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- Publisher Website: 10.1109/CEC.2012.6253003
- Scopus: eid_2-s2.0-84866850786
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Conference Paper: Chemical reaction optimization for the optimal power flow problem
Title | Chemical reaction optimization for the optimal power flow problem |
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Authors | |
Keywords | Chemical reaction optimization Metaheuristic Optimal power flow Power grid Smart grid |
Issue Date | 2012 |
Publisher | IEEE. 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? |
Abstract | This 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. |
Description | IEEE 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 Identifier | http://hdl.handle.net/10722/165307 |
ISBN |
DC Field | Value | Language |
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dc.contributor.author | Sun, Y | en_US |
dc.contributor.author | Lam, AYS | en_US |
dc.contributor.author | Li, VOK | en_US |
dc.contributor.author | Xu, J | en_US |
dc.contributor.author | Yu, J | en_US |
dc.date.accessioned | 2012-09-20T08:16:53Z | - |
dc.date.available | 2012-09-20T08:16:53Z | - |
dc.date.issued | 2012 | en_US |
dc.identifier.citation | The 2012 IEEE Congress on Evolutionary Computation (CEC 2012), Brisbane, Australia, 10-15 June 2012. In IEEE CEC Proceedings, 2012, p. 1-8 | en_US |
dc.identifier.isbn | 978-1-4673-1509-8 | - |
dc.identifier.uri | http://hdl.handle.net/10722/165307 | - |
dc.description | IEEE 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.abstract | This 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.language | eng | en_US |
dc.publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000284 | - |
dc.relation.ispartof | IEEE Congress on Evolutionary Computation | en_US |
dc.subject | Chemical reaction optimization | - |
dc.subject | Metaheuristic | - |
dc.subject | Optimal power flow | - |
dc.subject | Power grid | - |
dc.subject | Smart grid | - |
dc.title | Chemical reaction optimization for the optimal power flow problem | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Sun, Y: sunyimik@hku.hk | en_US |
dc.identifier.email | Lam, AYS: ayslam@eee.hku.hk | - |
dc.identifier.email | Li, VOK: vli@eee.hku.hk | - |
dc.identifier.email | Xu, J: xujin@eee.hku.hk | - |
dc.identifier.email | Yu, JJQ: jqyug@eee.hku.hk | - |
dc.identifier.authority | Lam, AYS=rp02083 | en_US |
dc.identifier.authority | Li, VOK=rp00150 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/CEC.2012.6253003 | - |
dc.identifier.scopus | eid_2-s2.0-84866850786 | - |
dc.identifier.hkuros | 210469 | en_US |
dc.identifier.hkuros | 261767 | - |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 8 | - |
dc.publisher.place | United States | - |
dc.customcontrol.immutable | sml 130508 ; sml 160909 - merged | - |