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Investments in transmission lines and storage units considering second-order stochastic dominance constraints

Author

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  • Domínguez, Ruth
  • Carrión, Miguel
  • Vitali, Sebastiano

Abstract

Increasing intermittent renewable generation to meet the climate goals entails a deep transformation of current power systems. The transmission system must adapt to ensure a rapid and flexible response to the changes in the energy flows. Flexibility can be provided by reinforcing the interconnection among all the market agents and/or by installing facilities with fast response to the changes. In this work, we study the investment problem of a central planner that seeks to expand the transmission network and install storage units considering decarbonizing measures. We propose a two-stage stochastic problem with uncertainty on the demand growth and including representative days to characterize the hourly demand and renewable power variability. To obtain better expansion strategies according to a limit on the carbon emissions, second-order stochastic dominance constraints are imposed. Numerical analyses based on the power system of the Canary island (Spain) are provided. The results show that to install storage units is key to efficiently integrate renewable generation. The investments in the transmission system are mostly in lower-voltage lines. The formulation with stochastic dominance constraints results in higher second-stage investments, allowing a better adaptation to the demand growth evolution.

Suggested Citation

  • Domínguez, Ruth & Carrión, Miguel & Vitali, Sebastiano, 2024. "Investments in transmission lines and storage units considering second-order stochastic dominance constraints," Energy Economics, Elsevier, vol. 134(C).
  • Handle: RePEc:eee:eneeco:v:134:y:2024:i:c:s0140988324003153
    DOI: 10.1016/j.eneco.2024.107607
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    More about this item

    Keywords

    Central planner; Decarbonization; Investment model; Stochastic dominance constraints; Transmission and storage;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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