Abstract—In this paper, a new variable fuzzy control algorithm is proposed for thyristor-controlled series capacitor (TCSC) to improve power system dynamic performance. Rules of adaptive neuron fuzzy inference system (ANFIS) devise this fuzzy controller for TCSC in power system. ANFIS uses a hybrid learning algorithm to identify the membership function parameters of Sugeno-type fuzzy inference system. Consequences of this control trend are compared with PI controller and it is shown by using fuzzy controller the system has more stable power flow and less power oscillations. Simulation results signify power stability improvement of two-area power system by using fuzzy controller in TCSC than traditional PI controller.
Index Terms—Fuzzy controller, PI controller, power stability, TCSC.
A. Zare, M. Nayeripour, and Taher Niknam are with the Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran (e-mail: amrzare@gmail.com, nayeri@sutech. ac.ir, niknam@sutech. ac. ir).
Xiaoning Kang and Mostafa Kheshti are with School of Electrical Engineering, Xi’an Jiaotong University, Xi’an, China.
Cite: Amir Zare, Majid Nayeripour, Xiaoning Kang, Mostafa Kheshti, and Taher Niknam, "Fuzzy Controller Design of TCSC with ANFIS to Improve the Dynamic Stability of Power System," International Journal of Engineering and Technology vol. 4, no. 3, pp. 248-252, 2012.
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