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基于LSSTM算法的配电网故障自动定位方法

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现行配电网故障定位方法在实践中故障选区错误率较高,而且RMSE也比较高,为此提出基于LSSTM算法的配电网故障自动定位方法.根据配电网故障特征确定感知目标,利用无线传感器感知配电网故障状态向量,采用SF算法对故障状态信号稀疏滤波,利用LSSTM算法对配电网故障状态特征进行学习训练,并进行故障所在区段的定位.所提出的方法在验证实验中,故障选区错误率在2%以内,均方根误差小于0.2.
LSSTM Algorithm-based Automatic Fault Location for Distribution Networks
Currently prevailing distribution network fault location methods suffer in practice high error rate of faulty zone determination and high RMSE.The present work studied an LSSTM algorithm-based fault location method.The method was designed to determine the perception target based on fault characteristics of distribution networks,to use wireless sensors to perceive fault state vectors,to sparsely filter fault state signal by adopting SF algorithm,and to learn and train fault state features by employing LSSTM algorithm,thereby determining the faulty zone.The proposed method achieved in verification experiment an error rate of faulty zone determination within 2%,and a root mean square error of less than 0.2.

LSSTM algorithmdistribution networkautomatic locationSF algorithmsparse filtering

刘策、鲁丛、徐丹

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国网北京大兴供电公司,北京 102600

LSSTM算法 配电网 自动定位 SF算法 稀疏滤波

2024

电工技术
重庆西南信息有限公司(原科技部西南信息中心)

电工技术

影响因子:0.177
ISSN:1002-1388
年,卷(期):2024.(14)