曾文入,王维博,周 超,张 斌,郑永康.应用能量算子和改进MODWT的孤岛检测算法研究[J].电子测量与仪器学报,2020,34(2):53-59
应用能量算子和改进MODWT的孤岛检测算法研究
Research on islanding detection algorithm based on energy operator and modified MODWT
  
DOI:
中文关键词:  孤岛检测  能量算子  改进MODWT
英文关键词:islanding detection  energy operator  modified MODWT
基金项目:国家自然科学基金(61571371)、广东省自然科学基金(2015A030313853)、四川省高校重点实验室开放基金(szjj2017 046)、西华大学大健康管理促进中心开放课题(DJKG2019 005)、西华大学研究生创新基金(ycjj2018082,ycjj2019054)资助项目
作者单位
曾文入 1.西华大学电气与电子信息学院 
王维博 1.西华大学电气与电子信息学院 
周 超 1.西华大学电气与电子信息学院 
张 斌 1.西华大学电气与电子信息学院 
郑永康 2.国网四川省电力公司电力科学研究院 
AuthorInstitution
Zeng Wenru 1.School of Electrical and Electronic Information, Xihua University 
Wang Weibo 1.School of Electrical and Electronic Information, Xihua University 
Zhou Chao 1.School of Electrical and Electronic Information, Xihua University 
Zhang Bin 1.School of Electrical and Electronic Information, Xihua University 
Zheng Yongkang 2.State Grid Sichuan Electric Power Research Institute 
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中文摘要:
      针对传统孤岛检测法定位精度差、抗噪性能不强的问题,提出了一种应用能量算子和改进最大重叠离散小波变换(maximal overlap discrete wavelet transform, MODWT)的孤岛检测算法。为了有效解决MODWT算法的边界效应问题,在传统MODWT算法的基础上,采用环形边界系数更新原来的小波系数,并通过滑动窗口分析其能量。再将该算法应用于孤岛检测,用处理得到的细节系数和近似系数能量分析孤岛状态下公共耦合点的电压扰动信号特征。仿真结果表明,该算法可准确检测电压扰动信号的起始时刻和幅值变化,且在实际信号检测中不受母小波和分解层数影响、抗噪能力强且时延偏差小。
英文摘要:
      For the problem of low positioning accuracy and low anti noise performance of traditional islanding detection methods, this paper proposes an islanding detection algorithm based on energy operator and improved maximal overlap discrete wavelet transform (MODWT). In order to effectively solve the boundary effect problem of MODWT algorithm, based on the traditional MODWT algorithm, the original wavelet coefficients are updated by the circular boundary coefficients. The energy is analyzed through the sliding window. Then the algorithm is applied to the island detection, and the detail coefficient and the approximate coefficient energy obtained by the processing are used to analyze the voltage disturbance signal characteristics of the common coupling point in the island state. The simulation results show that the algorithm can accurately detect the start time and amplitude variation of the voltage disturbance signal. And it is not affected by mother wavelet and decomposition layers and it has strong anti noise ability and small delay deviation in actual signal detection.
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