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Conference Paper: Genetic algorithms in power system small signal stability analysis

TitleGenetic algorithms in power system small signal stability analysis
Authors
Issue Date1998
Citation
Iee Conference Publication, 1998 n. 450, p. 342-347 How to Cite?
AbstractPower 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 the paper as different modifications of a general optimization problem, and each of them has multiple minima and maxima. The usual optimization procedures converge 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 the paper, we propose a new black box genetic technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima and derivatives which can not be expressed analytically.
Persistent Identifierhttp://hdl.handle.net/10722/169796
ISSN

 

DC FieldValueLanguage
dc.contributor.authorDong, Zhao Yangen_US
dc.contributor.authorMakarov, Yuri Ven_US
dc.contributor.authorHill, David Jen_US
dc.date.accessioned2012-10-25T04:55:39Z-
dc.date.available2012-10-25T04:55:39Z-
dc.date.issued1998en_US
dc.identifier.citationIee Conference Publication, 1998 n. 450, p. 342-347en_US
dc.identifier.issn0537-9989en_US
dc.identifier.urihttp://hdl.handle.net/10722/169796-
dc.description.abstractPower 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 the paper as different modifications of a general optimization problem, and each of them has multiple minima and maxima. The usual optimization procedures converge 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 the paper, we propose a new black box genetic technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima and derivatives which can not be expressed analytically.en_US
dc.languageengen_US
dc.relation.ispartofIEE Conference Publicationen_US
dc.titleGenetic algorithms in power system small signal stability analysisen_US
dc.typeConference_Paperen_US
dc.identifier.emailHill, David J:en_US
dc.identifier.authorityHill, David J=rp01669en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0031599429en_US
dc.identifier.issue450en_US
dc.identifier.spage342en_US
dc.identifier.epage347en_US
dc.identifier.scopusauthoridDong, Zhao Yang=7402274708en_US
dc.identifier.scopusauthoridMakarov, Yuri V=35461311800en_US
dc.identifier.scopusauthoridHill, David J=35398599500en_US

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