Optimization of steel production scheduling with complex time-sensitive electricity cost

Research output: Contribution to journalArticle

Researchers

Research units

  • Dortmund University
  • Carnegie Mellon University
  • ABB Group

Abstract

Energy-intensive industries can take advantage of process flexibility to reduce operating costs by optimal scheduling of production tasks. In this study, we develop an MILP formulation to extend a continuous-time model with energy-awareness to optimize the daily production schedules and the electricity purchase including the load commitment problem. The sources of electricity that are considered are purchase on volatile markets, time-of-use and base load contracts, as well as onsite generation. The possibility to sell electricity back to the grid is also included. The model is applied to the melt shop section of a stainless steel plant. Due to the large-scale nature of the combinatorial problem, we propose a bi-level heuristic algorithm to tackle instances of industrial size. Case studies show that the potential impact of high prices in the day-ahead markets of electricity can be mitigated by jointly optimizing the production schedule and the associated net electricity consumption cost.

Details

Original languageEnglish
Pages (from-to)117-136
Number of pages20
JournalComputers and Chemical Engineering
Volume76
Publication statusPublished - 8 May 2015
MoE publication typeA1 Journal article-refereed

    Research areas

  • Continuous-time models, Demand-side management, Energy optimization, Scheduling, Steel plant

ID: 6320112