Data-Driven Compartmental Modeling Method for Harmonic Analysis—A Study of the Electric Arc Furnace

Haobo Xu, Zhenguo Shao and Feixiong Chen
Additional contact information
Haobo Xu: College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
Zhenguo Shao: College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
Feixiong Chen: College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China

Energies, 2019, vol. 12, issue 22, 1-15

Abstract: The electric arc furnace (EAF) contributes to almost one-third of the global iron and steel industry, and its harmonic pollution has drawn attention. An accurate EAF harmonic model is essential to evaluate the harmonic pollution of EAF. In this paper, a data-driven compartmental modeling method (DCMM) is proposed for the multi-mode EAF harmonic model. The proposed DCMM considers the coupling relationship among different frequencies of harmonics to enhance the modeling accuracy, meanwhile, the dimensions of the harmonic dataset are reduced to improve computational efficiency. Furthermore, the proposed DCMM is applicable to establish a multi-mode EAF harmonic model by dividing the multi-mode EAF harmonic dataset into several clusters corresponding to the different modes of the EAF smelting process. The performance evaluation results show that the proposed DCMM is adaptive in terms of establishing the multi-mode model, even if the data volumes, number of clusters, and sample distribution change significantly. Finally, a case study of EAF harmonic data is conducted to establish a multi-mode EAF harmonic model, showing that the proposed DCMM is effective and accurate in EAF modeling.

Keywords: harmonic pollution; electric arc furnace (EAF); data-driven compartmental modeling; harmonic power-flow calculation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/22/4378/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/22/4378/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:22:p:4378-:d:287991

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().