IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i9p2200-d1388181.html
   My bibliography  Save this article

Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks

Author

Listed:
  • Byron Tasseff

    (Los Alamos National Laboratory, Los Alamos, NM 87545, USA)

  • Carleton Coffrin

    (Los Alamos National Laboratory, Los Alamos, NM 87545, USA)

  • Russell Bent

    (Los Alamos National Laboratory, Los Alamos, NM 87545, USA)

Abstract

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.

Suggested Citation

  • Byron Tasseff & Carleton Coffrin & Russell Bent, 2024. "Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks," Energies, MDPI, vol. 17(9), pages 1-21, May.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:9:p:2200-:d:1388181
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/9/2200/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/9/2200/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mitridati, Lesia & Kazempour, Jalal & Pinson, Pierre, 2020. "Heat and electricity market coordination: A scalable complementarity approach," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1107-1123.
    2. Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Liao, Siyang & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao, 2018. "Coordinated operation of gas-electricity integrated distribution system with multi-CCHP and distributed renewable energy sources," Applied Energy, Elsevier, vol. 211(C), pages 237-248.
    3. Farrokhifar, Meisam & Nie, Yinghui & Pozo, David, 2020. "Energy systems planning: A survey on models for integrated power and natural gas networks coordination," Applied Energy, Elsevier, vol. 262(C).
    4. DE WOLF, Daniel & SMEERS, Yves, 2000. "The gas transmission problem solved by an extension of the simplex algorithm," LIDAM Reprints CORE 1489, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Daniel De Wolf & Yves Smeers, 2000. "The Gas Transmission Problem Solved by an Extension of the Simplex Algorithm," Management Science, INFORMS, vol. 46(11), pages 1454-1465, November.
    Full references (including those not matched with items on IDEAS)

    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. Ratha, Anubhav & Pinson, Pierre & Le Cadre, Hélène & Virag, Ana & Kazempour, Jalal, 2023. "Moving from linear to conic markets for electricity," European Journal of Operational Research, Elsevier, vol. 309(2), pages 762-783.
    2. Duan, Jiandong & Liu, Fan & Yang, Yao, 2022. "Optimal operation for integrated electricity and natural gas systems considering demand response uncertainties," Applied Energy, Elsevier, vol. 323(C).
    3. Belderbos, Andreas & Valkaert, Thomas & Bruninx, Kenneth & Delarue, Erik & D’haeseleer, William, 2020. "Facilitating renewables and power-to-gas via integrated electrical power-gas system scheduling," Applied Energy, Elsevier, vol. 275(C).
    4. Yang, Hangbo & You, Pengcheng & Shang, Ce, 2021. "Distributed planning of electricity and natural gas networks and energy hubs," Applied Energy, Elsevier, vol. 282(PA).
    5. Liu, Rong-Peng & Sun, Wei & Yin, Wenqian & Zhou, Dali & Hou, Yunhe, 2021. "Extended convex hull-based distributed optimal energy flow of integrated electricity-gas systems," Applied Energy, Elsevier, vol. 287(C).
    6. Lars Schewe & Martin Schmidt & Johannes Thürauf, 2020. "Computing technical capacities in the European entry-exit gas market is NP-hard," Annals of Operations Research, Springer, vol. 295(1), pages 337-362, December.
    7. repec:cty:dpaper:10.1080/0013791x.2011.573615 is not listed on IDEAS
    8. Beyza, Jesus & Ruiz-Paredes, Hector F. & Garcia-Paricio, Eduardo & Yusta, Jose M., 2020. "Assessing the criticality of interdependent power and gas systems using complex networks and load flow techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    9. Daniel de Wolf, 2017. "Mathematical Properties of Formulations of the Gas Transmission Problem," Post-Print halshs-02396747, HAL.
    10. Liang, Yingzong & Hui, Chi Wai, 2018. "Convexification for natural gas transmission networks optimization," Energy, Elsevier, vol. 158(C), pages 1001-1016.
    11. Bao, Minglei & Hui, Hengyu & Ding, Yi & Sun, Xiaocong & Zheng, Chenghang & Gao, Xiang, 2023. "An efficient framework for exploiting operational flexibility of load energy hubs in risk management of integrated electricity-gas systems," Applied Energy, Elsevier, vol. 338(C).
    12. Mengying Xue & Tianhu Deng & Zuo‐Jun Max Shen, 2019. "Optimizing natural gas pipeline transmission with nonuniform elevation: A new initialization approach," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(7), pages 547-564, October.
    13. Xie, Shiwei & Hu, Zhijian & Wang, Jueying & Chen, Yuwei, 2020. "The optimal planning of smart multi-energy systems incorporating transportation, natural gas and active distribution networks," Applied Energy, Elsevier, vol. 269(C).
    14. Conrado Borraz-Sánchez & Dag Haugland, 2013. "Optimization methods for pipeline transportation of natural gas with variable specific gravity and compressibility," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 524-541, October.
    15. Zhou, Li & Liao, Zuwei & Wang, Jingdai & Jiang, Binbo & Yang, Yongrong & Du, Wenli, 2015. "Energy configuration and operation optimization of refinery fuel gas networks," Applied Energy, Elsevier, vol. 139(C), pages 365-375.
    16. repec:cty:dpaper:1464 is not listed on IDEAS
    17. Hong, Sung-Pil & Kim, Taegyoon & Lee, Subin, 2019. "A precision pump schedule optimization for the water supply networks with small buffers," Omega, Elsevier, vol. 82(C), pages 24-37.
    18. Dieckhoener, Caroline, 2010. "Simulating security of supply effects of the Nabucco and South Stream projects for the European natural gas market," EWI Working Papers 2010-7, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI), revised 21 Jan 2012.
    19. Caroline Dieckhöner, 2012. "Simulating Security of Supply Effects of the Nabucco and South Stream Projects for the European Natural Gas Market," The Energy Journal, , vol. 33(3), pages 153-182, July.
    20. Xie, Shiwei & Zheng, Jieyun & Hu, Zhijian & Wang, Jueying & Chen, Yuwei, 2020. "Urban multi-energy network optimization: An enhanced model using a two-stage bound-tightening approach," Applied Energy, Elsevier, vol. 277(C).
    21. Chen, Xi & Wang, Chengfu & Wu, Qiuwei & Dong, Xiaoming & Yang, Ming & He, Suoying & Liang, Jun, 2020. "Optimal operation of integrated energy system considering dynamic heat-gas characteristics and uncertain wind power," Energy, Elsevier, vol. 198(C).
    22. Song, Chenhui & Xiao, Jun & Zu, Guoqiang & Hao, Ziyuan & Zhang, Xinsong, 2021. "Security region of natural gas pipeline network system: Concept, method and application," Energy, Elsevier, vol. 217(C).

    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:gam:jeners:v:17:y:2024:i:9:p:2200-:d:1388181. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.