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Industrial applications of production planning with optimal electricity demand

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  • Nilsson, K.
  • Söderström, M.

Abstract

The differentiation of the electricity tariff is a way to influence the electricity demand. Savings can be made when part of the electricity demand can be shifted to low-rate periods. However, the optimal production flow is often related to the electricity demand in a non-linear way. For an industry with an approximately linear electricity demand the optimal production schedule implies decreased production to yield a decreased electricity demand. A strongly non-linear electricity demand, on the other hand, may even imply an increased production to yield a decreased electricity demand. The optimal production schedules of three industrial cases are studied in response to two price constructions, represented as two differentiated tariffs.

Suggested Citation

  • Nilsson, K. & Söderström, M., 1993. "Industrial applications of production planning with optimal electricity demand," Applied Energy, Elsevier, vol. 46(2), pages 181-192.
  • Handle: RePEc:eee:appene:v:46:y:1993:i:2:p:181-192
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    Cited by:

    1. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    2. Gahm, Christian & Denz, Florian & Dirr, Martin & Tuma, Axel, 2016. "Energy-efficient scheduling in manufacturing companies: A review and research framework," European Journal of Operational Research, Elsevier, vol. 248(3), pages 744-757.
    3. Trygg, Louise & Amiri, Shahnaz, 2007. "European perspective on absorption cooling in a combined heat and power system - A case study of energy utility and industries in Sweden," Applied Energy, Elsevier, vol. 84(12), pages 1319-1337, December.
    4. Sjödin, Jörgen & Henning, Dag, 2004. "Calculating the marginal costs of a district-heating utility," Applied Energy, Elsevier, vol. 78(1), pages 1-18, May.
    5. Konstantin Biel & Christoph H. Glock, 2017. "Prerequisites of efficient decentralized waste heat recovery and energy storage in production planning," Journal of Business Economics, Springer, vol. 87(1), pages 41-72, January.
    6. Lee, Dasheng & Cheng, Chin-Chi, 2016. "Energy savings by energy management systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 760-777.
    7. Gong, Mei, 2003. "Optimization of industrial energy systems by incorporating feedback loops into the MIND method," Energy, Elsevier, vol. 28(15), pages 1655-1669.
    8. Paulus, Moritz & Borggrefe, Frieder, 2011. "The potential of demand-side management in energy-intensive industries for electricity markets in Germany," Applied Energy, Elsevier, vol. 88(2), pages 432-441, February.
    9. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    10. Khan, Aftab Ahmed & Razzaq, Sohail & Khan, Asadullah & Khursheed, Fatima & Owais,, 2015. "HEMSs and enabled demand response in electricity market: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 773-785.
    11. Difs, Kristina & Trygg, Louise, 2009. "Pricing district heating by marginal cost," Energy Policy, Elsevier, vol. 37(2), pages 606-616, February.

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