IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i3p474-d1572873.html
   My bibliography  Save this article

Hybrid Optimization-Based Sequential Placement of DES in Unbalanced Active Distribution Networks Considering Multi-Scenario Operation

Author

Listed:
  • Ruihua Si

    (State Grid Henan Economic Research Institute, Zhengzhou 450052, China)

  • Xintong Yan

    (State Grid Henan Economic Research Institute, Zhengzhou 450052, China)

  • Wanxun Liu

    (State Grid Henan Economic Research Institute, Zhengzhou 450052, China)

  • Ping Zhang

    (State Grid Henan Economic Research Institute, Zhengzhou 450052, China)

  • Mengdi Wang

    (Offshore Wind Power Research Institute, Shanghai University of Electric Power, Shanghai 200090, China)

  • Fengyong Li

    (Offshore Wind Power Research Institute, Shanghai University of Electric Power, Shanghai 200090, China)

  • Jiajia Yang

    (College of Science and Engineering, James Cook University, Townsville 4811, Australia)

  • Xiangjing Su

    (Offshore Wind Power Research Institute, Shanghai University of Electric Power, Shanghai 200090, China)

Abstract

The increasing penetration of distributed generation (DG) brings about great economic and environmental benefits, while also negatively affecting the operation of distribution networks due to its high intermittency. Although distributed energy storage (DES) can effectively deal with the problems caused by massive DG penetrations by decoupling the generation and consumption of electricity, the placement of DES significantly determines the effectiveness of its capabilities. Unfortunately, existing DES placement studies are commonly based on a balanced network model, whereas practical distribution networks are unbalanced. In addition, existing DES placement studies are mostly based on an extreme scenario and rarely consider the operational complexity resulting from the uncertainties of DGs and loads. To address the aforementioned challenges, this paper proposes a hierarchical and sequential DES placement strategy in distribution networks by considering multi-scenario operations. Specifically, the proposed hierarchical framework for DES placement includes three sequential layers: outer, inter, and inner. In the outer layer, a multi-scenario comprehensive loss sensitivity index (MSCLSI) is first introduced to search for the most effective DES placement location. Subsequently, the sizing and scheduling of DES for the selected location are conducted through coordinated optimization across the inter and inner layers, which can be solved using a hybrid method combining particle swarm optimization and second-order cone programming (PSO-SOCP). Finally, a series of detailed simulations are carried out over the IEEE-33 test system and the experimental results demonstrate that the proposed scheme can provide significant effectiveness and superiority compared to the state-of-the-art schemes.

Suggested Citation

  • Ruihua Si & Xintong Yan & Wanxun Liu & Ping Zhang & Mengdi Wang & Fengyong Li & Jiajia Yang & Xiangjing Su, 2025. "Hybrid Optimization-Based Sequential Placement of DES in Unbalanced Active Distribution Networks Considering Multi-Scenario Operation," Energies, MDPI, vol. 18(3), pages 1-16, January.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:3:p:474-:d:1572873
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/3/474/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/3/474/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. João Fausto L. de Oliveira & Paulo S. G. de Mattos Neto & Hugo Valadares Siqueira & Domingos S. de O. Santos & Aranildo R. Lima & Francisco Madeiro & Douglas A. P. Dantas & Mariana de Morais Cavalcant, 2023. "Forecasting Methods for Photovoltaic Energy in the Scenario of Battery Energy Storage Systems: A Comprehensive Review," Energies, MDPI, vol. 16(18), pages 1-20, September.
    2. Lianling Ren & Wei Liao & Jun Chen, 2024. "Systematic Design and Implementation Method of Battery-Energy Comprehensive Management Platform in Charging and Swapping Scenarios," Energies, MDPI, vol. 17(5), pages 1-13, March.
    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. Lumbumba Taty-Etienne Nyamayoka & Lesedi Masisi & David Dorrell & Shuo Wang, 2025. "Techno-Economic Feasibility and Optimal Design Approach of Grid-Connected Hybrid Power Generation Systems for Electric Vehicle Battery Swapping Station," Energies, MDPI, vol. 18(5), pages 1-30, March.
    2. Yisen Niu & Ying Su & Ping Tang & Qian Wang & Yong Sun & Jifeng Song, 2025. "Estimation of Solar Irradiance Under Cloudy Weather Based on Solar Radiation Model and Ground-Based Cloud Image," Energies, MDPI, vol. 18(3), pages 1-21, February.

    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:18:y:2025:i:3:p:474-:d:1572873. 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.