基于小波包時間熵的配電網運行狀態(tài)特征提取方法
發(fā)布時間:2018-12-25 07:43
【摘要】:為了及時監(jiān)測配電網運行情況進而快速準確甄別配電網的正常、異常以及故障狀態(tài),提出基于小波包時間熵的配電網運行狀態(tài)特征提取方法,給出其小波基函數(shù)、分解層數(shù)和尺度、時間窗等相關參數(shù)的選擇規(guī)范,分析該小波熵對系統(tǒng)狀態(tài)表征的機理。搭建典型配電網模型,針對各種運行工況下典型配電網運行狀態(tài)進行模擬仿真,仿真結果表明,所提方法能夠正確區(qū)分配電網典型運行狀態(tài),并且不受網絡拓撲、線路類型、故障類型、故障時刻、故障位置、過渡電阻等因素的影響,具有較好的適應性。
[Abstract]:In order to monitor the operation of distribution network in time and quickly and accurately identify the normal, abnormal and fault state of distribution network, a method based on wavelet packet time entropy is proposed to extract the characteristics of distribution network operation state, and its wavelet basis function is given. The parameters of decomposition layer, scale, time window and so on are selected, and the mechanism of the wavelet entropy to represent the state of the system is analyzed. The simulation results show that the proposed method can correctly distinguish the typical operation state of distribution network and is not subject to network topology and line type. Fault type, fault time, fault location, transition resistance and other factors have good adaptability.
【作者單位】: 廣東電網公司電力科學研究院;武漢大學電氣工程學院;
【基金】:國家自然科學基金面上項目(51277135) 南方電網公司重點科技項目(K-GD2012-343)~~
【分類號】:TM732
本文編號:2390873
[Abstract]:In order to monitor the operation of distribution network in time and quickly and accurately identify the normal, abnormal and fault state of distribution network, a method based on wavelet packet time entropy is proposed to extract the characteristics of distribution network operation state, and its wavelet basis function is given. The parameters of decomposition layer, scale, time window and so on are selected, and the mechanism of the wavelet entropy to represent the state of the system is analyzed. The simulation results show that the proposed method can correctly distinguish the typical operation state of distribution network and is not subject to network topology and line type. Fault type, fault time, fault location, transition resistance and other factors have good adaptability.
【作者單位】: 廣東電網公司電力科學研究院;武漢大學電氣工程學院;
【基金】:國家自然科學基金面上項目(51277135) 南方電網公司重點科技項目(K-GD2012-343)~~
【分類號】:TM732
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,本文編號:2390873
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