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author:

Kavousi-Fard, Abdollah (Kavousi-Fard, Abdollah.) [1] | Su, Wencong (Su, Wencong.) [2] | Jin, Tao (Jin, Tao.) [3] (Scholars:金涛) | Al-Sumaiti, Ameena Saad (Al-Sumaiti, Ameena Saad.) [4] | Samet, Haidar (Samet, Haidar.) [5] | Khosravi, Abbas (Khosravi, Abbas.) [6]

Indexed by:

EI Scopus SCIE

Abstract:

This paper develops a new predictive approach to improve the static VAr compensator (SVC) performance in the electric arc furnaces (EAFs). The proposed method models the reactive power consumption pattern in the EAF for a half-cycle ahead to improve the SVC compensation process. Given this, a new nonparametric approach based on lower upper bound estimation method and support vector regression (SVR) is developed to construct prediction intervals (PIs) around the reactive power consumption pattern in the SVC. The proposed method makes use of the PI concept to model the uncertainties of reactive power and, thus, avoid the flicker issues. Owing to the high complexity and nonlinearity of the proposed problem, a new optimization method based on the krill herd (KH) algorithm is proposed to adjust the SVR setting parameters, optimally. Also, a three-stage modification method is suggested to increase the krill population and avoid the premature convergence. The feasibility and performance of the proposed method are examined using experimental data gathered from the Mobarakeh Steel Company, Iran.

Keyword:

Electric arc furnace (EAF) prediction reactive power compensation static VAr compensator (SVC) uncertainty

Community:

  • [ 1 ] [Kavousi-Fard, Abdollah]Fuzhou Univ, Dept Elect Engn, Fuzhou 350116, Fujian, Peoples R China
  • [ 2 ] [Su, Wencong]Fuzhou Univ, Dept Elect Engn, Fuzhou 350116, Fujian, Peoples R China
  • [ 3 ] [Jin, Tao]Fuzhou Univ, Dept Elect Engn, Fuzhou 350116, Fujian, Peoples R China
  • [ 4 ] [Su, Wencong]Univ Michigan, Dept Elect & Comp Engn, Dearborn, MI 48126 USA
  • [ 5 ] [Al-Sumaiti, Ameena Saad]Khalifa Univ, Dept Elect & Comp Engn, Abu Dhabi 127788, U Arab Emirates
  • [ 6 ] [Samet, Haidar]Shiraz Univ, Sch Elect & Comp Engn, Shiraz 7134851154, Iran
  • [ 7 ] [Khosravi, Abbas]Deakin Univ, Inst Intelligent Syst Res & Innovat, Geelong, Vic 3217, Australia

Reprint 's Address:

  • 蔡其洪

    [Kavousi-Fard, Abdollah]Fuzhou Univ, Dept Elect Engn, Fuzhou 350116, Fujian, Peoples R China

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Source :

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

ISSN: 0278-0046

Year: 2019

Issue: 10

Volume: 66

Page: 7976-7985

7 . 5 1 5

JCR@2019

7 . 5 0 0

JCR@2023

ESI Discipline: ENGINEERING;

ESI HC Threshold:150

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 11

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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