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首页> 外文期刊>International journal of electrical and power engineering >Fuzzy Bang-Bang Control with ANN Based Voltage Flicker Mitigation Using DVR
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Fuzzy Bang-Bang Control with ANN Based Voltage Flicker Mitigation Using DVR

机译：使用DVR的基于ANN的电压闪变缓解模糊Bang-Bang控制

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摘要

The quality of electric power is of supreme importance to electrical utilities and their customers. Modern equipments are more sensitive to power system anomalies than in the past. Microprocessor based controls and power electronics devices are sensitive to many types of disturbances. Voltage flicker is caused by loads that exhibit continuous, rapid variations in load current. The phenomenon of flickering has been known since the introduction of power supply networks. However, it grew rapidly along with the increase in the number of loads and the increase in the power consumed. Electric arc furnace is the main generator of voltage flicker which affects the performance of other sensitive loads connected with the system. Hence, mitigation of voltage flicker becomes inevitable. FACTS devices have been gradually introduced for voltage flicker compensation. Dynamic Voltage Restorer (DVR) has been widely used to mitigate voltage flicker. The DVR with series active compensation capability opposed to variations of the arc resistance and suppress voltage flicker at the source. The control strategy adopted to mitigate flicker in an effective and robust manner is the key issue. A scheme based on fuzzy bang-bang control with ANN is proposed for flicker mitigation using DVR in this study. Two dimensional fuzzy control rules are framed based on Lyapunov function analysis and selection of control rule with best response to current state is done using Artificial Neural Network (ANN). Using the proposed control algorithm, the DVR will contribute to the mitigation of flicker without deteriorating the effect of the other compensating devices. The control algorithm is simulated on a power system model with arc furnace load. Numerical simulations show the effectiveness of the controller in compensating voltage flicker.
机译：电力质量对于电力公司及其客户至关重要。与过去相比，现代设备对电源系统异常更加敏感。基于微处理器的控件和电力电子设备对许多类型的干扰都很敏感。电压闪烁是由负载引起的，负载电流连续快速变化。自从引入电源网络以来，就已经知道闪烁现象。但是，随着负载数量的增加和功耗的增加，它迅速增长。电弧炉是电压闪变的主要发生器，它会影响与系统连接的其他敏感负载的性能。因此，减轻电压闪烁变得不可避免。 FACTS器件已逐步引入，用于电压闪烁补偿。动态电压恢复器（DVR）已被广泛用于减轻电压闪烁。具有串联有源补偿功能的DVR可以抵抗电弧电阻的变化，并抑制电源处的电压闪变。关键问题是采用有效有效地减轻闪烁的控制策略。在本研究中，提出了一种基于模糊神经网络的神经网络闪烁抑制方法。基于Lyapunov函数分析构建了二维模糊控制规则，并使用人工神经网络（ANN）选择了对当前状态具有最佳响应的控制规则。使用提出的控制算法，DVR将有助于减轻闪烁，而不会降低其他补偿设备的效果。该控制算法是在电弧炉负载的电力系统模型上进行仿真的。数值仿真显示了控制器在补偿电压闪烁方面的有效性。

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