Title :
Modeling highly nonlinear load dynamics for harmonic assessment
Author_Institution :
Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan
Abstract :
In this paper, an advanced method based on measured data and neural network for highly nonlinear loads such as electric arc furnaces (EAFs) is introduced. An industrial power system with the EAF load is used for field measurements. Modeling results obtained by the proposed method are then compared with the measured data. It shows that the presented method can model the highly nonlinear load dynamics with a good accuracy.
Keywords :
industrial power systems; neural nets; power system harmonics; power system simulation; EAF load; electric arc furnaces; field measurements; harmonic assessment; highly nonlinear load dynamic modelling; industrial power system; neural network; Current measurement; Furnaces; Harmonic analysis; Load modeling; Mathematical model; Power system harmonics; Voltage measurement; Electric arc furnace; harmonics; neural network;
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
DOI :
10.1109/PESGM.2012.6344563
