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Article: Nonlinear predictive control scheme with immune optimization for voltage security control of power system
Title | Nonlinear predictive control scheme with immune optimization for voltage security control of power system |
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Authors | |
Keywords | Immune Algorithm Model Predictive Control Nonlinear System Power System Control Voltage Security Control |
Issue Date | 2004 |
Citation | Dianli Xitong Zidonghua/Automation Of Electric Power Systems, 2004, v. 28 n. 16, p. 25-31 How to Cite? |
Abstract | An immune algorithm based nonlinear predictive control scheme is proposed to solve power system voltage security control problems. A nonlinear differential-algebraic model is used to predict system behavior. A gradational targeting method is developed to decompose global horizon control targets into sub-objectives in receding prediction intervals via Pareto-type weighting functions. A novel immune algorithm is presented, using a multiple gene chain structure of antibodies to represent the solution candidates of the complicated optimization problem. A pattern recognition technique is employed to extract gene patterns of better antibodies. Similar antigen patterns are identified via learning, and memorized to create a better initial guess of solutions in order to accelerate the convergence of the optimal searching procedure. System performance comparative results are reported based on the emergency voltage control of a six-bus example power system. The results indicate the promising application potential of the method. |
Persistent Identifier | http://hdl.handle.net/10722/169722 |
ISSN | 2023 SCImago Journal Rankings: 1.171 |
References |
DC Field | Value | Language |
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dc.contributor.author | Li, Y | en_US |
dc.contributor.author | Hill, DJ | en_US |
dc.contributor.author | Wu, T | en_US |
dc.date.accessioned | 2012-10-25T04:54:25Z | - |
dc.date.available | 2012-10-25T04:54:25Z | - |
dc.date.issued | 2004 | en_US |
dc.identifier.citation | Dianli Xitong Zidonghua/Automation Of Electric Power Systems, 2004, v. 28 n. 16, p. 25-31 | en_US |
dc.identifier.issn | 1000-1026 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/169722 | - |
dc.description.abstract | An immune algorithm based nonlinear predictive control scheme is proposed to solve power system voltage security control problems. A nonlinear differential-algebraic model is used to predict system behavior. A gradational targeting method is developed to decompose global horizon control targets into sub-objectives in receding prediction intervals via Pareto-type weighting functions. A novel immune algorithm is presented, using a multiple gene chain structure of antibodies to represent the solution candidates of the complicated optimization problem. A pattern recognition technique is employed to extract gene patterns of better antibodies. Similar antigen patterns are identified via learning, and memorized to create a better initial guess of solutions in order to accelerate the convergence of the optimal searching procedure. System performance comparative results are reported based on the emergency voltage control of a six-bus example power system. The results indicate the promising application potential of the method. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Dianli Xitong Zidonghua/Automation of Electric Power Systems | en_US |
dc.subject | Immune Algorithm | en_US |
dc.subject | Model Predictive Control | en_US |
dc.subject | Nonlinear System | en_US |
dc.subject | Power System Control | en_US |
dc.subject | Voltage Security Control | en_US |
dc.title | Nonlinear predictive control scheme with immune optimization for voltage security control of power system | 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-s2.0-6944233590 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-6944233590&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 28 | en_US |
dc.identifier.issue | 16 | en_US |
dc.identifier.spage | 25 | en_US |
dc.identifier.epage | 31 | en_US |
dc.publisher.place | China | en_US |
dc.identifier.scopusauthorid | Li, Y=25925968000 | en_US |
dc.identifier.scopusauthorid | Hill, DJ=35398599500 | en_US |
dc.identifier.scopusauthorid | Wu, T=7404815480 | en_US |
dc.identifier.issnl | 1000-1026 | - |