摘要
盲源分离技术可以在不知道网络参数或拓扑结构的情况下,仅用部分支路有功潮流估计出各节点负荷。本文采用了核独立分量分析算法进行负荷曲线估计,使用再生核希尔伯特空间上的典型相关性分析作为目标函数。实验基于IEEE-14母线系统,估计出了8个负荷节点的有功功率。结果表明,同独立分量分析方法得到的仿真结果相比,核独立分量分析算法估计的结果误差更小,相关系数更大。
Blind source separation（BSS） can be applied to estimate load profiles using only a small set of active line flow measurements without prior knowledge of the electric network model parameters or topology. In this paper Kernel independent component analysis is used to estimate electric load profiles which use contrast functions based on canonical correlations in a reproducing Kernel Hilbert space. The proposed approach is demonstrated for the IEEE-14 system to estimate eight active load profiles. The results from Kernel independent component analysis algorithm have lower estimation errors and larger correlation coefficients compared with those from independent component analysis algorithm.
出处
《电工技术学报》
EI
CSCD
北大核心
2009年第10期160-164,169,共6页
Transactions of China Electrotechnical Society
关键词
盲源分离
独立分量分析
核独立分量分析
负荷估计
有功功率
Blind source separation（BSS）, independent component analysis, Kernel independent component analysis, load profile estimation, active power
