Frontiers of Information Technology (2013)
Islamabad, Pakistan Pakistan
Dec. 16, 2013 to Dec. 18, 2013
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FIT.2013.25
This article presents, indirect adaptive NeuroFuzzy control techniques for SSSC to damp low frequency oscillations. The proposed control strategy optimizes the conventional Takagi-Sugeno-Kang (TSK) structure by inclusion of wavelets and Fourier series Neural Networks (NNs). The parameters of the controller are updated online using the current estimate of the plant model, based on the online sensitivity measure. Nonlinear time domain simulation results and different performance indices for Single Machine Infinite Bus (SMIB) and multi-machine test systems are used to validate the controller performance. A comparative analysis reveals that wavelets based control performs better in both the transient and steady-state regions for different operating conditions as compared to the controls based on TSK and Fourier series NNs.
Oscillators, Power system stability, Load flow, Artificial neural networks, Fourier series, Rotors, Damping,power system stability, SSSC, indirect adaptive control, wavelets, NeuroFuzzy, Fourier series
Rabiah Badar, Laiq Khan, "Neurofuzzy Based Fully Adaptive Indirect Controls for SSSC: A Comparative Analysis", Frontiers of Information Technology, vol. 00, no. , pp. 95-100, 2013, doi:10.1109/FIT.2013.25