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多谐波源同次谐波叠加计算方法
引用本文:华回春,郑璐,王莉,贾秀芳.多谐波源同次谐波叠加计算方法[J].电力系统自动化,2016,40(19):107-112.
作者姓名:华回春  郑璐  王莉  贾秀芳
作者单位:新能源电力系统国家重点实验室(华北电力大学), 河北省保定市 071003,新能源电力系统国家重点实验室(华北电力大学), 河北省保定市 071003,国网河南省电力公司检修公司, 河南省郑州市 450000,新能源电力系统国家重点实验室(华北电力大学), 河北省保定市 071003
基金项目:中央高校基本科研业务费专项资金资助项目(2014MS164)
摘    要:在相角未知条件下,国家标准中采用系数估算的方法进行谐波叠加计算,效果往往并不理想。在谐波叠加理论分析的基础上,文中构造了基于核密度估计与重要抽样的蒙特卡洛方法,用以计算多谐波源的同次谐波叠加电流。首先,运用核密度估计法可以计算谐波电流相角的概率密度函数,且通过重要抽样方法可对其进行抽样并得到核样本数据。再利用蒙特卡洛方法结合核样本数据对谐波叠加的交叉项进行估算,最终确定出谐波叠加电流的计算公式。仿真分析与实际算例表明,所提算法可获得更为精确的谐波叠加电流估计量,并可以简单高效地应用于多谐波源系统的谐波叠加中。

关 键 词:谐波叠加  蒙特卡洛法  核密度估计  重要抽样
收稿时间:2015/11/10 0:00:00
修稿时间:2016/8/23 0:00:00

Calculation Method for Same-order Harmonic Superposition of Multiple Harmonic Sources
HUA Huichun,ZHENG Lu,WANG Li and JIA Xiufang.Calculation Method for Same-order Harmonic Superposition of Multiple Harmonic Sources[J].Automation of Electric Power Systems,2016,40(19):107-112.
Authors:HUA Huichun  ZHENG Lu  WANG Li and JIA Xiufang
Affiliation:State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University), Baoding 071003, China,State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University), Baoding 071003, China,Maintenance Company of State Grid Henan Electric Power Company, Zhengzhou 450000, China and State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University), Baoding 071003, China
Abstract:In the case of unknown phase angle, the harmonic superposition calculation using the coefficient estimation method in the national standard is usually not ideal. According to the theory analysis of harmonic superposition, this paper develops a Monte Carlo method based on kernel estimate and important sampling to calculate the same-order harmonic current superposition of multiple harmonic sources. Firstly, the probability density function of harmonic current phase angle is calculated using the kernel density estimation and sampled by using the important sampling method to obtain the kernel sample data. Then, the Monte Carlo method and the kernel sample data are used to estimate the cross terms of harmonic superposition. Finally, the formula for harmonic current superposition is determined. Simulation analysis and actual examples show that the proposed algorithm can yield more accurate estimator of the superposition of harmonic current and be efficiently applied to the harmonic superposition of multiple harmonic source systems. This work is supported by Fundamental Research Funds for the Central Universities(No. 2014MS164).
Keywords:harmonic superposition  Monte Carlo method  kernel density estimation  important sampling
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