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Article: Analysis of small signal stability margins using genetic optimization
Title | Analysis of small signal stability margins using genetic optimization |
---|---|
Authors | |
Keywords | Bifurcations Genetic Algorithms Power System Security Stability |
Issue Date | 1998 |
Publisher | Elsevier SA. The Journal's web site is located at http://www.elsevier.com/locate/epsr |
Citation | Electric Power Systems Research, 1998, v. 46 n. 3, p. 195-204 How to Cite? |
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. © 1998 Elsevier Science S.A. All rights reserved. |
Persistent Identifier | http://hdl.handle.net/10722/169662 |
ISSN | 2023 Impact Factor: 3.3 2023 SCImago Journal Rankings: 1.029 |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Dong, ZY | en_US |
dc.contributor.author | Makarov, YV | en_US |
dc.contributor.author | Hill, DJ | en_US |
dc.date.accessioned | 2012-10-25T04:54:04Z | - |
dc.date.available | 2012-10-25T04:54:04Z | - |
dc.date.issued | 1998 | en_US |
dc.identifier.citation | Electric Power Systems Research, 1998, v. 46 n. 3, p. 195-204 | en_US |
dc.identifier.issn | 0378-7796 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/169662 | - |
dc.description.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. © 1998 Elsevier Science S.A. All rights reserved. | en_US |
dc.language | eng | en_US |
dc.publisher | Elsevier SA. The Journal's web site is located at http://www.elsevier.com/locate/epsr | en_US |
dc.relation.ispartof | Electric Power Systems Research | en_US |
dc.subject | Bifurcations | en_US |
dc.subject | Genetic Algorithms | en_US |
dc.subject | Power System Security | en_US |
dc.subject | Stability | en_US |
dc.title | Analysis of small signal stability margins using genetic optimization | en_US |
dc.type | Article | en_US |
dc.identifier.email | Hill, DJ: | en_US |
dc.identifier.authority | Hill, DJ=rp01669 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.scopus | eid_2-s2.0-0032157393 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-0032157393&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 46 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.spage | 195 | en_US |
dc.identifier.epage | 204 | en_US |
dc.publisher.place | Switzerland | en_US |
dc.identifier.scopusauthorid | Dong, ZY=7402274708 | en_US |
dc.identifier.scopusauthorid | Makarov, YV=35461311800 | en_US |
dc.identifier.scopusauthorid | Hill, DJ=35398599500 | en_US |
dc.identifier.issnl | 0378-7796 | - |