摘要
为准确辨别导致高速铁路牵引负荷产生谐波电流的主要影响因素,通过相关性分析建立基于电能质量多维度实测数据的量化指标特征数据集,并使用基于信息熵的信息增益算法对影响谐波电流发射特性的主要因素进行影响度大小评估,进而辨别出主导因素。结合安装于牵引站的电能质量终端监测数据对该算法进行了验证,实验结果证明该算法可以准确判别导致谐波电流超标的主导因素。
In order to accurately identify the main influencing factors of harmonic current of high-speed railway traction load,the correlation analysis is used to establish the index feature data set based on multi-dimensional measured data of power quality.Then,the information gain algorithm based on information entropy is proposed to evaluate the influence degree of main factors.Finally,the dominant factors can be identified.The algorithm is verified by the power quality terminal monitoring data installed in the traction station.The experimental results show that the algorithm can accurately identify the dominant factors which lead to the harmonic current exceeding the standard.
作者
曾杰
许中平
李守超
于希永
吴耀军
Zeng Jie;Xu Zhongping;Li Shouchao;Yu Xiyong;Wu Yaojun(State Grid Tibet Electric Power Co.,Ltd.,Xizang Lhasa,850000,China;Beijing State Grid Xintong Accenture Information Technology Co.,Ltd.,Beijing,100089,China)
出处
《机械设计与制造工程》
2021年第7期92-96,共5页
Machine Design and Manufacturing Engineering
关键词
信息增益
谐波电流
牵引供电
概率分布模型
information gain
harmonic current
traction power supply
probability distribution model
