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The multi-scale generation and transmission expansion model

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  • Sarid, A.
  • Tzur, M.

Abstract

One of the challenges in electrical grid expansion planning is how to expand the infrastructure while considering fundamental changes in demand and supply, in part due to “game-changing” consumers, such as electric vehicles (EVs), and optional distributed generation (DG) by consumers. This work proposes an optimization model that addresses the generation and transmission expansion of the grid, including the facilities' locations, upgrades, and the network's design decisions. In contrast to some other models, it is not static in time: the model considers time-dependent demand in short-term (hourly) and long-term (yearly) variations. The proposed optimization model considers energy loss, transmission substations upgrades, constraints such as demand, capacities, and more. The model minimizes the long-term costs of infrastructure investments and the operational costs of generation. The work is supplemented by numerical experiments of the model in simulated scenarios. Sensitivity analysis conducted on some of the model features, demonstrates the importance of including them in the model.

Suggested Citation

  • Sarid, A. & Tzur, M., 2018. "The multi-scale generation and transmission expansion model," Energy, Elsevier, vol. 148(C), pages 977-991.
    • Handle: RePEc:eee:energy:v:148:y:2018:i:c:p:977-991
    DOI: 10.1016/j.energy.2018.01.091
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    References listed on IDEAS

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    Cited by:

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    2. Fitiwi, Desta & Lynch, Muireann Á. & Bertsch, Valentin, 2019. "Optimal development of electricity generation mix considering fossil fuel phase-out and strategic multi-area interconnection," Papers WP616, Economic and Social Research Institute (ESRI).
    3. Zhang, Zhaoyan & Wang, Peiguang & Jiang, Ping & Liu, Zhiheng & Fu, Lei, 2022. "Energy management of ultra-short-term optimal scheduling of integrated energy system considering the characteristics of heating network," Energy, Elsevier, vol. 240(C).
    4. Zhang, Zhaoyan & Jiang, Ping & Liu, Zhibin & Fu, Lei & Wang, Peiguang, 2023. "Capacity optimal configuration and collaborative planning of multi-region integrated energy system," Energy, Elsevier, vol. 278(PB).
    5. Javadi, Mohammad Sadegh & Razavi, Seyed-Ehsan & Ahmadi, Abdollah & Siano, Pierluigi, 2019. "A novel approach for distant wind farm interconnection: Iran South-West wind farms integration," Renewable Energy, Elsevier, vol. 140(C), pages 737-750.
    6. Tong Koecklin, Manuel & Fitiwi, Desta & de Carolis, Joseph F. & Curtis, John, 2020. "Renewable electricity generation and transmission network developments in light of public opposition: Insights from Ireland," Papers WP653, Economic and Social Research Institute (ESRI).
    7. Li, Tianxiao & Li, Zheng & Li, Weiqi, 2020. "Scenarios analysis on the cross-region integrating of renewable power based on a long-period cost-optimization power planning model," Renewable Energy, Elsevier, vol. 156(C), pages 851-863.
    8. Fitiwi, Desta Z. & Lynch, Muireann & Bertsch, Valentin, 2020. "Enhanced network effects and stochastic modelling in generation expansion planning: Insights from an insular power system," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    9. Manríquez, Francisco & Sauma, Enzo & Aguado, José & de la Torre, Sebastián & Contreras, Javier, 2020. "The impact of electric vehicle charging schemes in power system expansion planning," Applied Energy, Elsevier, vol. 262(C).
    10. Carrión, Miguel & Domínguez, Ruth & Zárate-Miñano, Rafael, 2019. "Influence of the controllability of electric vehicles on generation and storage capacity expansion decisions," Energy, Elsevier, vol. 189(C).
    11. Sarid, Adi S. & Glynn, Peter W. & Tzur, Michal, 2024. "Power distribution in developing countries — Planning for effectiveness and equity," Omega, Elsevier, vol. 123(C).

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