IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i13p1998-d1424427.html
   My bibliography  Save this article

Topology Design and Operation of Distribution Network Based on Multi-Objective Framework and Heuristic Strategies

Author

Listed:
  • Qingxia Li

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

  • Shengjun Huang

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

  • Xueyang Zhang

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

  • Wenhua Li

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

  • Rui Wang

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

  • Tao Zhang

    (College of Systems Engineering, National University of Defense Technology, Changsha 410073, China)

Abstract

This work elucidates a methodological approach employed in the process of planning the expansion of distribution network (DN) lines, wherein the amalgamation of system reconfiguration capabilities with operational equilibrium and reliability is paramount. The expansion proposals for the DN and the radial operation schemes post-expansion are encompassed. We formulate a bi-objective DN planning optimization model that concurrently addresses resource optimization configuration and operational optimization. Subsequently, the NSGA-II algorithm is employed to solve the optimization model, providing a coordinated presentation of multiple alternative solutions. However, this problem diverges from conventional bi-objective optimization problems due to its nature as a bi-objective optimization problem with embedded sub-optimization problem, consequently imposing a substantial computational burden. To address this issue, heuristic algorithms are designed to optimize system operational configuration, which is regarded as a sub-optimization problem. The proposed metric, model, and algorithms are validated on two case studies using the IEEE 33-bus and 70-bus test systems. Notably, the proposed method achieves solution efficiency by over 200 times compared to existing methods.

Suggested Citation

  • Qingxia Li & Shengjun Huang & Xueyang Zhang & Wenhua Li & Rui Wang & Tao Zhang, 2024. "Topology Design and Operation of Distribution Network Based on Multi-Objective Framework and Heuristic Strategies," Mathematics, MDPI, vol. 12(13), pages 1-21, June.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:1998-:d:1424427
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/13/1998/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/13/1998/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ma, Mingtao & Huang, Huijun & Song, Xiaoling & Peña-Mora, Feniosky & Zhang, Zhe & Chen, Jie, 2022. "Optimal sizing and operations of shared energy storage systems in distribution networks: A bi-level programming approach," Applied Energy, Elsevier, vol. 307(C).
    2. Hussain, Akhtar & Bui, Van-Hai & Kim, Hak-Man, 2019. "Microgrids as a resilience resource and strategies used by microgrids for enhancing resilience," Applied Energy, Elsevier, vol. 240(C), pages 56-72.
    3. Abedi, Amin & Gaudard, Ludovic & Romerio, Franco, 2019. "Review of major approaches to analyze vulnerability in power system," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 153-172.
    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. Zhang, Dongdong & Li, Chunjiao & Goh, Hui Hwang & Ahmad, Tanveer & Zhu, Hongyu & Liu, Hui & Wu, Thomas, 2022. "A comprehensive overview of modeling approaches and optimal control strategies for cyber-physical resilience in power systems," Renewable Energy, Elsevier, vol. 189(C), pages 1383-1406.
    2. Hussain Abdalla Sajwani & Bassel Soudan & Abdul Ghani Olabi, 2024. "Empowering Sustainability: Understanding Determinants of Consumer Investment in Microgrid Technology in the UAE," Energies, MDPI, vol. 17(9), pages 1-28, May.
    3. Deng Xu & Yong Long, 2019. "The Impact of Government Subsidy on Renewable Microgrid Investment Considering Double Externalities," Sustainability, MDPI, vol. 11(11), pages 1-15, June.
    4. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Saad Mekhilef & Mehdi Seyedmahmoudian & Alex Stojcevski & Ibrahim Alhamrouni, 2024. "AI Applications to Enhance Resilience in Power Systems and Microgrids—A Review," Sustainability, MDPI, vol. 16(12), pages 1-35, June.
    5. Antoine Boche & Clément Foucher & Luiz Fernando Lavado Villa, 2022. "Understanding Microgrid Sustainability: A Systemic and Comprehensive Review," Energies, MDPI, vol. 15(8), pages 1-29, April.
    6. Soheil Mohseni & Alan C. Brent & Daniel Burmester, 2020. "Community Resilience-Oriented Optimal Micro-Grid Capacity Expansion Planning: The Case of Totarabank Eco-Village, New Zealand," Energies, MDPI, vol. 13(15), pages 1-29, August.
    7. Huang, Chunjun & Zong, Yi & You, Shi & Træholt, Chresten & Zheng, Yi & Wang, Jiawei & Zheng, Zixuan & Xiao, Xianyong, 2023. "Economic and resilient operation of hydrogen-based microgrids: An improved MPC-based optimal scheduling scheme considering security constraints of hydrogen facilities," Applied Energy, Elsevier, vol. 335(C).
    8. Tang, Daogui & Fang, Yi-Ping & Zio, Enrico, 2023. "Vulnerability analysis of demand-response with renewable energy integration in smart grids to cyber attacks and online detection methods," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    9. Zou, Qiling & Chen, Suren, 2019. "Enhancing resilience of interdependent traffic-electric power system," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    10. Felix Garcia-Torres & Ascension Zafra-Cabeza & Carlos Silva & Stephane Grieu & Tejaswinee Darure & Ana Estanqueiro, 2021. "Model Predictive Control for Microgrid Functionalities: Review and Future Challenges," Energies, MDPI, vol. 14(5), pages 1-26, February.
    11. Zhang, Shizhong & Pei, Wei & Xiao, Hao & Yang, Yanhong & Ye, Hua & Kong, Li, 2020. "Enhancing the survival time of multiple islanding microgrids through composable modular energy router after natural disasters," Applied Energy, Elsevier, vol. 270(C).
    12. Saqib Iqbal & Kamyar Mehran, 2022. "A Day-Ahead Energy Management for Multi MicroGrid System to Optimize the Energy Storage Charge and Grid Dependency—A Comparative Analysis," Energies, MDPI, vol. 15(11), pages 1-19, June.
    13. Ahmadi, Somayeh & Saboohi, Yadollah & Vakili, Ali, 2021. "Frameworks, quantitative indicators, characters, and modeling approaches to analysis of energy system resilience: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    14. Han, Ouzhu & Ding, Tao & Zhang, Xiaosheng & Mu, Chenggang & He, Xinran & Zhang, Hongji & Jia, Wenhao & Ma, Zhoujun, 2023. "A shared energy storage business model for data center clusters considering renewable energy uncertainties," Renewable Energy, Elsevier, vol. 202(C), pages 1273-1290.
    15. Baohong Jin & Zhichao Liu & Yichuan Liao, 2023. "Exploring the Impact of Regional Integrated Energy Systems Performance by Energy Storage Devices Based on a Bi-Level Dynamic Optimization Model," Energies, MDPI, vol. 16(6), pages 1-21, March.
    16. Pere Ariza-Montobbio & Susana Herrero Olarte, 2021. "Socio-metabolic profiles of electricity consumption along the rural–urban continuum of Ecuador: Whose energy sovereignty?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 7961-7995, May.
    17. Zhaonian Ye & Yongzhen Wang & Kai Han & Changlu Zhao & Juntao Han & Yilin Zhu, 2023. "Bi-Objective Optimization and Emergy Analysis of Multi-Distributed Energy System Considering Shared Energy Storage," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    18. Liu, Hanchen & Wang, Chong & Ju, Ping & Li, Hongyu, 2022. "A sequentially preventive model enhancing power system resilience against extreme-weather-triggered failures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    19. Younesi, Abdollah & Shayeghi, Hossein & Wang, Zongjie & Siano, Pierluigi & Mehrizi-Sani, Ali & Safari, Amin, 2022. "Trends in modern power systems resilience: State-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    20. Wu, Raphael & Sansavini, Giovanni, 2020. "Integrating reliability and resilience to support the transition from passive distribution grids to islanding microgrids," Applied Energy, Elsevier, vol. 272(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:jmathe:v:12:y:2024:i:13:p:1998-:d:1424427. 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.