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首页> 外文期刊>IEE proceedings. Part C >Damping of power system oscillations using adaptive thyristor-controlled series compensators tuned by artificial neural networks
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Damping of power system oscillations using adaptive thyristor-controlled series compensators tuned by artificial neural networks

机译:利用人工神经网络调整的自适应晶闸管控制串联补偿器抑制电力系统振荡

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摘要

A proportional-integral (PI) controller is designed for thyristor-controlled series compensators (TCSCs) to improve the damping of power system oscillations. To maintain a good damping characteristic over a wide range of operating conditions, the gains of the PI controller are adapted in real time, based on online measured transmission line loadings (real and reactive power flows). To speed up the online gain adaptation process, an artificial neural network which is capable of performing complicated computations in a parallel, distributed manner is designed. A major feature of the proposed adaptive PI controller is that only physically measurable variables (real and reactive power flows over the transmission line) are employed as inputs to the adaptive controller. To demonstrate the effectiveness of the proposed adaptive TCSC controller, computer simulations are performed on a power system under disturbance conditions. It is concluded from the simulation results that the proposed adaptive TCSC controller can yield satisfactory dynamic responses over a wide range of operating conditions. Low-frequency oscillations in the frequency range 0.3-2Hz have been effectively damped by the proposed compensators.
机译:比例积分(PI)控制器设计用于晶闸管控制的串联补偿器(TCSC),以改善电力系统振荡的阻尼。为了在宽范围的工作条件下保持良好的阻尼特性,PI控制器的增益会根据在线测量的传输线负载(有功和无功功率)实时调整。为了加快在线增益自适应过程,设计了一种能够以并行,分布式方式执行复杂计算的人工神经网络。所提出的自适应PI控制器的主要特征是仅将物理上可测量的变量(传输线上的有功和无功功率)用作自适应控制器的输入。为了证明所提出的自适应TCSC控制器的有效性,在干扰条件下对电力系统进行了计算机仿真。从仿真结果可以得出结论,所提出的自适应TCSC控制器可以在宽范围的工作条件下产生令人满意的动态响应。所提出的补偿器已有效地抑制了频率范围为0.3-2Hz的低频振荡。

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