IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v386y2025ics0306261925002946.html
   My bibliography  Save this article

A data-driven hybrid robust optimization approach for microgrid operators in the energy reserve market considering different wind power producers’ strategies

Author

Listed:
  • Xiao, Guowei
  • Zhang, Miao
  • Huang, Weiqiang
  • Mo, Zihao
  • Xie, Haishun
  • Tang, Xiongmin

Abstract

In recent years, an increasing number of studies have indicated that wind power producers (WPP) have the potential to provide reserve capacity, enabling WPP to profit in the reserve market. However, the inherent uncertainty of wind power may affect the stability of this service. Therefore, WPP need to develop capacity strategies that account for the uncertainty of wind power while also serving the microgrids (MG). Moreover, inappropriate allocation of reserve capacity within the MG may lead to increased total operational costs. To address this issue, this paper proposes a new energy management framework aimed at optimizing the joint scheduling of MG in the day-ahead energy reserve market. Specifically, the information gap decision theory (IGDT) method is employed to model the capacity strategies of WPP while considering wind power uncertainty, and data-driven distributionally robust optimization (DDRO) techniques are utilized to determine the optimal reserved reserve capacity allocation for the MG. Experimental results demonstrate that different strategies significantly impact the trading of MG in the energy reserve market, and an analysis of the risk-return profiles of WPP under various strategies is provided. Additionally, the DDRO reduces the conservativeness of the results while ensuring a certain level of robustness.

Suggested Citation

  • Xiao, Guowei & Zhang, Miao & Huang, Weiqiang & Mo, Zihao & Xie, Haishun & Tang, Xiongmin, 2025. "A data-driven hybrid robust optimization approach for microgrid operators in the energy reserve market considering different wind power producers’ strategies," Applied Energy, Elsevier, vol. 386(C).
    • Handle: RePEc:eee:appene:v:386:y:2025:i:c:s0306261925002946
    DOI: 10.1016/j.apenergy.2025.125564
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925002946
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.125564?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhai, Junyi & Wang, Sheng & Guo, Lei & Jiang, Yuning & Kang, Zhongjian & Jones, Colin N., 2022. "Data-driven distributionally robust joint chance-constrained energy management for multi-energy microgrid," Applied Energy, Elsevier, vol. 326(C).
    2. Quashie, Mike & Marnay, Chris & Bouffard, François & Joós, Géza, 2018. "Optimal planning of microgrid power and operating reserve capacity," Applied Energy, Elsevier, vol. 210(C), pages 1229-1236.
    3. Zhou, Siyu & Han, Yang & Zalhaf, Amr S. & Lehtonen, Matti & Darwish, Mohamed M.F. & Mahmoud, Karar, 2024. "A novel stochastic multistage dispatching model of hybrid battery-electric vehicle-supercapacitor storage system to minimize three-phase unbalance," Energy, Elsevier, vol. 296(C).
    4. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    5. Nikzad, Mehdi & Samimi, Abouzar, 2021. "Integration of designing price-based demand response models into a stochastic bi-level scheduling of multiple energy carrier microgrids considering energy storage systems," Applied Energy, Elsevier, vol. 282(PA).
    6. Zhou, Kaile & Fei, Zhineng & Hu, Rong, 2023. "Hybrid robust decentralized optimization of emission-aware multi-energy microgrids considering multiple uncertainties," Energy, Elsevier, vol. 265(C).
    7. Edmunds, Calum & Martín-Martínez, Sergio & Browell, Jethro & Gómez-Lázaro, Emilio & Galloway, Stuart, 2019. "On the participation of wind energy in response and reserve markets in Great Britain and Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    8. Dai, Xuemei & Li, Yaping & Zhang, Kaifeng & Feng, Wei, 2020. "A robust offering strategy for wind producers considering uncertainties of demand response and wind power," Applied Energy, Elsevier, vol. 279(C).
    9. Rezaei, Navid & Khazali, Amirhossein & Mazidi, Mohammadreza & Ahmadi, Abdollah, 2020. "Economic energy and reserve management of renewable-based microgrids in the presence of electric vehicle aggregators: A robust optimization approach," Energy, Elsevier, vol. 201(C).
    10. Ma, Yunfeng & Zhang, Chao & Mi, Zengqiang & Zhang, Long & Parisio, Alessandra, 2024. "Secondary flexibility market mechanism design and response behavior analysis among multi-microgrids with high proportional BTM-RERs," Applied Energy, Elsevier, vol. 367(C).
    11. Wu, Xiong & Zhao, Wencheng & Li, Haoyu & Liu, Bingwen & Zhang, Ziyu & Wang, Xiuli, 2021. "Multi-stage stochastic programming based offering strategy for hydrogen fueling station in joint energy, reserve markets," Renewable Energy, Elsevier, vol. 180(C), pages 605-615.
    12. Zhou, Siyu & Han, Yang & Mahmoud, Karar & Darwish, Mohamed M.F. & Lehtonen, Matti & Yang, Ping & Zalhaf, Amr S., 2023. "A novel unified planning model for distributed generation and electric vehicle charging station considering multi-uncertainties and battery degradation," Applied Energy, Elsevier, vol. 348(C).
    13. Fazlalipour, Pary & Ehsan, Mehdi & Mohammadi-Ivatloo, Behnam, 2019. "Risk-aware stochastic bidding strategy of renewable micro-grids in day-ahead and real-time markets," Energy, Elsevier, vol. 171(C), pages 689-700.
    14. Mazidi, Mohammadreza & Monsef, Hassan & Siano, Pierluigi, 2016. "Robust day-ahead scheduling of smart distribution networks considering demand response programs," Applied Energy, Elsevier, vol. 178(C), pages 929-942.
    15. Kim, James Hyungkwan & Kahrl, Fredrich & Mills, Andrew & Wiser, Ryan & Montañés, Cristina Crespo & Gorman, Will, 2023. "Economic evaluation of variable renewable energy participation in U.S. ancillary services markets," Utilities Policy, Elsevier, vol. 82(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lei Zhang & Yuxing Yuan & Su Yan & Hang Cao & Tao Du, 2025. "Advances in Modeling and Optimization of Intelligent Power Systems Integrating Renewable Energy in the Industrial Sector: A Multi-Perspective Review," Energies, MDPI, vol. 18(10), pages 1-50, May.

    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. Qiu, Haifeng & Vinod, Ashwin & Lu, Shuai & Gooi, Hoay Beng & Pan, Guangsheng & Zhang, Suhan & Veerasamy, Veerapandiyan, 2023. "Decentralized mixed-integer optimization for robust integrated electricity and heat scheduling," Applied Energy, Elsevier, vol. 350(C).
    2. Jun Dong & Yuanyuan Wang & Xihao Dou & Zhengpeng Chen & Yaoyu Zhang & Yao Liu, 2021. "Research on Decision Optimization Model of Microgrid Participating in Spot Market Transaction," Sustainability, MDPI, vol. 13(12), pages 1-26, June.
    3. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    4. Park, Sung-Won & Yu, Jung-Un & Lee, Jin-Wook & Son, Sung-Yong, 2024. "A comprehensive review of battery-based power service applications considering degradation: Research status and model integration," Applied Energy, Elsevier, vol. 374(C).
    5. Li, Bingkang & Zhao, Huiru & Wang, Xuejie & Zhao, Yihang & Zhang, Yuanyuan & Lu, Hao & Wang, Yuwei, 2022. "Distributionally robust offering strategy of the aggregator integrating renewable energy generator and energy storage considering uncertainty and connections between the mid-to-long-term and spot elec," Renewable Energy, Elsevier, vol. 201(P1), pages 400-417.
    6. Matamala, Yolanda & Feijoo, Felipe, 2021. "A two-stage stochastic Stackelberg model for microgrid operation with chance constraints for renewable energy generation uncertainty," Applied Energy, Elsevier, vol. 303(C).
    7. Mazidi, Mohammadreza & Rezaei, Navid & Ghaderi, Abdolsalam, 2019. "Simultaneous power and heat scheduling of microgrids considering operational uncertainties: A new stochastic p-robust optimization approach," Energy, Elsevier, vol. 185(C), pages 239-253.
    8. Yang, Peiwen & Dong, Jun & Lin, Jin & Liu, Yao & Fang, Debin, 2021. "Analysis of offering behavior of generation-side integrated energy aggregator in electricity market:A Bayesian evolutionary approach," Energy, Elsevier, vol. 228(C).
    9. Yang, Zhichun & Tian, Hao & Min, Huaidong & Yang, Fan & Hu, Wei & Su, Lei & SaeidNahaei, Sanam, 2023. "Optimal microgrid programming based on an energy storage system, price-based demand response, and distributed renewable energy resources," Utilities Policy, Elsevier, vol. 80(C).
    10. Cao, Zehao & Li, Zhengshuo & Yang, Chang, 2025. "Credible joint chance-constrained low-carbon energy Management for Multi-energy Microgrids," Applied Energy, Elsevier, vol. 377(PA).
    11. Jun Dong & Yaoyu Zhang & Yuanyuan Wang & Yao Liu, 2021. "A Two-Stage Optimal Dispatching Model for Micro Energy Grid Considering the Dual Goals of Economy and Environmental Protection under CVaR," Sustainability, MDPI, vol. 13(18), pages 1-28, September.
    12. Bodong, Song & Wiseong, Jin & Chengmeng, Li & Khakichi, Aroos, 2023. "Economic management and planning based on a probabilistic model in a multi-energy market in the presence of renewable energy sources with a demand-side management program," Energy, Elsevier, vol. 269(C).
    13. Shaterabadi, Mohammad & Ahmadi, Shahab & Ahmadi Jirdehi, Mehdi, 2024. "Stochastic energy planning of a deltoid structure of interconnected multilateral grids by considering hydrogen station and demand response programs," Applied Energy, Elsevier, vol. 375(C).
    14. Yu, Min Gyung & Pavlak, Gregory S., 2023. "Risk-aware sizing and transactive control of building portfolios with thermal energy storage," Applied Energy, Elsevier, vol. 332(C).
    15. Ahmadi, Seyed Ehsan & Sadeghi, Delnia & Marzband, Mousa & Abusorrah, Abdullah & Sedraoui, Khaled, 2022. "Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies," Energy, Elsevier, vol. 245(C).
    16. Silva, Ana R. & Pousinho, H.M.I. & Estanqueiro, Ana, 2022. "A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets," Energy, Elsevier, vol. 258(C).
    17. Gao, Yang & Ai, Qian & He, Xing & Fan, Songli, 2023. "Coordination for regional integrated energy system through target cascade optimization," Energy, Elsevier, vol. 276(C).
    18. Ye, Jin & Shuai, Qilin & Hua, Qingsong, 2025. "Dynamic programming-based low-carbon and economic scheduling of integrated energy system," Energy, Elsevier, vol. 322(C).
    19. Zhang, Zhenwei & Wang, Chengfu & Wu, Qiuwei & Dong, Xiaoming, 2024. "Optimal dispatch for cross-regional integrated energy system with renewable energy uncertainties: A unified spatial-temporal cooperative framework," Energy, Elsevier, vol. 292(C).
    20. Dong, Xiao-Jian & Shen, Jia-Ni & Ma, Zi-Feng & He, Yi-Jun, 2025. "Stochastic optimization of integrated electric vehicle charging stations under photovoltaic uncertainty and battery power constraints," Energy, Elsevier, vol. 314(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:eee:appene:v:386:y:2025:i:c:s0306261925002946. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.