摘要
为了取消正弦相似性原理中的最小二乘法等中间环节,获得直接固定标准正弦波形所需要的能量信息。借鉴时域概率分布的方法论,从优势互补的角度出发,设计了一种基于Wasserstein距离算法的变压器励磁涌流闭锁方案。该方案采用特征离散化的方式,提取目标对象和模板信号并转化为状态向量作为样本标签,以此来判别两者之间的能量分布差异,从而达到正弦场景同源识别的效果。理论分析与仿真结果表明,该方法实现简便,不需要频域计算。相比于现有正弦相似性原理,降低了保护流程的复杂程度,具有更强的实际应用价值和速动性能。通过PSCAD/MATLAB平台对现场合闸的录波数据进行测试分析,验证了所提方案对促进变压器保护性能的积极意义。
In order to eliminate the intermediate links such as the least square method in the sine similarity principle,the energy information required to directly fix the standard sine waveform is obtained.Based on the methodology of time-domain probability distribution,an inrush current locking scheme based on Wasser⁃stein distance algorithm is designed from the perspective of complementary advantages.The proposed scheme uses feature discretization to extract target objects and template signals and convert them into state vectors as sample labels,so as to distinguish the energy distribution difference between the two and achieve the effect of homologous recognition of sinusoidal scenes.Theoretical analysis and simulative results show that the proposed scheme is simple and does not need frequency domain calculation.Compared with the existing sinusoidal similarity principle,it reduces the complexity of the protection process and has stronger practical application value and quick performance.The recorded data of on-site closing are tested and ana⁃lyzed by PSCAD/MATLAB platform software,which verifies the positive significance of the proposed scheme to promote the transformer protection performance.
作者
陈勇
张员宁
黄景光
刘琦
李浙栋
林湘宁
CHEN Yong;ZHANG Yuanning;HUANG Jingguang;LIU Qi;LI Zhedong;LIN Xiangning(Hubei Provincial Engineering Center for Intelligent Energy Technology,China Three Gorges University,Yichang 443002,China;Super High Voltage Company of State Grid Hubei Electric Power Co.,Ltd.,Wuhan 430050,China;National Electric Power Conversion and Control Engineering Technology Research Center,Hunan University,Changsha 410082,China;State Key Laboratory of Advanced Electromagnetic Engineering and Technology,Huazhong University of Science and Technology,Wuhan 430074,China)
出处
《电力自动化设备》
EI
CSCD
北大核心
2024年第1期196-202,共7页
Electric Power Automation Equipment
基金
国家自然科学基金资助项目(51877088)。
