Robust Design of a TCSC Supplementary Controller to Damp Inter-Area Oscillations

Kuiava, Rôman; Ramos, Rodrigo A.; Bretas, N.G.

doi:10.1109/pes.2007.385579

Cited by 6 publications

(3 citation statements)

References 22 publications

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“…7, the nonlinear adaptive TCSC controller uses the of the rotor speed deviation 12 ω between generator G1 and G2 as its input signal. This choice is based on system small-signal analysis results, where the rotor speed signal presents a better observability of the low frequency mode than other signal, for the configuration and operating conditions considered in the tests.…”

Section: Fig 6 Tcsc Nonlinear Damping Controller Based On Rbfnnmentioning

confidence: 99%

“…In dynamic application of the TCSC, various control techniques have been proposed for damping power oscillations to improve the system dynamic response [10][11][12][13][14][15][16][17][18][19]. Some evolutionary algorithms (EA) have been used optimal tuning of the TCSC based damping controller in order to enhance the damping of the power system low frequency oscillations in Ref.…”

Section: Introductionmentioning

confidence: 99%

“…To overcome this issue, many robust control theories have been proposed to improve the robustness of the TCSC based damping controller under variations of operation conditions and model uncertainties in Ref. [12][13][14][15][16]. However, most of them have high-order controller as high as the open-loop plant which are not preferred in the industry practice.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

TCSC Nonlinear Adaptive Damping Controller Design Based on RBF Neural Network to Enhance Power System Stability

Yao¹,

Zhao²,

Liu³

et al. 2013

Journal of Electrical Engineering and Technology

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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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Section: Fig 6 Tcsc Nonlinear Damping Controller Based On Rbfnnmentioning

confidence: 99%