基于自适应神经模糊小波的SSSC阻尼控制范式

R. Badar, L. Khan
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引用次数: 4

摘要

补充阻尼控制可以有效地应用于柔性交流输电系统(FACTS)控制器中,以抑制单机和多机电力系统中的低频振荡。如果不适当地抑制这些低频振荡,可能会导致系统的不稳定。本文提出了一种基于小波的自适应模糊神经网络(CAFNN)的自适应神经模糊辅助控制方法。该控制系统已成功应用于单机无限母线系统(SMIB)和多机电力系统的各种故障和运行工况。最后,通过对各种故障和运行条件的非线性时域仿真,将所提出的控制方法与CAFNN进行了比较。结果表明,与CAFNN相比,所提出的控制方法在局部和区域间振荡模式下都具有最佳的阻尼性能。
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Adaptive Neuro Fuzzy Wavelet Based SSSC Damping Control Paradigm
The supplementary damping control can be efficiently used for Flexible AC Transmission System (FACTS) controllers to damp the low frequency oscillations in single and multi-machine power systems. These low frequency oscillations may lead to the instability of the system if not damped out properly. This paper presents, wavelet based adaptive NeuroFuzzy supplementary control by incorporating wavelets in the structure of Conventional Adaptive Fuzzy NN (CAFNN) for SSSC. The proposed control system has successfully been applied to single machine infinite bus system (SMIB) and multi-machine power system for various faults and operating conditions. Finally, the proposed control technique is compared with CAFNN using nonlinear time domain simulations for various faults and operating conditions. The results reveal that the proposed control has optimal damping performance as compared to CAFNN for both local and inter-area modes of oscillation.
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