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Conference Paper: Chemical reaction optimization for the optimal power flow problem

TitleChemical reaction optimization for the optimal power flow problem
Authors
KeywordsChemical reaction optimization
Metaheuristic
Optimal power flow
Power grid
Smart grid
Issue Date2012
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000284
Citation
The 2012 IEEE Congress on Evolutionary Computation (CEC 2012), Brisbane, Australia, 10-15 June 2012. In IEEE CEC Proceedings, 2012, p. 1-8 How to Cite?
AbstractThis paper presents an implementation of the Chemical Reaction Optimization (CRO) algorithm to solve the optimal power flow (OPF) problem in power systems with the objective of minimizing generation costs. Multiple constraints, such as the balance of the power, bus voltage magnitude limits, transmission line flow limits, transformer tap settings, etc., are considered. We adapt the CRO framework to the OPF problem by redesigning the elementary reaction operators. We perform simulations on the standard IEEE-14, -30, and -57 bus benchmark systems. We compare the perform of CRO with other reported evolutionary algorithms in the IEEE-30 test case. Simulation results show that CRO can obtain a solution with the lowest cost, when compared with other algorithms. To be more complete, we also give the average result for the IEEE-30 case, and the best and average results for the IEEE-14 and -57 test cases. The results given in this paper suggest that CRO is a better alternative for solving the OPF problem, as well as its variants for the future smart grid. © 2012 IEEE.
DescriptionIEEE World Congress on Computational Intelligence (WCCI 2012), Brisbane, Australia, 10-15 June 2012 hosted three conferences: the 2012 International Joint Conference on Neural Networks (IJCNN 2012), the 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2012), and the 2012 IEEE Congress on Evolutionary Computation (IEEE CEC 2012)
Persistent Identifierhttp://hdl.handle.net/10722/165307
ISBN

 

DC FieldValueLanguage
dc.contributor.authorSun, Yen_US
dc.contributor.authorLam, AYSen_US
dc.contributor.authorLi, VOKen_US
dc.contributor.authorXu, Jen_US
dc.contributor.authorYu, JJQen_US
dc.date.accessioned2012-09-20T08:16:53Z-
dc.date.available2012-09-20T08:16:53Z-
dc.date.issued2012en_US
dc.identifier.citationThe 2012 IEEE Congress on Evolutionary Computation (CEC 2012), Brisbane, Australia, 10-15 June 2012. In IEEE CEC Proceedings, 2012, p. 1-8en_US
dc.identifier.isbn978-1-4673-1509-8-
dc.identifier.urihttp://hdl.handle.net/10722/165307-
dc.descriptionIEEE World Congress on Computational Intelligence (WCCI 2012), Brisbane, Australia, 10-15 June 2012 hosted three conferences: the 2012 International Joint Conference on Neural Networks (IJCNN 2012), the 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2012), and the 2012 IEEE Congress on Evolutionary Computation (IEEE CEC 2012)-
dc.description.abstractThis paper presents an implementation of the Chemical Reaction Optimization (CRO) algorithm to solve the optimal power flow (OPF) problem in power systems with the objective of minimizing generation costs. Multiple constraints, such as the balance of the power, bus voltage magnitude limits, transmission line flow limits, transformer tap settings, etc., are considered. We adapt the CRO framework to the OPF problem by redesigning the elementary reaction operators. We perform simulations on the standard IEEE-14, -30, and -57 bus benchmark systems. We compare the perform of CRO with other reported evolutionary algorithms in the IEEE-30 test case. Simulation results show that CRO can obtain a solution with the lowest cost, when compared with other algorithms. To be more complete, we also give the average result for the IEEE-30 case, and the best and average results for the IEEE-14 and -57 test cases. The results given in this paper suggest that CRO is a better alternative for solving the OPF problem, as well as its variants for the future smart grid. © 2012 IEEE.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000284-
dc.relation.ispartofCongress on Evolutionary Computation Proceedingsen_US
dc.rightsCongress on Evolutionary Computation Proceedings. Copyright © IEEE.-
dc.rights©2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectChemical reaction optimization-
dc.subjectMetaheuristic-
dc.subjectOptimal power flow-
dc.subjectPower grid-
dc.subjectSmart grid-
dc.titleChemical reaction optimization for the optimal power flow problemen_US
dc.typeConference_Paperen_US
dc.identifier.emailSun, Y: sunyimik@hku.hken_US
dc.identifier.emailLam, AYS: albertlam@ieee.org-
dc.identifier.emailLi, VOK: vli@eee.hku.hk-
dc.identifier.emailXu, J: xujin@eee.hku.hk-
dc.identifier.emailYu, JJQ: jqyug@eee.hku.hk-
dc.identifier.authorityLi, VOK=rp00150en_US
dc.description.naturepublished_or_final_version-
dc.identifier.scopuseid_2-s2.0-84866850786-
dc.identifier.hkuros210469en_US
dc.identifier.spage1-
dc.identifier.epage8-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 130508-

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