Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm
Considering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/939326 |
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| _version_ | 1832558168073306112 |
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| author | Feifei Dong Dichen Liu Jun Wu Bingcheng Cen Haolei Wang Chunli Song Lina Ke |
| author_facet | Feifei Dong Dichen Liu Jun Wu Bingcheng Cen Haolei Wang Chunli Song Lina Ke |
| author_sort | Feifei Dong |
| collection | DOAJ |
| description | Considering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into an improved biogeography-based optimization (IBBO) algorithm in order to design an optimal subsynchronous damping controller based on the mechanism of suppressing SSR by static var compensator (SVC). The effectiveness of the improved controller is verified by eigenvalue analysis and electromagnetic simulations. The simulation results of Jinjie plant indicate that the subsynchronous damping controller optimized by the IBBO algorithm can remarkably improve the damping of torsional modes and thus effectively depress SSR, and ensure the safety and stability of units and power grid operation. Moreover, the IBBO algorithm has the merits of a faster searching speed and higher searching accuracy in seeking the optimal control parameters over traditional algorithms, such as BBO algorithm, PSO algorithm, and GA algorithm. |
| format | Article |
| id | doaj-art-3e81affed7734c73b605248013433359 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-3e81affed7734c73b6052480134333592025-02-03T01:33:05ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/939326939326Design of SVC Controller Based on Improved Biogeography-Based Optimization AlgorithmFeifei Dong0Dichen Liu1Jun Wu2Bingcheng Cen3Haolei Wang4Chunli Song5Lina Ke6School of Electric Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Electric Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Electric Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Electric Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Electric Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Electric Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Electric Engineering, Wuhan University, Wuhan 430072, ChinaConsidering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into an improved biogeography-based optimization (IBBO) algorithm in order to design an optimal subsynchronous damping controller based on the mechanism of suppressing SSR by static var compensator (SVC). The effectiveness of the improved controller is verified by eigenvalue analysis and electromagnetic simulations. The simulation results of Jinjie plant indicate that the subsynchronous damping controller optimized by the IBBO algorithm can remarkably improve the damping of torsional modes and thus effectively depress SSR, and ensure the safety and stability of units and power grid operation. Moreover, the IBBO algorithm has the merits of a faster searching speed and higher searching accuracy in seeking the optimal control parameters over traditional algorithms, such as BBO algorithm, PSO algorithm, and GA algorithm.http://dx.doi.org/10.1155/2014/939326 |
| spellingShingle | Feifei Dong Dichen Liu Jun Wu Bingcheng Cen Haolei Wang Chunli Song Lina Ke Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm Journal of Applied Mathematics |
| title | Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm |
| title_full | Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm |
| title_fullStr | Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm |
| title_full_unstemmed | Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm |
| title_short | Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm |
| title_sort | design of svc controller based on improved biogeography based optimization algorithm |
| url | http://dx.doi.org/10.1155/2014/939326 |
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