RT Journal Article
A1 Samaneh Golestani
AD School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran
A1 Haidar Samet
AD School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran

PB iet
T1 Generalised Cassie–Mayr electric arc furnace models
JN IET Generation, Transmission & Distribution
VO 10
IS 13
SP 3364
OP 3373
AB Electric arc furnace (EAF) is one of the largest loads in the power systems. Unfortunately, it is highly non-linear and time varying which causes power quality problems such as harmonics and flicker. Therefore, having an accurate EAF model is necessary. Cassie model is one of the most utilised EAF models in the related fields. However, actual data from electrical system of Mobarakeh Steel Company in Isfahan/Iran show that this model is unable to take into account some important quantities such as the active power and harmonics. Hence, as the first step in this study, different Cassie–Mayr model variants (include the Cassie model) are investigated and the best variant is attained. A novel procedure using large number of recorded actual data is utilised for the models assessment. In the second step, two generalised types of the original Cassie–Mayr model are proposed. Both the generalised types are more accurate than the best-selected Cassie–Mayr variant. All the proposed models have time-varying parameters. Their time-varying nature is studied and by analysing the time series, the proper auto regressive moving average models are attained for every parameter.
K1 autoregressive moving average model
K1 harmonics
K1 time-varying parameter
K1 flicker
K1 Mobarakeh steel company
K1 time series
K1 Isfahan-Iran
K1 active power
K1 generalised Cassie-Mayr electric arc furnace model
K1 power quality problem
K1 EAF model
K1 power systems
DO https://doi.org/10.1049/iet-gtd.2016.0405
UL https://digital-library.theiet.org/;jsessionid=183l61n2ps3jq.x-iet-live-01content/journals/10.1049/iet-gtd.2016.0405
LA English
SN 1751-8687
YR 2016
OL EN