Analysis of small signal stability margins using genetic optimization

Dong, ZY, Makarov, YV and Hill, DJ (1998) Analysis of small signal stability margins using genetic optimization. Electric Power Systems Research, 46 3: 195-204. doi:10.1016/S0378-7796(98)00009-1

Author Dong, ZY
Makarov, YV
Hill, DJ
Title Analysis of small signal stability margins using genetic optimization
Journal name Electric Power Systems Research   Check publisher's open access policy
ISSN 0378-7796
Publication date 1998
Sub-type Article (original research)
DOI 10.1016/S0378-7796(98)00009-1
Volume 46
Issue 3
Start page 195
End page 204
Total pages 10
Language eng
Abstract Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.
Keyword Engineering, Electrical & Electronic
Genetic Algorithms
Power System Security
Saddle Node Bifurcation
Voltage Collapse
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 14 times in Thomson Reuters Web of Science Article | Citations
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Created: Mon, 13 Aug 2007, 10:43:03 EST