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Natural gas cash-out problem: Bilevel stochastic optimization approach

Author

Listed:
  • Kalashnikov, Vyacheslav V.
  • Pérez-Valdés, Gerardo A.
  • Tomasgard, Asgeir
  • Kalashnykova, Nataliya I.

Abstract

A stochastic formulation of the natural gas cash-out problem is given in a form of a bilevel multi-stage stochastic programming model with recourse. After reducing the original formulation to a bilevel linear problem, a stochastic scenario tree is defined by its node events, and time series forecasting is used to produce stochastic values for data of natural gas price and demand. Numerical experiments were run to compare the stochastic solution with the perfect information solution and the expected value solutions.

Suggested Citation

  • Kalashnikov, Vyacheslav V. & Pérez-Valdés, Gerardo A. & Tomasgard, Asgeir & Kalashnykova, Nataliya I., 2010. "Natural gas cash-out problem: Bilevel stochastic optimization approach," European Journal of Operational Research, Elsevier, vol. 206(1), pages 18-33, October.
  • Handle: RePEc:eee:ejores:v:206:y:2010:i:1:p:18-33
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Alizadeh, S.M. & Marcotte, P. & Savard, G., 2013. "Two-stage stochastic bilevel programming over a transportation network," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 92-105.
    2. Kovacevic, Raimund M. & Pflug, Georg Ch., 2014. "Electricity swing option pricing by stochastic bilevel optimization: A survey and new approaches," European Journal of Operational Research, Elsevier, vol. 237(2), pages 389-403.
    3. Chen, Yizhong & He, Li & Li, Jing & Cheng, Xi & Lu, Hongwei, 2016. "An inexact bi-level simulation–optimization model for conjunctive regional renewable energy planning and air pollution control for electric power generation systems," Applied Energy, Elsevier, vol. 183(C), pages 969-983.
    4. Dempe, Stephan & Kalashnikov, Vyacheslav V. & Pérez-Valdés, Gerardo A. & Kalashnykova, Nataliya I., 2011. "Natural gas bilevel cash-out problem: Convergence of a penalty function method," European Journal of Operational Research, Elsevier, vol. 215(3), pages 532-538, December.

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