IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i10p4506-d1656487.html
   My bibliography  Save this article

A Pricing Strategy for Key Customers: A Method Considering Disaster Outage Compensation and System Stability Penalty

Author

Listed:
  • Seonghyeon Kim

    (School of Electrical Engineering, Korea University, Seoul 02841, Republic of Korea)

  • Yongju Son

    (School of Electrical Engineering, Korea University, Seoul 02841, Republic of Korea)

  • Hyeon Woo

    (School of Electrical Engineering, Korea University, Seoul 02841, Republic of Korea)

  • Xuehan Zhang

    (College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350116, China)

  • Sungyun Choi

    (School of Electrical Engineering, Korea University, Seoul 02841, Republic of Korea)

Abstract

When power system equipment fails due to disasters, resulting in the isolation of parts of the network, the loads within the isolated system cannot be guaranteed a continuous power supply. However, for critical loads—such as hospitals or data centers—continuous power supply is of utmost importance. While distributed energy resources (DERs) within the network can supply power to some loads, outages may lead to compensation and fairness issues regarding the unsupplied loads. In response, this study proposes a methodology to determine the appropriate power contract price for key customers by estimating the unsupplied power demand for critical loads in isolated networks and incorporating both outage compensation costs and voltage stability penalties. The microgrid under consideration comprises DERs—including electric vehicles (EVs), fuel cell electric vehicles (FCEVs), photovoltaic (PV) plants, and wind turbine (WT) plants—as well as controllable resources such as battery energy storage systems (BESS) and hydrogen energy storage systems (HESS). It serves both residential load clusters and critical loads associated with social infrastructure. The proposed methodology is structured in two stages. In normal operating conditions, optimal scheduling is simulated using second-order conic programming (SOCP). In the event of a fault, mixed-integer SOCP (MISOCP) is employed to determine the optimal load shedding strategy. A case study is conducted using the IEEE 123 bus test node system to simulate the outage compensation cost calculation and voltage penalty assessment processes. Based on this analysis, a contract price for key customers that considers both disaster-induced outages and voltage impacts is presented.

Suggested Citation

  • Seonghyeon Kim & Yongju Son & Hyeon Woo & Xuehan Zhang & Sungyun Choi, 2025. "A Pricing Strategy for Key Customers: A Method Considering Disaster Outage Compensation and System Stability Penalty," Sustainability, MDPI, vol. 17(10), pages 1-28, May.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:10:p:4506-:d:1656487
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/10/4506/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/10/4506/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xuehan Zhang & Yongju Son & Sungyun Choi, 2022. "Optimal Scheduling of Battery Energy Storage Systems and Demand Response for Distribution Systems with High Penetration of Renewable Energy Sources," Energies, MDPI, vol. 15(6), pages 1-18, March.
    2. Masoumeh Sharifpour & Mohammad Taghi Ameli & Hossein Ameli & Goran Strbac, 2023. "A Resilience-Oriented Approach for Microgrid Energy Management with Hydrogen Integration during Extreme Events," Energies, MDPI, vol. 16(24), pages 1-18, December.
    3. Zhang, Xuehan & Son, Yongju & Cheong, Taesu & Choi, Sungyun, 2022. "Affine-arithmetic-based microgrid interval optimization considering uncertainty and battery energy storage system degradation," Energy, Elsevier, vol. 242(C).
    4. Hyeon Woo & Yongju Son & Jintae Cho & Sungyun Choi, 2022. "Stochastic Second-Order Conic Programming for Optimal Sizing of Distributed Generator Units and Electric Vehicle Charging Stations," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    5. Alexandre F. M. Correia & Pedro Moura & Aníbal T. de Almeida, 2022. "Technical and Economic Assessment of Battery Storage and Vehicle-to-Grid Systems in Building Microgrids," Energies, MDPI, vol. 15(23), pages 1-23, November.
    6. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Fernández-Lobato, Lázuli & Jurado, Francisco, 2023. "Robust energy management in isolated microgrids with hydrogen storage and demand response," Applied Energy, Elsevier, vol. 345(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. Luiz Almeida & Ana Soares & Pedro Moura, 2023. "A Systematic Review of Optimization Approaches for the Integration of Electric Vehicles in Public Buildings," Energies, MDPI, vol. 16(13), pages 1-26, June.
    2. Tostado-Véliz, Marcos & Horrillo-Quintero, Pablo & García-Triviño, Pablo & Fernández-Ramírez, Luis M. & Jurado, Francisco, 2024. "Optimal sitting and sizing of hydrogen refilling stations in distribution networks under locational marginal prices," Applied Energy, Elsevier, vol. 374(C).
    3. Fei Feng & Xin Du & Qiang Si & Hao Cai, 2022. "Hybrid Game Optimization of Microgrid Cluster (MC) Based on Service Provider (SP) and Tiered Carbon Price," Energies, MDPI, vol. 15(14), pages 1-22, July.
    4. Lin, Yu-Hsiu & Shen, Ting-Yu, 2023. "Novel cell screening and prognosing based on neurocomputing-based multiday-ahead time-series forecasting for predictive maintenance of battery modules in frequency regulation-energy storage systems," Applied Energy, Elsevier, vol. 351(C).
    5. Huy, Truong Hoang Bao & Duy, Nguyen Thanh Minh & Phu, Pham Van & Le, Tien-Dat & Park, Seongkeun & Kim, Daehee, 2024. "Robust real-time energy management for a hydrogen refueling station using generative adversarial imitation learning," Applied Energy, Elsevier, vol. 373(C).
    6. Xu, Xuesong & Xu, Kai & Zeng, Ziyang & Tang, Jiale & He, Yuanxing & Shi, Guangze & Zhang, Tao, 2024. "Collaborative optimization of multi-energy multi-microgrid system: A hierarchical trust-region multi-agent reinforcement learning approach," Applied Energy, Elsevier, vol. 375(C).
    7. Qamar, Hafiz Ghulam Murtza & Guo, Xiaoqiang & Ahmad, Fareed, 2024. "Intelligent energy management system of hydrogen based microgrid empowered by AI optimization technique," Renewable Energy, Elsevier, vol. 237(PB).
    8. Zhu, Yansong & Liu, Jizhen & Hu, Yong & Xie, Yan & Zeng, Deliang & Li, Ruilian, 2024. "Distributionally robust optimization model considering deep peak shaving and uncertainty of renewable energy," Energy, Elsevier, vol. 288(C).
    9. Xie, Rui & Wei, Wei & Li, Mingxuan & Dong, ZhaoYang & Mei, Shengwei, 2023. "Sizing capacities of renewable generation, transmission, and energy storage for low-carbon power systems: A distributionally robust optimization approach," Energy, Elsevier, vol. 263(PA).
    10. Wang, Qi & Huang, Chunyi & Wang, Chengmin & Li, Kangping & Shafie-khah, Miadreza, 2025. "Risk-averse frequency regulation strategy of electric vehicle aggregator considering multiple uncertainties," Applied Energy, Elsevier, vol. 382(C).
    11. Wang, Sen & Li, Fengting & Zhang, Gaohang & Yin, Chunya, 2023. "Analysis of energy storage demand for peak shaving and frequency regulation of power systems with high penetration of renewable energy," Energy, Elsevier, vol. 267(C).
    12. Chen, Yuxin & Jiang, Yuewen, 2023. "Interval energy flow calculation method for electricity-heat-hydrogen integrated energy system considering the correlation between variables," Energy, Elsevier, vol. 263(PB).
    13. Huo, Shasha & Li, Qi & Pu, Yuchen & Xie, Shuqi & Chen, Weirong, 2024. "Low carbon dispatch method for hydrogen-containing integrated energy system considering seasonal carbon trading and energy sharing mechanism," Energy, Elsevier, vol. 308(C).
    14. Yin, Xin & Chen, Haoyong & Liang, Zipeng & Zhu, Yanjin, 2023. "A Flexibility-oriented robust transmission expansion planning approach under high renewable energy resource penetration," Applied Energy, Elsevier, vol. 351(C).
    15. Jincheng Tang & Xiaolan Li, 2025. "Two-Stage Dual-Level Dispatch Optimization Model for Multiple Virtual Power Plants with Electric Vehicles and Demand Response Based on a Stackelberg Game," Energies, MDPI, vol. 18(4), pages 1-22, February.
    16. Ștefan-Andrei Lupu & Dan Floricău, 2025. "Bidirectional Energy Transfer Between Electric Vehicle, Home, and Critical Load," Energies, MDPI, vol. 18(9), pages 1-19, April.
    17. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Mansouri, Seyed Amir & Zhou, Yuekuan & Jurado, Francisco, 2024. "A local electricity-hydrogen market model for industrial parks," Applied Energy, Elsevier, vol. 360(C).
    18. Lu, Na & Wang, Guangyan & Su, Chengguo & Ren, Zaimin & Peng, Xiaoyue & Sui, Quan, 2024. "Medium- and long-term interval optimal scheduling of cascade hydropower-photovoltaic complementary systems considering multiple uncertainties," Applied Energy, Elsevier, vol. 353(PA).
    19. Haelee Kim & Hyeon Woo & Yeunggurl Yoon & Hyun-Tae Kim & Yong Jung Kim & Moonho Kang & Xuehan Zhang & Sungyun Choi, 2024. "An Enhanced Continuation Power Flow Method Using Hybrid Parameterization," Sustainability, MDPI, vol. 16(17), pages 1-15, September.
    20. Zhang, Rongquan & Bu, Siqi & Li, Gangqiang, 2024. "Multi-market P2P trading of cooling–heating-power-hydrogen integrated energy systems: An equilibrium-heuristic online prediction optimization approach," Applied Energy, Elsevier, vol. 367(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:jsusta:v:17:y:2025:i:10:p:4506-:d:1656487. 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.