神经网络在微机变压器继电保护中的应用

Li Yongli, H. Jiali, Duan Yuqian
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引用次数: 13

摘要

提出并建立了一种用于变压器运行状态识别的神经网络方法。它优于传统的变压器保护继电器,能在故障发生后半周内正确识别空载变压器的内部故障、励磁涌流状态、外部故障和内部导通故障。此外,该方法具有广泛的可用性和高容错能力。大量的仿真实验证明了该方法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of neural network to microprocessor-based transformer protective relaying
A neural network method used to identify the operating states of transformers has been proposed and established. It is superior to the traditional transformer protective relays and can correctly identify, within half cycle from the fault inception, the internal faults, magnetizing inrush current state, external faults and switching on internal faults of a no-load transformer. In addition, this method has broad availability and high fault-tolerant ability. A lot of simulations have demonstrated its superiority.
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