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논문 기본 정보

자료유형
학술저널
저자정보
Wei Yao (Huazhong University of Science and Technology) Jiakun Fang (Huazhong University of Science and Technology) Ping Zhao (Huazhong University of Science and Technology) Shilin Liu (Huazhong University of Science and Technology) Jinyu Wen (Huazhong University of Science and Technology) Shaorong Wang (Huazhong University of Science and Technology)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.8 No.2
발행연도
2013.3
수록면
252 - 261 (10page)

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초록· 키워드

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In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have the characteristics of the conventional PID, but adjust the parameters of PID controller online using identified Jacobian information from RBFNN. Hence, it has strong adaptability to the variation of the system operating condition. The effectiveness of the proposed controller is tested on a two-machine five-bus power system and a four-machine two-area power system under different operating conditions in comparison with the lead-lag damping controller tuned by evolutionary algorithm (EA). Simulation results show that the proposed damping controller achieves good robust performance for damping the low frequency oscillations under different operating conditions and is superior to the lead-lag damping controller tuned by EA.

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Abstract
1. Introduction
2. TCSC Current Injection Model
3. The Proposed Approach
4. Adaptive Controller Design for TCSC
5. Simulation Results: Two-Machine System
6. Simulation Results: Four-Machine System
7. Conclusion
Acknowledgements
Appendix
References

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UCI(KEPA) : I410-ECN-0101-2014-560-000290160