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Neural Networks Applied to Solve the Voltage Sag State Estimation Problem: An Approach Based on the Fault Positions Concept

机译:神经网络应用于解决电压SAG状态估计问题:一种基于故障位置概念的方法

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In this paper, the application of neural networks is proposed to solve the problem of voltage sags state estimation. This problem is based on estimating the voltage sags occurrence frequency at non monitored buses from the recorded voltage sags occurrence frequency at a limited number of monitored buses. The fault position method is used to formulate the optimization problem. The methodology is implemented by using Neural Networks routines from the Matlab Neural Network Toolbox. Several case studies are showed in the IEEE-24 bus Reliability Test System (RTS).
机译:本文提出了神经网络的应用来解决电压SAG状态估计的问题。该问题是基于在有限数量的受监控总线上从记录的电压SAG发生频率估计非监视总线处的电压SAG发生频率。故障位置方法用于制定优化问题。通过使用来自MATLAB神经网络工具箱的神经网络例程来实现方法。在IEEE-24总线可靠性测试系统(RTS)中显示了几种案例研究。

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