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Robust expansion planning and hardening strategy of meshed multi-energy distribution networks for resilience enhancement

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  • Li, Tingjun
  • Han, Xiaoqing
  • Wu, Wenchuan
  • Sun, Hongbin

Abstract

As an integrated energy system (IES) incorporated with electricity, gas, and heating networks, the meshed multi-energy distribution network (MMDN) can operate more economically with higher energy utilization efficiency. To achieve high reliability, MMDN is mesh-constructed and radial-operated, complicating the operation scenarios involved in planning. Existing coordinated planning models seldom consider network reconfiguration and hardening strategies collaboratively for extreme contingencies, which is not consistent with actual conditions. In addition, considering the multi-stage discreteness of the expansion planning problem, the existing robust algorithms may feedback invalid cuts. The neglect of such issues could introduce a momentous impact on the optimality of solutions. This paper presents a resiliency-oriented expansion planning and hardening model of MMDN, and the hierarchical algorithm is developed. Specifically, the model is formulated as a min–max-min optimization problem including investment and operation levels. The investment level problem optimizes planning schemes constrained with the robustness verification of the operation level problem. The operation level problem examines the operational cost and feeds back iterative information to the investment level. An additional cuts generation method is developed in the operation level, which effectively deals with invalid feedback information caused by the existing binary variable parameterization. Furthermore, accelerating strategies including infeasible region reduction, multi-cut feedback, and contingency set reduction are developed. To be solved by off-the-shelf solvers, the model is cast as a mixed-integer linear programming (MILP) problem by adopting the convex hull relaxation and linearization techniques for operational constraints with high accuracy. Numerical test results justify the effectiveness of the model.

Suggested Citation

  • Li, Tingjun & Han, Xiaoqing & Wu, Wenchuan & Sun, Hongbin, 2023. "Robust expansion planning and hardening strategy of meshed multi-energy distribution networks for resilience enhancement," Applied Energy, Elsevier, vol. 341(C).
    • Handle: RePEc:eee:appene:v:341:y:2023:i:c:s0306261923004300
    DOI: 10.1016/j.apenergy.2023.121066
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    References listed on IDEAS

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    1. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Xu, Xiandong & Yu, Xiaodan, 2016. "Optimal day-ahead scheduling of integrated urban energy systems," Applied Energy, Elsevier, vol. 180(C), pages 1-13.
    2. Zhang, Wei & Valencia, Andrea & Gu, Lixing & Zheng, Qipeng P. & Chang, Ni-Bin, 2020. "Integrating emerging and existing renewable energy technologies into a community-scale microgrid in an energy-water nexus for resilience improvement," Applied Energy, Elsevier, vol. 279(C).
    3. Shi, Qingxin & Li, Fangxing & Dong, Jin & Olama, Mohammed & Wang, Xiaofei & Winstead, Chris & Kuruganti, Teja, 2022. "Co-optimization of repairs and dynamic network reconfiguration for improved distribution system resilience," Applied Energy, Elsevier, vol. 318(C).
    4. Yildirim, Nurdan & Toksoy, Macit & Gokcen, Gulden, 2010. "Piping network design of geothermal district heating systems: Case study for a university campus," Energy, Elsevier, vol. 35(8), pages 3256-3262.
    5. Tobajas, Javier & Garcia-Torres, Felix & Roncero-Sánchez, Pedro & Vázquez, Javier & Bellatreche, Ladjel & Nieto, Emilio, 2022. "Resilience-oriented schedule of microgrids with hybrid energy storage system using model predictive control," Applied Energy, Elsevier, vol. 306(PB).
    6. Saravi, Vahid Sabzpoosh & Kalantar, Mohsen & Anvari-Moghaddam, Amjad, 2022. "Resilience-constrained expansion planning of integrated power–gas–heat distribution networks," Applied Energy, Elsevier, vol. 323(C).
    7. Wang, Y. & Rousis, A. Oulis & Strbac, G., 2022. "Resilience-driven optimal sizing and pre-positioning of mobile energy storage systems in decentralized networked microgrids," Applied Energy, Elsevier, vol. 305(C).
    8. Wang, Xu & Bie, Zhaohong & Liu, Fan & Kou, Yu, 2021. "Co-optimization planning of integrated electricity and district heating systems based on improved quadratic convex relaxation," Applied Energy, Elsevier, vol. 285(C).
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    Cited by:

    1. Zhu, Junpeng & Huang, Yong & Lu, Shuai & Shen, Mengya & Yuan, Yue, 2024. "Incorporating local uncertainty management into distribution system planning: An adaptive robust optimization approach," Applied Energy, Elsevier, vol. 363(C).
    2. Jing, Xiang & Qin, Wenping & Yao, Hongmin & Han, Xiaoqing & Wang, Peng, 2024. "Resilience-oriented planning strategy for the cyber-physical ADN under malicious attacks," Applied Energy, Elsevier, vol. 353(PA).

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