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ORIGINAL RESEARCH article

Front. Energy Res.
Sec. Sustainable Energy Systems
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1505582
This article is part of the Research Topic Advanced Data-Driven Uncertainty Optimization for Planning, Operation, and Analysis of Renewable Power Systems View all 11 articles

Planning of Distributed Energy Storage Considering Extreme Weather with the Coordination of Transmission and Distribution Systems

Provisionally accepted
Yawei Xue Yawei Xue 1*Ke Zhang Ke Zhang 2*Zhidong Wang Zhidong Wang 1*Guodong Guo Guodong Guo 1*Dong Liu Dong Liu 1*Rui Shi Rui Shi 2*Shengjin Huang Shengjin Huang 3
  • 1 State Grid Economic and Technological Research Institute Co., Ltd, Beijing, China
  • 2 State Grid Corporation of China (SGCC), Beijing, Beijing Municipality, China
  • 3 Xi'an Jiaotong University, Xi'an, China

The final, formatted version of the article will be published soon.

    As the penetration level of renewable energy is continuously growing, it is essential for transmission and distribution system operators to collaborate on optimizing the siting and sizing of distributed energy storage to enhance the operational flexibility and economic efficiency. Given the frequent occurrence of extreme weather in recent years, the planning should also account for such factors. Hence, a planning method of distributed energy storage considering extreme weather with the coordination of transmission and distribution systems is proposed. Firstly, a Gaussian mixture modelbased chance constraint is established to describe the uncertainty of wind and solar power, ensuring high confidence that the bus voltage of the distribution system is within a safe range. Secondly, aiming to maximize the social welfare, a bi-level planning model for distributed energy storage is developed. The upper-level addresses the siting and sizing issues of distributed energy storage, while the lower-level characterizes the day-ahead clearing problem of power market. By leveraging Karush-Kuhn-Tucker (KKT) conditions and linearization techniques, the bi-level model is transformed into a single-level mixed integer linear programming model that is easier to solve. Finally, numerical analysis is conducted on a modified IEEE 24-node system combined with two IEEE 33-node systems. The case study verifies the effectiveness of the proposed model.

    Keywords: transmission and distribution coordination, Bi-level optimization, Energy storage sizing and siting, Market clearing, uncertainty, extreme weather

    Received: 03 Oct 2024; Accepted: 06 Nov 2024.

    Copyright: © 2024 Xue, Zhang, Wang, Guo, Liu, Shi and Huang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Yawei Xue, State Grid Economic and Technological Research Institute Co., Ltd, Beijing, China
    Ke Zhang, State Grid Corporation of China (SGCC), Beijing, 100031, Beijing Municipality, China
    Zhidong Wang, State Grid Economic and Technological Research Institute Co., Ltd, Beijing, China
    Guodong Guo, State Grid Economic and Technological Research Institute Co., Ltd, Beijing, China
    Dong Liu, State Grid Economic and Technological Research Institute Co., Ltd, Beijing, China
    Rui Shi, State Grid Corporation of China (SGCC), Beijing, 100031, Beijing Municipality, China

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