Power system voltage small-disturbance stability studies based on the power flow equation

Guo-yun, Cao; Hill, David J.

doi:10.1049/iet-gtd.2010.0016

Cited by 12 publications

(2 citation statements)

References 12 publications

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“…Voltage stability critical state is related to saddle-node bifurcation (SNB) of the power flow equations [27]. The following transversality conditions can be used to characterize and detect SNB [28][29] ( , ) 0…”

Section: Voltage Stability Margin: Problem Formulation and Calculatiomentioning

confidence: 99%

Probabilistic Assessment of Voltage Stability Margin in Presence of Wind Speed Correlation

Li¹,

Cai

2013

Journal of Electrical Engineering and Technology

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-Probabilistic assessment of voltage stability margin (VSM) with existence of correlated wind speeds is investigated. Nataf transformation is adopted to establish wind speed correlation (WSC) model. Based on the saddle-node bifurcation transversality condition equations and Monte Carlo simulation technique, probability distribution of VSM is determined. With correlation coefficients range low to high value, the effect of WSC on VSM is studied. In addition, two risk indexes are proposed and the possible threat caused by WSC is evaluated from the viewpoint of risk analysis. Experimental results show that the presence of correlated wind speeds is harmful to safe and stable operation of a power system as far as voltage stability is concerned. The achievement of this paper gives a detailed elaboration about the influence of WSC on voltage stability and provides a potentially effective analytical tool for modern power system with large-scale wind power sources integration.

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Section: Voltage Stability Margin: Problem Formulation and Calculatiomentioning

confidence: 99%

Probabilistic Assessment of Voltage Stability Margin in Presence of Wind Speed Correlation

Li¹,

Cai

2013

Journal of Electrical Engineering and Technology

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“…Many researches have been conducted in this field, such as dynamic equivalents [1][2][3], model analysis [4,5] and identification [6,7], singular perturbation techniques [8], Hankel norm approximation [9], balanced realization approach [10], etc. There are already some effective theories and applications published on linear power system model reduction.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear power system model reduction based on empirical Gramians

Zhao

Xiaoming

Ren

2017

Journal of Electrical Engineering

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An effective nonlinear model reduction approach, empirical Gramians balanced reduction approach, is studied, to reduce the computation complexity in nonlinear power system model application. The realization procedure is: firstly, computing the empirical controllable and observable Gramians matrices of nonlinear power system model, secondly, by these two matrices, computing the balance transformation matrix to obtain the balanced system model of the original model, then, computing the controllable and observable matrices of the balanced system to obtain the diagonal Hankel singular matrix. Finally, deciding the lower-order subspace to obtain the reduced power system model. A 15-machine power system model is taken as an example to perform the reduction simulation analysis.K e y w o r d s: power system, nonlinear model reduction, empirical Gramians, balanced truncation

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Adverse Control Effects on Steady-State Voltage Stability in Wind Power Systems Based on Sensitivities of B and L Indices

Xue

Li³

et al. 2019

Proceedings of PURPLE MOUNTAIN FORUM 2019-International Forum on Smart Grid Protection and Control

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Power system voltage small-disturbance stability studies based on the power flow equation

Cited by 12 publications

References 12 publications

Probabilistic Assessment of Voltage Stability Margin in Presence of Wind Speed Correlation

Probabilistic Assessment of Voltage Stability Margin in Presence of Wind Speed Correlation

Nonlinear power system model reduction based on empirical Gramians

Adverse Control Effects on Steady-State Voltage Stability in Wind Power Systems Based on Sensitivities of B and L Indices

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