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Thyristor control series capacitor ANFIS controller for damping oscillations

机译:晶闸管控制串联电容器ANFIS控制器,用于阻尼振荡

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摘要

This study applies Adaptive Neuro Fuzzy Inference System (ANFIS)-based TCSC controller for damping oscillations. ANFIS which tunes the fuzzy inference system with a back propagation algorithm based on collection of input-output data makes fuzzy system to learn ANFIS controller is designed to damp out the low frequency local and inter-area oscillations of the Multimachine power system. Direct inverse control techniques are used in the design-of TCSC ANFIS controller which is derived directly from neural networks counterpart’s methodologies of the power system and the controller network to provide optimal damping. By applying this controller to the TCSC devices the damping of inter-area modes of oscillations in a multi-machine power system is handled properly. The effectiveness of the proposed TCSC ANFIS controller is demonstrated on two area four machine power system (Kundur system) which has provided a comprehensive evaluation of the learning control performance. Finally, several fault and load disturbance simulation results are presented to stress the effectiveness of the proposed TCSC controller in a multimachine power system and show that the proposed intelligent controls improve the dynamic performance of the TCSC devices and the associated power network
机译:本研究将基于自适应神经模糊推理系统(ANFIS)的TCSC控制器用于阻尼振荡。 ANFIS通过基于输入-输出数据的收集的反向传播算法对模糊推理系统进行调整,使得模糊系统学习ANFIS控制器的设计旨在抑制多机电力系统的低频局部和区域间振荡。 TCSC ANFIS控制器的设计中使用了直接逆控制技术,该技术直接从神经网络对等方的电力系统方法和控制器网络派生而来,以提供最佳的阻尼。通过将此控制器应用于TCSC设备,可以正确处理多机电源系统中区域间振荡模式的阻尼。提出的TCSC ANFIS控制器的有效性在两区四机动力系统(Kundur系统)上得到了证明,该系统对学习控制性能进行了全面评估。最后,给出了一些故障和负载扰动仿真结果,以强调所提出的TCSC控制器在多机电力系统中的有效性,并表明所提出的智能控制提高了TCSC设备和相关电网的动态性能。

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