Open AccessModeling and Analysis of Industrial Power Load Based on Measured Data
Author(s) -
Yan Zhang,
Huajia Wang,
Deyong Yu,
Gaofeng Zhang,
Weichao Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1601/2/022033
Subject(s) - harmonics , smart grid , reliability (semiconductor) , electric arc furnace , automotive engineering , electrical load , power (physics) , wind power , computer science , electric power system , reliability engineering , load distribution , electric power , electrical engineering , engineering , structural engineering , voltage , physics , materials science , quantum mechanics , metallurgy
With the rapid development of electronic technology, the construction of smart grids has been accelerated. Establishing an accurate load model is of great significance to the stability of distribution network system. Some large-capacity installations with more harmonics and impact, such as electric arc furnaces and wind farm are connected to the grid, which has a serious impact on the power quality of the distribution network. This paper adopts a method of industrial load modeling based on the fitting of measured data, selects electric arc furnace and aluminum rolling mill as typical industrial loads, establishes its model through fitting the measured data, which proves the reliability and accuracy of the load model.