شماره ركورد كنفرانس :
1730
عنوان مقاله :
Damping of Inter-Area Oscillations by Self-Recurrent Wavelet Neural Adaptive Controlled SSSC
عنوان به زبان ديگر :
Damping of Inter-Area Oscillations by Self-Recurrent Wavelet Neural Adaptive Controlled SSSC
پديدآورندگان :
Alizadeh Mojtaba نويسنده , Ganjefar Soheil نويسنده , Farahani Mohsen نويسنده
كليدواژه :
Self-Recurren , SSSC , Self-Recurrent Wavelet Neural Network SRWNN , Discrete Lyapunov Stability Theorem , DLST , Static Synchronous Series Compensator SSSC , Inter-area oscillations damping
عنوان كنفرانس :
بيستمين كنفرانس مهندسي برق ايران
چكيده لاتين :
This article aims to propose a Self-Recurrent Wavelet Neural Adaptive Supplementary Controller (SRWNASC) design of Static Synchronous Series Compensator (SSSC) for inter-areaoscillations damping. The proposed approach employs the SRWNN as two distinct sub-networks namely; the SRWNNIdentifier(SRWNNI) and the SRWNN-Controller (SRWNNC), based on the indirect adaptive control theory. To guarantee the convergence of the proposed control scheme, the parameters ofboth the SRWNNI and the SRWNNC are updated online employing a stable Back-Propagation (BP) training algorithmwith Adaptive Learning Rates (ALRs) based on Discrete Lyapunov Stability Theorem (DLST). A two-machine two-areapower system is used to show the effectiveness of the proposed approach for damping the inter-area oscillations
شماره مدرك كنفرانس :
4460809