Cost-Effective Scheduling of Steel Plants with Flexible EAFs

Xiao Zhang, Gabriela Hug, Iiro Harjunkoski

Research output: Contribution to journalArticleScientificpeer-review

35 Citations (Scopus)

Abstract

Electric arc furnaces (EAFs) in steel plants consume a large amount of electric energy, and the energy cost constitutes a significant proportion of the total costs in producing steel. However, a steel plant can take advantage of time-based electricity prices by optimally arranging energy-consuming activities to avoid peak hours. Besides, the EAFs' power rate can be adjusted by switching transformers' taps, which offers additional flexibility for arranging energy consumption and minimizing the cost of electricity. In this paper, we propose scheduling models based on resource-task network formulations that incorporate the EAFs' flexibilities to reduce the electricity cost. The effectiveness of the model is demonstrated in multiple case studies.

Original languageEnglish
Article number7482812
Pages (from-to)239-249
Number of pages11
JournalIEEE Transactions on Smart Grid
Volume8
Issue number1
DOIs
Publication statusPublished - 1 Jan 2017
MoE publication typeA1 Journal article-refereed

Keywords

  • demand response
  • industrial load
  • mixed integer programming
  • Resource task network
  • steel manufacturing

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