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Automatic contingency grouping using partial least squares and feed forward neural network technologies applied to the static security assessment problem

机译:使用偏最小二乘和前馈神经网络技术的自动权变分组,应用于静态安全评估问题

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摘要

The paper shows how a number of feed forward back propagation neural networks can be trained to predict power system bus voltages after a contingency. The approach is designed to use very few learning examples. thus being suitable for on-line use. The method was applied to the 10-machine, 39-bus New England Power System model.
机译:本文展示了如何训练许多前馈传播神经网络,以在意外事件发生后预测电力系统的母线电压。该方法旨在使用很少的学习示例。因此适合在线使用。该方法已应用于10机,39总线的New England Power System模型。

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