IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-48862-5.html
   My bibliography  Save this article

Multi-resource dynamic coordinated planning of flexible distribution network

Author

Listed:
  • Rui Wang

    (Tianjin University)

  • Haoran Ji

    (Tianjin University)

  • Peng Li

    (Tianjin University)

  • Hao Yu

    (Tianjin University)

  • Jinli Zhao

    (Tianjin University)

  • Liang Zhao

    (State Grid Tianjin Electric Power Company)

  • Yue Zhou

    (Cardiff University)

  • Jianzhong Wu

    (Cardiff University)

  • Linquan Bai

    (University of Tennessee)

  • Jinyue Yan

    (Mälardalen University)

  • Chengshan Wang

    (Tianjin University)

Abstract

The flexible distribution network presents a promising architecture to accommodate highly integrated distributed generators and increasing loads in an efficient and cost-effective way. The distribution network is characterised by flexible interconnections and expansions based on soft open points, which enables it to dispatch power flow over the entire system with enhanced controllability and compatibility. Herein, we propose a multi-resource dynamic coordinated planning method of flexible distribution network that allows allocation strategies to be determined over a long-term planning period. Additionally, we establish a probabilistic framework to address source-load uncertainties, which mitigates the security risks of voltage violations and line overloads. A practical distribution network is adopted for flexible upgrading based on soft open points, and its cost benefits are evaluated and compared with that of traditional planning approaches. By adjusting the acceptable violation probability in chance constraints, a trade-off between investment efficiency and operational security can be realised.

Suggested Citation

  • Rui Wang & Haoran Ji & Peng Li & Hao Yu & Jinli Zhao & Liang Zhao & Yue Zhou & Jianzhong Wu & Linquan Bai & Jinyue Yan & Chengshan Wang, 2024. "Multi-resource dynamic coordinated planning of flexible distribution network," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48862-5
    DOI: 10.1038/s41467-024-48862-5
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-48862-5
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-024-48862-5?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
    ---><---

    References listed on IDEAS

    as
    1. Khezri, Rahmat & Mahmoudi, Amin & Aki, Hirohisa, 2022. "Optimal planning of solar photovoltaic and battery storage systems for grid-connected residential sector: Review, challenges and new perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    2. Ehsan, Ali & Yang, Qiang, 2019. "State-of-the-art techniques for modelling of uncertainties in active distribution network planning: A review," Applied Energy, Elsevier, vol. 239(C), pages 1509-1523.
    3. Long, Chao & Wu, Jianzhong & Thomas, Lee & Jenkins, Nick, 2016. "Optimal operation of soft open points in medium voltage electrical distribution networks with distributed generation," Applied Energy, Elsevier, vol. 184(C), pages 427-437.
    4. Zwickl-Bernhard, Sebastian & Auer, Hans, 2021. "Open-source modeling of a low-carbon urban neighborhood with high shares of local renewable generation," Applied Energy, Elsevier, vol. 282(PA).
    5. Rahim, Sahar & Wang, Zhen & Ju, Ping, 2022. "Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review," Applied Energy, Elsevier, vol. 319(C).
    6. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    7. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Ding, Fei & Wu, Jianzhong, 2017. "An enhanced SOCP-based method for feeder load balancing using the multi-terminal soft open point in active distribution networks," Applied Energy, Elsevier, vol. 208(C), pages 986-995.
    8. Wang, Chengshan & Song, Guanyu & Li, Peng & Ji, Haoran & Zhao, Jinli & Wu, Jianzhong, 2017. "Optimal siting and sizing of soft open points in active electrical distribution networks," Applied Energy, Elsevier, vol. 189(C), pages 301-309.
    9. Wang, Rui & Li, Peng & Yu, Hao & Ji, Haoran & Xi, Wei & Wang, Chengshan, 2023. "Identification of critical uncertain factors of distribution networks with high penetration of photovoltaics and electric vehicles," Applied Energy, Elsevier, vol. 329(C).
    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. Li, Peng & Ji, Haoran & Yu, Hao & Zhao, Jinli & Wang, Chengshan & Song, Guanyu & Wu, Jianzhong, 2019. "Combined decentralized and local voltage control strategy of soft open points in active distribution networks," Applied Energy, Elsevier, vol. 241(C), pages 613-624.
    2. Irina I. Picioroaga & Andrei M. Tudose & Dorian O. Sidea & Constantin Bulac, 2022. "Supply Restoration in Active Distribution Networks Based on Soft Open Points with Embedded DC Microgrids," Mathematics, MDPI, vol. 10(2), pages 1-21, January.
    3. Bai, Linquan & Jiang, Tao & Li, Fangxing & Chen, Houhe & Li, Xue, 2018. "Distributed energy storage planning in soft open point based active distribution networks incorporating network reconfiguration and DG reactive power capability," Applied Energy, Elsevier, vol. 210(C), pages 1082-1091.
    4. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Wu, Jianzhong, 2018. "Quantified flexibility evaluation of soft open points to improve distributed generator penetration in active distribution networks based on difference-of-convex programming," Applied Energy, Elsevier, vol. 218(C), pages 338-348.
    5. Aithal, Avinash & Li, Gen & Wu, Jianzhong & Yu, James, 2018. "Performance of an electrical distribution network with Soft Open Point during a grid side AC fault," Applied Energy, Elsevier, vol. 227(C), pages 262-272.
    6. Ibrahim Diaaeldin & Shady Abdel Aleem & Ahmed El-Rafei & Almoataz Abdelaziz & Ahmed F. Zobaa, 2019. "Optimal Network Reconfiguration in Active Distribution Networks with Soft Open Points and Distributed Generation," Energies, MDPI, vol. 12(21), pages 1-31, November.
    7. Ghadi, Mojtaba Jabbari & Rajabi, Amin & Ghavidel, Sahand & Azizivahed, Ali & Li, Li & Zhang, Jiangfeng, 2019. "From active distribution systems to decentralized microgrids: A review on regulations and planning approaches based on operational factors," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    8. Zhenshan Zhu & Dichen Liu & Qingfen Liao & Fei Tang & Jun Jason Zhang & Huaiguang Jiang, 2018. "Optimal Power Scheduling for a Medium Voltage AC/DC Hybrid Distribution Network," Sustainability, MDPI, vol. 10(2), pages 1-22, January.
    9. Bastami, Houman & Shakarami, Mahmoud Reza & Doostizadeh, Meysam, 2021. "A decentralized cooperative framework for multi-area active distribution network in presence of inter-area soft open points," Applied Energy, Elsevier, vol. 300(C).
    10. Ji, Haoran & Wang, Chengshan & Li, Peng & Song, Guanyu & Wu, Jianzhong, 2018. "SOP-based islanding partition method of active distribution networks considering the characteristics of DG, energy storage system and load," Energy, Elsevier, vol. 155(C), pages 312-325.
    11. Escalera, Alberto & Prodanović, Milan & Castronuovo, Edgardo D. & Roldan-Perez, Javier, 2020. "Contribution of active management technologies to the reliability of power distribution networks," Applied Energy, Elsevier, vol. 267(C).
    12. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Ding, Fei & Wu, Jianzhong, 2017. "An enhanced SOCP-based method for feeder load balancing using the multi-terminal soft open point in active distribution networks," Applied Energy, Elsevier, vol. 208(C), pages 986-995.
    13. Qi, Qi & Wu, Jianzhong & Long, Chao, 2017. "Multi-objective operation optimization of an electrical distribution network with soft open point," Applied Energy, Elsevier, vol. 208(C), pages 734-744.
    14. Wu, Pan & Huang, Wentao & Tai, Nengling & Liang, Shuo, 2018. "A novel design of architecture and control for multiple microgrids with hybrid AC/DC connection," Applied Energy, Elsevier, vol. 210(C), pages 1002-1016.
    15. Zhang, Lu & Shen, Chen & Chen, Ying & Huang, Shaowei & Tang, Wei, 2018. "Coordinated allocation of distributed generation, capacitor banks and soft open points in active distribution networks considering dispatching results," Applied Energy, Elsevier, vol. 231(C), pages 1122-1131.
    16. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    17. Kim, Sunwoo & Choi, Yechan & Park, Joungho & Adams, Derrick & Heo, Seongmin & Lee, Jay H., 2024. "Multi-period, multi-timescale stochastic optimization model for simultaneous capacity investment and energy management decisions for hybrid Micro-Grids with green hydrogen production under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    18. 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.
    19. Scott, James & Ho, William & Dey, Prasanta K. & Talluri, Srinivas, 2015. "A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments," International Journal of Production Economics, Elsevier, vol. 166(C), pages 226-237.
    20. Minjiao Zhang & Simge Küçükyavuz & Saumya Goel, 2014. "A Branch-and-Cut Method for Dynamic Decision Making Under Joint Chance Constraints," Management Science, INFORMS, vol. 60(5), pages 1317-1333, May.

    More about this item

    Statistics

    Access and download statistics

    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:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48862-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.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.