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A coal shipping and blending problem for an electric utility company

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  • Liu, Chiun-Ming
  • Sherali, Hanif D.

Abstract

In this paper, we address the issues of coal supply and blending pertaining to an electric utility company in Taiwan. Since the fuel used by coal-fired power plants are mainly imported in bulk from overseas sources, the planning of coal shipping and blending is of great economic importance. This operation involves the consideration of (1) each contract's coal supply, quality and price, (2) each power plant's demand, environmental constraints and limit on the maximum number of different coal sources that can supply it, (3) installation of blending facilities and (4) the transient seaport's shipload capacity. A mixed-integer zero-one programming model is presented for finding optimal shipping and blending decisions of coal fuel from each overseas contract to each power plant. A solution procedure is developed that employs heuristic rules in conjunction with branch-and-bound methods, and is illustrated using real-world data collected from the electric power company. Results reveal the benefits of the proposed approach, which has proven to be very practical and convincing for the top management of the company.

Suggested Citation

  • Liu, Chiun-Ming & Sherali, Hanif D., 2000. "A coal shipping and blending problem for an electric utility company," Omega, Elsevier, vol. 28(4), pages 433-444, August.
    • Handle: RePEc:eee:jomega:v:28:y:2000:i:4:p:433-444
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    References listed on IDEAS

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    1. Shih, Jhih-Shyang & Frey, H. Christopher, 1995. "Coal blending optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 83(3), pages 452-465, June.
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    Citations

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    Cited by:

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    3. Marielle Christiansen & Kjetil Fagerholt & David Ronen, 2004. "Ship Routing and Scheduling: Status and Perspectives," Transportation Science, INFORMS, vol. 38(1), pages 1-18, February.
    4. Prasad, Sanjeev K. & Mangaraj, B.K., 2022. "A multi-objective competitive-design framework for fuel procurement planning in coal-fired power plants for sustainable operations," Energy Economics, Elsevier, vol. 108(C).
    5. Djeumou Fomeni, Franklin, 2018. "A multi-objective optimization approach for the blending problem in the tea industry," International Journal of Production Economics, Elsevier, vol. 205(C), pages 179-192.
    6. Gaurav Singh & Rodolfo García-Flores & Andreas Ernst & Palitha Welgama & Meimei Zhang & Kerry Munday, 2014. "Medium-Term Rail Scheduling for an Iron Ore Mining Company," Interfaces, INFORMS, vol. 44(2), pages 222-240, April.
    7. Baskoro, Firly Rachmaditya & Takahashi, Katsuhiko & Morikawa, Katsumi & Nagasawa, Keisuke, 2022. "Multi-objective optimization on total cost and carbon dioxide emission of coal supply for coal-fired power plants in Indonesia," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    8. Bilgen, Bilge & Ozkarahan, Irem, 2007. "A mixed-integer linear programming model for bulk grain blending and shipping," International Journal of Production Economics, Elsevier, vol. 107(2), pages 555-571, June.
    9. Dai, C. & Cai, X.H. & Cai, Y.P. & Huang, G.H., 2014. "A simulation-based fuzzy possibilistic programming model for coal blending management with consideration of human health risk under uncertainty," Applied Energy, Elsevier, vol. 133(C), pages 1-13.
    10. Akgün, İbrahim & Özkil, Altan & Gören, Selçuk, 2020. "A multimodal, multicommodity, and multiperiod planning problem for coal distribution to poor families," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    11. Arigoni, Ashley & Newman, Alexandra & Turner, Cameron & Kaptur, Casey, 2017. "Optimizing global thermal coal shipments," Omega, Elsevier, vol. 72(C), pages 118-127.
    12. Pablo Benalcazar & Jacek Kamiński & Karol Stós, 2022. "An Integrated Approach to Long-Term Fuel Supply Planning in Combined Heat and Power Systems," Energies, MDPI, vol. 15(22), pages 1-22, November.

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