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文章摘要
基于小波包能量熵和BP神经网络的孤岛检测法
Island detection method based on wavelet packet energy entropy and BP neural network
Received:August 14, 2019  Revised:August 15, 2019
DOI:10.19753/j.issn1001-1390.2022.02.009
中文关键词: 孤岛检测  小波包变换  信息熵  BP神经网络
英文关键词: island detection, wavelet packet transform, information entropy, BP neural network
基金项目:国家自然科学基金项目( 项目编号)
Author NameAffiliationE-mail
Sang Baoxu* School of Electrical Engineering,Xinjiang University
Xinjiang,China 
624596376@qq.com 
Pazilai Mahemuti School of Electrical Engineering,Xinjiang University
Xinjiang,China 
624596376@qq.com 
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中文摘要:
      非计划性孤岛会对电网造成严重的冲击以及人身伤害,实现孤岛检测必须准确快速。针对目前的基于信号处理的孤岛检测技术,提出了小波包能量熵和BP神经网络的孤岛检测法。通过小波包变换分解重构公共点电压与逆变器输出电流,得到重构序列,对其进行熵运算,得到更稳定,且更具有代表性的特征向量,可以更有效地区分孤岛发生前后的能量分布。通过BP神经网络对孤岛进行判断,实现了孤岛检测。通过MATLAB/Simulink仿真,表明了此方法的有效性,并且响应速度非常快,未引入扰动,故不会产生电能质量的问题,其稳定性高,检测盲区小。
英文摘要:
      Unplanned island detection will cause serious impact on the power grid and personal injury, so the implementation of the island detection must be accurate and rapid. Aiming at the current island detection technology based on signal processing, this paper proposes the novel island detection method based on wavelet packet energy entropy and BP neural network. Firstly, the common point voltage and the output current of an inverter are decomposed and reconstructed by wavelet packet transformation, and the reconstructed sequences are obtained. Then, entropy operation is conducted on the sequences, which can get a more stable and representative eigenvector. In this way, we can distinguish the energy distribution before and after island occurrence more effectively. Finally, the BP neural network is adopted to judge the island for realizing the island detection. In addition, the MATLAB/Simulink simulation shows the effectiveness of the proposed method, and the response speed is fast. And there is no need to introduce disturbances, which will not cause the power quality problems, and its stability is high, and the detection blind zone is small.
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