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Demand-side management via optimal production scheduling in power-intensive industries: The case of metal casting process

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  • Ramin, D.
  • Spinelli, S.
  • Brusaferri, A.

Abstract

The increasing challenges to the grid stability posed by the penetration of renewable energy resources urge a more active role for demand response programs as viable alternatives to a further expansion of peak power generators. This work presents a methodology to exploit the demand flexibility of energy-intensive industries under Demand-Side Management programs in the energy and reserve markets. To this end, we propose a novel scheduling model for a multi-stage multi-line process, which incorporates both the critical manufacturing constraints and the technical requirements imposed by the market. Using mixed integer programming approach, two optimization problems are formulated to sequentially minimize the cost in a day-ahead energy market and maximize the reserve provision when participating in the ancillary market. The effectiveness of day-ahead scheduling model has been verified for the case of a real metal casting plant in the Nordic market, where a significant reduction of energy cost is obtained. Furthermore, the reserve provision is shown to be a potential tool for capitalizing on the reserve market as a secondary revenue stream.

Suggested Citation

  • Ramin, D. & Spinelli, S. & Brusaferri, A., 2018. "Demand-side management via optimal production scheduling in power-intensive industries: The case of metal casting process," Applied Energy, Elsevier, vol. 225(C), pages 622-636.
  • Handle: RePEc:eee:appene:v:225:y:2018:i:c:p:622-636
    DOI: 10.1016/j.apenergy.2018.03.084
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    References listed on IDEAS

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    Cited by:

    1. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, Open Access Journal, vol. 12(11), pages 1-26, June.
    2. Alaperä, Ilari & Honkapuro, Samuli & Paananen, Janne, 2018. "Data centers as a source of dynamic flexibility in smart girds," Applied Energy, Elsevier, vol. 229(C), pages 69-79.
    3. Dandan Zhu & Wenying Liu & Yang Hu & Weizhou Wang, 2018. "A Practical Load-Source Coordinative Method for Further Reducing Curtailed Wind Power in China with Energy-Intensive Loads," Energies, MDPI, Open Access Journal, vol. 11(11), pages 1-14, October.
    4. Brusaferri, Alessandro & Matteucci, Matteo & Portolani, Pietro & Vitali, Andrea, 2019. "Bayesian deep learning based method for probabilistic forecast of day-ahead electricity prices," Applied Energy, Elsevier, vol. 250(C), pages 1158-1175.
    5. Otashu, Joannah I. & Baldea, Michael, 2020. "Scheduling chemical processes for frequency regulation," Applied Energy, Elsevier, vol. 260(C).
    6. Kirchem, Dana & Lynch, Muireann Á. & Bertsch, Valentin & Casey, Eoin, 2020. "Modelling demand response with process models and energy systems models: Potential applications for wastewater treatment within the energy-water nexus," Applied Energy, Elsevier, vol. 260(C).
    7. Xu, Fangyuan & Wu, Wanli & Zhao, Fei & Zhou, Ya & Wang, Yongjian & Wu, Runji & Zhang, Tao & Wen, Yongchen & Fan, Yiliang & Jiang, Shengli, 2019. "A micro-market module design for university demand-side management using self-crossover genetic algorithms," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Jörn C. Richstein & Seyed Saeed Hosseinioun, 2020. "Industrial Demand Response: How Network Tariffs and Regulation Do (Not) Impact Flexibility Provision in Electricity Markets and Reserves," Discussion Papers of DIW Berlin 1853, DIW Berlin, German Institute for Economic Research.
    9. Zhou, Shengchao & Jin, Mingzhou & Du, Ni, 2020. "Energy-efficient scheduling of a single batch processing machine with dynamic job arrival times," Energy, Elsevier, vol. 209(C).
    10. Bohlayer, Markus & Fleschutz, Markus & Braun, Marco & Zöttl, Gregor, 2020. "Energy-intense production-inventory planning with participation in sequential energy markets," Applied Energy, Elsevier, vol. 258(C).
    11. Desta, Alemayehu Addisu & Badis, Hakim & George, Laurent, 2018. "Demand response scheduling in industrial asynchronous production lines constrained by available power and production rate," Applied Energy, Elsevier, vol. 230(C), pages 1414-1424.

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