An energy storage system (ESS) installed in a power system can effectively damp power system oscillations through controlling exchange of either active or reactive power between the ESS and power system. This paper investigates the robustness of damping control implemented by the ESS to the variations of power system operating conditions. It proposes a new analytical method based on the well-known equal-area criterion and small-signal stability analysis. By using the proposed method, it is concluded in the paper that damping control implemented by the ESS through controlling its active power exchange with the power system is robust to the changes of power system operating conditions. While if the ESS damping control is realized by controlling its reactive power exchange with the power system, effectiveness of damping control changes with variations of power system operating condition. In the paper, an example power system installed with a battery ESS (BESS) is presented. Simulation results confirm the analytical conclusions made in the paper about the robustness of ESS damping control. Laboratory experiment of a physical power system installed with a 35kJ/7kW SMES (Superconducting Magnetic Energy Storage) was carried out to evaluate theoretical study. Results are given in the paper, which demonstrate that effectiveness of SMES damping control realized through regulating active power is robust to changes of load conditions of the physical power system.

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This paper investigates the use of plug-in parking lots (SmartPark) as integral energy storage to improve small-signal stability using plug-in electric vehicles (PEV). The paper establishes the Phillips-Heffron model of a power system for a SmartPark solution. Based on this model, SmartPark-based stabilisers have been designed based using phase compensation to improve power system oscillation stability. The effectiveness of stabilisation superimposed on the active and reactive power regulators is verified by simulations obtained from a multi-machine power system model with SmartPark and a large-scale wind farm inclusion.

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A grid-connected DFIG for wind power generation can affect power system small-signal angular stability in two ways: by changing the system load flow condition and dynamically interacting with synchronous generators (SGs). This paper presents the application of conventional method of damping torque analysis (DTA) to examine the effect of DFIG’s dynamic interactions with SGs on the small-signal angular stability. It shows that the effect is due to the dynamic variation of power exchange between the DFIG and power system and can be estimated approximately by the DTA. Consequently, if the DFIG is modelled as a constant power source when the effect of zero dynamic interactions is assumed, the impact of change of load flow brought about by the DFIG can be determined. Thus the total effect of DFIG can be estimated from the result of DTA added on that of constant power source model. Applications of the DTA method proposed in the paper are discussed. An example of multi-machine power systems with grid-connected DFIGs are presented to demonstrate and validate the DTA method proposed and conclusions obtained in the paper.

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This paper gives the first experimental characterisation of the phase noise response of the recently introduced Inverse Class E topology when operated as an amplifier and then as an oscillator. The results indicate that in amplifier and oscillator modes of operation conversion efficiencies of 64%, and 42% respectively are available, and that the excess PM noise added as a consequence of saturated Class E operation results in about a 10 dB increase in PM over that expected from a small-signal Class A amplifier operating at much lower efficiency. Inverse Class E phase transfer dependence on device drain bias and flicker noise are presented in order to show, respectively, that the Inverse Class E amplifier and oscillator follow the trends predicted by conventional phase noise theory. © 2007 EuMA.

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The losses within the substrate of an RF IC can have significant effect on performance in a mixed signal application. in order to model substrate coupling accurately, it is represented by an RC network to account for both resistive and dielectric losses at high frequency (> 1 GHz). A small-signal equivalent circuit model of an RF IC inclusive of substrate parasitic effect is analysed in terms of its y-parameters and an extraction procedure for substrate parameters has been developed. By coupling the extracted substrate parameters along with extrinsic resistances associated with gate, source and drain, a standard BSIM3 model has been extended for RF applications. The new model exhibits a significant improvement in prediction of output reflection coefficient S-22 in the frequency range from 1 to 10 GHz in device mode of operation and for a low noise amplifier (LNA) at 2.4 GHz. Copyright (C) 2006 John Wiley & Sons, Ltd.

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An analytical approach for CMOS parameter extraction which includes the effect of parasitic resistance is presented. The method is based on small-signal equivalent circuit valid in all region of operation to uniquely extract extrinsic resistances, which can be used to extend the industry standard BSIM3v3 MOSFET model for radio frequency applications. The verification of the model was carried out through frequency domain measurements of S-parameters and direct time domain measurement at 2.4 GHz in a large signal non-linear mode of operation. (C) 2003 Elsevier Ltd. All rights reserved.

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A similar to 3 ps travelling wave chirped pulse amplified pulse at 6 x 10(14) W cm(-2) superimposed on similar to 300 ps background pulses is shown to be an efficient method to pump transient collisional excitation X-ray lasers in both Ni-like and Ne-like ions. Measurements of X-ray laser output as a function of plasma length are fitted with results of an amplified spontaneous emission model of the laser output taking account of travelling wave pumping effects. A small signal gain coefficient similar to 42 cm(-1) and a effective gain length product of similar to 18 are measured for the Ni-like Sn laser at 120 Angstrom. Simulations from a hydrodynamic and atomic physics code (EHYBRID) coupled to a ray trace code show that a spatially averaged small signal gain similar to 65 cm(-1) can be obtained in Ne-like Ge provided the optimum pumping pulse arrangement is used. (C) 1999 Elsevier Science B.V. All rights reserved.

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Driven by a double 75 ps pulse with 2.2 ns separation, saturated operation of nickel-like Ag, In, Sn, and Sm X-ray lasers have been demonstrated with only 75 J drive energy on target. The variation of X-ray laser output with target length is found to fit well to a simple model for an amplified spontaneous emission (ASE) laser including saturation. Small signal gains of similar to 10 cm(-1), effective gain length products of similar to 18, and saturation irradiance of (1-5)x 10(10) W/cm(2) are measured for these lasers using a fitting procedure. (C) 1998 Elsevier Science B.V. All rights reserved.