Open AccessPrincipal Component Regression and Its Application in Power Harmonic Emission Level Evaluation
Author(s) -
Shuping Song,
Jie Wang,
Linheng Li,
Shuo Cheng,
Li Z
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/677/4/042087
Subject(s) - harmonic , principal component analysis , power (physics) , component (thermodynamics) , electrical impedance , electric power system , principal component regression , harmonic analysis , electronic engineering , computer science , engineering , physics , electrical engineering , acoustics , artificial intelligence , quantum mechanics , thermodynamics
Accurate harmonic emission level evaluation is the basis of distinguishing the responsibility of harmonic pollution between power supply system and consumer. A new harmonic emission level evaluation method via principal component regression (PCR) is proposed in this paper. Firstly, the principle of PCR is analyzed. Then, harmonic impedance of supply system is evaluated by PCR-based method. Subsequently, harmonic emission level of supply system and consumer is evaluated according to the harmonic impedance of supply system. This technique has the advantage of high accuracy in estimating harmonic emission level. The effectiveness of the proposed method was verified by computer simulations and field test.