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Stochastic and minimum regret formulations for transmission network expansion planning under uncertainties

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  • E Bustamante-Cedeño

    (University of Minnesota)

  • S Arora

    (University of Minnesota)

Abstract

After deregulation of the Power sector, uncertainty has increased considerably. Vertically integrated utilities were unbundled into independent generation, transmission and distribution companies. Transmission network expansion planning (TNEP) is now performed independent from generation planning. In this environment TNEP must include uncertainties of the generation sector as well as its own. Uncertainty in generation costs affecting optimal dispatch and uncertainty in demand loads are captured through composite scenarios. Probabilities are assigned to different scenarios. The effects of these uncertainties are transferred to the objective function in terms of total costs, which include: generation (dispatch), transmission expansion and load curtailment costs. Two formulations are presented: stochastic and minimum regret. The stochastic formulation seeks a design with minimum expected cost. The minimum regret formulation seeks a design with robust performance in terms of variance of the operational costs. Results for a test problem and a potential application to a real system are presented.

Suggested Citation

  • E Bustamante-Cedeño & S Arora, 2008. "Stochastic and minimum regret formulations for transmission network expansion planning under uncertainties," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(11), pages 1547-1556, November.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:11:d:10.1057_palgrave.jors.2602492
    DOI: 10.1057/palgrave.jors.2602492
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    References listed on IDEAS

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    Cited by:

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    3. Spyros Giannelos & Stefan Borozan & Goran Strbac, 2022. "A Backwards Induction Framework for Quantifying the Option Value of Smart Charging of Electric Vehicles and the Risk of Stranded Assets under Uncertainty," Energies, MDPI, vol. 15(9), pages 1-22, May.

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