Dimensionality reduction based on parallel factor analysis model and independent component analysis method

2019 ◽  
Vol 13 (01) ◽  
pp. 1 ◽  
Author(s):  
Ronghua Yan ◽  
Jinye Peng ◽  
Dongmei Ma
Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 323
Author(s):  
Jinshuai Zhao ◽  
Honggeng Yang ◽  
Xiaoyang Ma ◽  
Fangwei Xu

Evaluating the harmonic contributions of each nonlinear customer is important for harmonic mitigation in a power system with diverse and complex harmonic sources. The existing evaluation methods have two shortcomings: (1) the calculation accuracy is easily affected by background harmonics fluctuation; and (2) they rely on Global Positioning System (GPS) measurements, which is not economic when widely applied. In this paper, based on the properties of asynchronous measurements, we propose a model for evaluating harmonic contributions without GPS technology. In addition, based on the Gaussianity of the measured harmonic data, a mixed entropy screening mechanism is proposed to assess the fluctuation degree of the background harmonics for each data segment. Only the segments with relatively stable background harmonics are chosen for calculation, which reduces the impacts of the background harmonics in a certain degree. Additionally, complex independent component analysis, as a potential method to this field, is improved in this paper. During the calculation process, the sparseness of the mixed matrix in this method is used to reduce the optimization dimension and enhance the evaluation accuracy. The validity and the effectiveness of the proposed methods are verified through simulations and field case studies.


Sign in / Sign up

Export Citation Format

Share Document