IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v98y2021ics0140988321001511.html
   My bibliography  Save this article

Robust transmission network expansion planning considering non-convex operational constraints

Author

Listed:
  • García-Cerezo, Álvaro
  • Baringo, Luis
  • García-Bertrand, Raquel

Abstract

This paper proposes a two-stage robust optimization model for the transmission network expansion planning problem. Long-term uncertainties in the peak demand and generation capacity are modeled using confidence bounds, while the short-term variability of demand and renewable production is modeled using a set of representative days. As a distinctive feature, this work takes into account the non-convex operation of conventional generating units and storage facilities, which results in a two-stage robust optimization model with a discrete recourse problem. The resulting problem is solved using a nested column-and-constraint generation algorithm that guarantees convergence to the global optimum in a finite number of iterations. An illustrative example and a case study are used to show the performance of the proposed approach. Numerical results show that neglecting the non-convex operation of conventional generating units and storage facilities leads to suboptimal expansion decisions.

Suggested Citation

  • García-Cerezo, Álvaro & Baringo, Luis & García-Bertrand, Raquel, 2021. "Robust transmission network expansion planning considering non-convex operational constraints," Energy Economics, Elsevier, vol. 98(C).
    • Handle: RePEc:eee:eneeco:v:98:y:2021:i:c:s0140988321001511
    DOI: 10.1016/j.eneco.2021.105246
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988321001511
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2021.105246?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ioannou, Anastasia & Fuzuli, Gulistiani & Brennan, Feargal & Yudha, Satya Widya & Angus, Andrew, 2019. "Multi-stage stochastic optimization framework for power generation system planning integrating hybrid uncertainty modelling," Energy Economics, Elsevier, vol. 80(C), pages 760-776.
    2. Poncelet, Kris & Delarue, Erik & D’haeseleer, William, 2020. "Unit commitment constraints in long-term planning models: Relevance, pitfalls and the role of assumptions on flexibility," Applied Energy, Elsevier, vol. 258(C).
    3. Álvaro García-Cerezo & Luis Baringo & Raquel García-Bertrand, 2020. "Representative Days for Expansion Decisions in Power Systems," Energies, MDPI, vol. 13(2), pages 1-18, January.
    4. Pisciella, P. & Vespucci, M.T. & Bertocchi, M. & Zigrino, S., 2016. "A time consistent risk averse three-stage stochastic mixed integer optimization model for power generation capacity expansion," Energy Economics, Elsevier, vol. 53(C), pages 203-211.
    5. Ramteen Sioshansi & Antonio J. Conejo, 2017. "Optimization in Engineering," Springer Optimization and Its Applications, Springer, number 978-3-319-56769-3, June.
    6. Ruiz, C. & Conejo, A.J., 2015. "Robust transmission expansion planning," European Journal of Operational Research, Elsevier, vol. 242(2), pages 390-401.
    7. Baringo, L. & Conejo, A.J., 2013. "Correlated wind-power production and electric load scenarios for investment decisions," Applied Energy, Elsevier, vol. 101(C), pages 475-482.
    8. Boffino, Luigi & Conejo, Antonio J. & Sioshansi, Ramteen & Oggioni, Giorgia, 2019. "A two-stage stochastic optimization planning framework to decarbonize deeply electric power systems," Energy Economics, Elsevier, vol. 84(C).
    9. Caunhye, Aakil M. & Cardin, Michel-Alexandre, 2018. "Towards more resilient integrated power grid capacity expansion: A robust optimization approach with operational flexibility," Energy Economics, Elsevier, vol. 72(C), pages 20-34.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yıldıran, Uğur, 2023. "Robust multi-stage economic dispatch with renewable generation and storage," European Journal of Operational Research, Elsevier, vol. 309(2), pages 890-909.
    2. García-Cerezo, Álvaro & Baringo, Luis & García-Bertrand, Raquel, 2023. "Expansion planning of the transmission network with high penetration of renewable generation: A multi-year two-stage adaptive robust optimization approach," Applied Energy, Elsevier, vol. 349(C).
    3. Bichler, Martin & Knörr, Johannes, 2023. "Getting prices right on electricity spot markets: On the economic impact of advanced power flow models," Energy Economics, Elsevier, vol. 126(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Baringo, Luis & Boffino, Luigi & Oggioni, Giorgia, 2020. "Robust expansion planning of a distribution system with electric vehicles, storage and renewable units," Applied Energy, Elsevier, vol. 265(C).
    2. Li, Carmen & Chyong, Chi Kong & Reiner, David M. & Roques, Fabien, 2024. "Taking a Portfolio approach to wind and solar deployment: The case of the National Electricity Market in Australia," Applied Energy, Elsevier, vol. 369(C).
    3. Kang, Jidong & Wu, Zhuochun & Ng, Tsan Sheng & Su, Bin, 2023. "A stochastic-robust optimization model for inter-regional power system planning," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1234-1248.
    4. Barrera-Santana, J. & Sioshansi, Ramteen, 2023. "An optimization framework for capacity planning of island electricity systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    5. Han Wang & Zhenghui Fu & Shulan Wang & Wenjie Zhang, 2021. "Analysis of CO 2 Emissions in the Whole Production Process of Coal-Fired Power Plant," Sustainability, MDPI, vol. 13(19), pages 1-13, October.
    6. Domínguez, Ruth & Vitali, Sebastiano & Carrión, Miguel & Moriggia, Vittorio, 2021. "Analysing decarbonizing strategies in the European power system applying stochastic dominance constraints," Energy Economics, Elsevier, vol. 101(C).
    7. Kang, Jidong & Ng, Tsan Sheng & Su, Bin, 2020. "Optimizing electricity mix for CO2 emissions reduction: A robust input-output linear programming model," European Journal of Operational Research, Elsevier, vol. 287(1), pages 280-292.
    8. Zolfaghari, Saeed & Akbari, Tohid, 2018. "Bilevel transmission expansion planning using second-order cone programming considering wind investment," Energy, Elsevier, vol. 154(C), pages 455-465.
    9. Després, Jacques & Hadjsaid, Nouredine & Criqui, Patrick & Noirot, Isabelle, 2015. "Modelling the impacts of variable renewable sources on the power sector: Reconsidering the typology of energy modelling tools," Energy, Elsevier, vol. 80(C), pages 486-495.
    10. Bojana Škrbić & Željko Đurišić, 2023. "Novel Planning Methodology for Spatially Optimized RES Development Which Minimizes Flexibility Requirements for Their Integration into the Power System," Energies, MDPI, vol. 16(7), pages 1-34, April.
    11. Sander Claeys & Marta Vanin & Frederik Geth & Geert Deconinck, 2021. "Applications of optimization models for electricity distribution networks," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 10(5), September.
    12. M. Jenabi & S. M. T. Fatemi Ghomi & S. A. Torabi & Moeen Sammak Jalali, 2022. "An accelerated Benders decomposition algorithm for stochastic power system expansion planning using sample average approximation," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1304-1336, December.
    13. Irawan, Chandra Ade & Jones, Dylan & Hofman, Peter S. & Zhang, Lina, 2023. "Integrated strategic energy mix and energy generation planning with multiple sustainability criteria and hierarchical stakeholders," European Journal of Operational Research, Elsevier, vol. 308(2), pages 864-883.
    14. Kenjiro Yagi & Ramteen Sioshansi, 2023. "Simplifying capacity planning for electricity systems with hydroelectric and renewable generation," Computational Management Science, Springer, vol. 20(1), pages 1-28, December.
    15. Jiang, Sufan & Gao, Shan & Pan, Guangsheng & Zhao, Xin & Liu, Yu & Guo, Yasen & Wang, Sicheng, 2020. "A novel robust security constrained unit commitment model considering HVDC regulation," Applied Energy, Elsevier, vol. 278(C).
    16. Helistö, Niina & Kiviluoma, Juha & Morales-España, Germán & O’Dwyer, Ciara, 2021. "Impact of operational details and temporal representations on investment planning in energy systems dominated by wind and solar," Applied Energy, Elsevier, vol. 290(C).
    17. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    18. Rintamäki, Tuomas & Siddiqui, Afzal S. & Salo, Ahti, 2020. "Strategic offering of a flexible producer in day-ahead and intraday power markets," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1136-1153.
    19. Xiang, Yue & Guo, Yongtao & Wu, Gang & Liu, Junyong & Sun, Wei & Lei, Yutian & Zeng, Pingliang, 2022. "Low-carbon economic planning of integrated electricity-gas energy systems," Energy, Elsevier, vol. 249(C).
    20. Grimm, Veronika & Schewe, Lars & Schmidt, Martin & Zöttl, Gregor, 2017. "Uniqueness of market equilibrium on a network: A peak-load pricing approach," European Journal of Operational Research, Elsevier, vol. 261(3), pages 971-983.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:98:y:2021:i:c:s0140988321001511. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.