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Conference Paper: A heuristic to generate initial feasible solutions for the Unit Commitment problem

TitleA heuristic to generate initial feasible solutions for the Unit Commitment problem
Authors
KeywordsChemical reaction optimization
Heuristic
Unit commitment
Power grid
Issue Date2014
PublisherIEEE.
Citation
The 2014 International Joint Conference on Neural Networks (IJCNN 2014), Beijing, China, 6-11 July 2014. In Conference Proceedings, 2014, p. 913-920 How to Cite?
AbstractThis paper presents a heuristic approach to generate initial feasible solutions for the Unit Commitment (UC) problem in electric power generation. The Chemical Reaction Optimization (CRO) algorithm is implemented to solve this problem. Multiple generator constraints and system constraints are considered. We also program the binary PSO and the Elite PSO (EPSO) for comparison. The proposed heuristic approach is combined with the three optimization algorithms to form H-CRO, H-PSO and H-EPSO. We test the performance of all algorithms on the standard 10-unit system. Simulation results show that the heuristic can improve the performance and CRO provides better convergence than the two PSO algorithms. H-CRO is also tested on a 20-unit and 100-unit system to show its capability. The results provided in this paper suggest that the proposed heuristic approach is a better alternative for solving the UC problem. CRO also has its advantage in optimizing UC problems. © 2014 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/219764
ISBN

 

DC FieldValueLanguage
dc.contributor.authorSun, Y-
dc.contributor.authorLam, AYS-
dc.contributor.authorLi, VOK-
dc.date.accessioned2015-09-23T02:57:54Z-
dc.date.available2015-09-23T02:57:54Z-
dc.date.issued2014-
dc.identifier.citationThe 2014 International Joint Conference on Neural Networks (IJCNN 2014), Beijing, China, 6-11 July 2014. In Conference Proceedings, 2014, p. 913-920-
dc.identifier.isbn978-1-4799-1484-5-
dc.identifier.urihttp://hdl.handle.net/10722/219764-
dc.description.abstractThis paper presents a heuristic approach to generate initial feasible solutions for the Unit Commitment (UC) problem in electric power generation. The Chemical Reaction Optimization (CRO) algorithm is implemented to solve this problem. Multiple generator constraints and system constraints are considered. We also program the binary PSO and the Elite PSO (EPSO) for comparison. The proposed heuristic approach is combined with the three optimization algorithms to form H-CRO, H-PSO and H-EPSO. We test the performance of all algorithms on the standard 10-unit system. Simulation results show that the heuristic can improve the performance and CRO provides better convergence than the two PSO algorithms. H-CRO is also tested on a 20-unit and 100-unit system to show its capability. The results provided in this paper suggest that the proposed heuristic approach is a better alternative for solving the UC problem. CRO also has its advantage in optimizing UC problems. © 2014 IEEE.-
dc.languageeng-
dc.publisherIEEE.-
dc.relation.ispartofInternational Joint Conference on Neural Networks, IJCNN 2014-
dc.rightsInternational Joint Conference on Neural Networks, IJCNN 2014. Copyright © IEEE.-
dc.rights©2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectChemical reaction optimization-
dc.subjectHeuristic-
dc.subjectUnit commitment-
dc.subjectPower grid-
dc.titleA heuristic to generate initial feasible solutions for the Unit Commitment problem-
dc.typeConference_Paper-
dc.identifier.emailSun, Y: sunyimik@hku.hk-
dc.identifier.emailLam, AYS: ayslam@eee.hku.hk-
dc.identifier.emailLi, VOK: vli@eee.hku.hk-
dc.identifier.authorityLam, AYS=rp02083-
dc.identifier.authorityLi, VOK=rp00150-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1109/IJCNN.2014.6889548-
dc.identifier.scopuseid_2-s2.0-84908476585-
dc.identifier.hkuros254220-
dc.identifier.spage913-
dc.identifier.epage920-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 151103-

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