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Supply, Storage, and Service Reliability Decisions by Gas Distribution Utilities: A Chance-Constrained Approach

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  • Jean-Michel Guldmann

    (Ohio State University)

Abstract

This paper explores the trade-offs among purchases, storage, and service reliability decisions faced by natural gas distribution utilities. The short-term demand for natural gas fluctuates because of the weather. To encourage load leveling, the pipeline transmission companies that supply the utilities use a demand contract that charges utilities based on their peak day needs and often charge for a minimum daily purchase requirement whether that purchase is made or not. The policy variables available to the utility include increasing its storage capacity and providing interruptible service to some customers thereby lowering reliability of service. There are also technological constraints on the maximum storage gas flows. To explore these trade-offs, a chance-constrained cost minimization problem is formulated. Two decision rules for gas purchases and storage operation are examined. In these rules, an initial decision is made at the beginning of each month about either the level of purchases or the level of storage flow for that month. The two rules differ in that the supplier is assumed either to be able to adjust sales during the month up to the limit set by the demand contract or to be inflexible. In the latter case, storage must provide flexibility for meeting demand. Solutions have been obtained under the conditions that apply to the East Ohio Gas Company. A large number of cases have been considered for several levels of increased storage capacity, decreased reliability of service, and conversion capability from gas to oil for commercial and industrial customers. The results show the breakeven points in storage costs under which various policies become feasible and the savings that can be achieved.

Suggested Citation

  • Jean-Michel Guldmann, 1983. "Supply, Storage, and Service Reliability Decisions by Gas Distribution Utilities: A Chance-Constrained Approach," Management Science, INFORMS, vol. 29(8), pages 884-906, August.
  • Handle: RePEc:inm:ormnsc:v:29:y:1983:i:8:p:884-906
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    File URL: http://dx.doi.org/10.1287/mnsc.29.8.884
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    References listed on IDEAS

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    1. Ian I. Mitroff, 1972. "The Myth of Objectivity OR Why Science Needs a New Psychology of Science," Management Science, INFORMS, vol. 18(10), pages 613-618, June.
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    Cited by:

    1. Lise, Wietze & Hobbs, Benjamin F. & van Oostvoorn, Frits, 2008. "Natural gas corridors between the EU and its main suppliers: Simulation results with the dynamic GASTALE model," Energy Policy, Elsevier, vol. 36(6), pages 1890-1906, June.
    2. Lise, Wietze & Hobbs, Benjamin F., 2008. "Future evolution of the liberalised European gas market: Simulation results with a dynamic model," Energy, Elsevier, vol. 33(7), pages 989-1004.
    3. Aouam, Tarik & Rardin, Ronald & Abrache, Jawad, 2010. "Robust strategies for natural gas procurement," European Journal of Operational Research, Elsevier, vol. 205(1), pages 151-158, August.
    4. Gabriel, Steven A. & Zhuang, Jifang & Kiet, Supat, 2005. "A large-scale linear complementarity model of the North American natural gas market," Energy Economics, Elsevier, vol. 27(4), pages 639-665, July.
    5. Lo, Hong K. & Tung, Yeou-Koung, 2003. "Network with degradable links: capacity analysis and design," Transportation Research Part B: Methodological, Elsevier, vol. 37(4), pages 345-363, May.
    6. Guldmann, Jean-Michel & Wang, Fahui, 1999. "Optimizing the natural gas supply mix of local distribution utilities," European Journal of Operational Research, Elsevier, vol. 112(3), pages 598-612, February.
    7. Sakalauskas, Leonidas L., 2002. "Nonlinear stochastic programming by Monte-Carlo estimators," European Journal of Operational Research, Elsevier, vol. 137(3), pages 558-573, March.
    8. Jirutitijaroen, Panida & Kim, Sujin & Kittithreerapronchai, Oran & Prina, José, 2013. "An optimization model for natural gas supply portfolios of a power generation company," Applied Energy, Elsevier, pages 1-9.

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