IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v327y2025ics0360544225020444.html
   My bibliography  Save this article

Optimal bidding strategy for integrated energy system participating in spot power market: A Wasserstein metric based DRO method

Author

Listed:
  • Shen, Weijie
  • Ding, Hongjian
  • Zeng, Ming
  • Zhang, Xiaochun

Abstract

The ongoing reforms in electricity markets have pushed energy producers and consumers to confront an increasingly uncertain market environment. The integrated energy systems (IES), designed to integrate a wide range of energy resources and carriers, have the potential to address the uncertainties of market trading. To this end, this paper innovatively introduces the Wasserstein metric-based distributionally robust optimization theory to construct a bidding model for IES participating in the spot power market. Firstly, the bidding mechanisms of the spot market across day-ahead, intraday and real-time market are analyzed, the decision-making keys for IES operators are proposed. Secondly, a data-driven Wasserstein metric ambiguity set is constructed to deal with price uncertainty, taking the minimization of expected cost and conditioned value-at-risk as objective, a distributionally robust optimization (DRO) bidding model is proposed for IES participating in the market. Thirdly, addressing the inherent complexity of the infinite-dimensional worst-case expectation problem, the proposed model is reformulated to a finite-dimensional mixed integer linear programming problem for computationally tractable, with rigorous reformulation process and final model presented in detail. Finally, taking the spot power market in Shandong Province, China, as an example, a case study is carried out to verify the feasibility and superiority of the proposed model. Comparison with stochastic programming and robust optimization show that the proposed model has better out-of-sample performance.

Suggested Citation

  • Shen, Weijie & Ding, Hongjian & Zeng, Ming & Zhang, Xiaochun, 2025. "Optimal bidding strategy for integrated energy system participating in spot power market: A Wasserstein metric based DRO method," Energy, Elsevier, vol. 327(C).
  • Handle: RePEc:eee:energy:v:327:y:2025:i:c:s0360544225020444
    DOI: 10.1016/j.energy.2025.136402
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225020444
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.136402?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Roald, Line A. & Pozo, David & Papavasiliou, Anthony & Molzahn, Daniel K. & Kazempour, Jalal & Conejo, Antonio, 2023. "Power systems optimization under uncertainty: a review of methods and applications," LIDAM Reprints CORE 3257, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Akbari, Ebrahim & Hooshmand, Rahmat-Allah & Gholipour, Mehdi & Parastegari, Moein, 2019. "Stochastic programming-based optimal bidding of compressed air energy storage with wind and thermal generation units in energy and reserve markets," Energy, Elsevier, vol. 171(C), pages 535-546.
    3. Neuhoff, Karsten & Richstein, Jörn C. & Kröger, Mats, 2023. "Reacting to changing paradigms: How and why to reform electricity markets," Energy Policy, Elsevier, vol. 180(C).
    4. Wang, Yuwei & Yang, Yuanjuan & Fei, Haoran & Song, Minghao & Jia, Mengyao, 2022. "Wasserstein and multivariate linear affine based distributionally robust optimization for CCHP-P2G scheduling considering multiple uncertainties," Applied Energy, Elsevier, vol. 306(PA).
    5. Bart P. G. Van Parys & Peyman Mohajerin Esfahani & Daniel Kuhn, 2021. "From Data to Decisions: Distributionally Robust Optimization Is Optimal," Management Science, INFORMS, vol. 67(6), pages 3387-3402, June.
    6. Pourmohammadi, Pardis & Saif, Ahmed, 2023. "Robust metamodel-based simulation-optimization approaches for designing hybrid renewable energy systems," Applied Energy, Elsevier, vol. 341(C).
    7. Wang, Yi & Zhang, Ning & Zhuo, Zhenyu & Kang, Chongqing & Kirschen, Daniel, 2018. "Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch," Applied Energy, Elsevier, vol. 210(C), pages 1141-1150.
    8. 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).
    9. Herding, Robert & Ross, Emma & Jones, Wayne R. & Charitopoulos, Vassilis M. & Papageorgiou, Lazaros G., 2023. "Stochastic programming approach for optimal day-ahead market bidding curves of a microgrid," Applied Energy, Elsevier, vol. 336(C).
    10. Fusco, Andrea & Gioffrè, Domenico & Francesco Castelli, Alessandro & Bovo, Cristian & Martelli, Emanuele, 2023. "A multi-stage stochastic programming model for the unit commitment of conventional and virtual power plants bidding in the day-ahead and ancillary services markets," Applied Energy, Elsevier, vol. 336(C).
    11. Yang Yu & Jianxiao Wang & Qixin Chen & Johannes Urpelainen & Qingguo Ding & Shuo Liu & Bing Zhang, 2023. "Decarbonization efforts hindered by China’s slow progress on electricity market reforms," Nature Sustainability, Nature, vol. 6(8), pages 1006-1015, August.
    12. Tahir, Muhammad Faizan & Haoyong, Chen & Guangze, Han, 2022. "Evaluating individual heating alternatives in integrated energy system by employing energy and exergy analysis," Energy, Elsevier, vol. 249(C).
    13. Wang, Jiexin & Wang, Song, 2023. "The effect of electricity market reform on energy efficiency in China," Energy Policy, Elsevier, vol. 181(C).
    14. Ning, Chao & You, Fengqi, 2019. "Data-driven Wasserstein distributionally robust optimization for biomass with agricultural waste-to-energy network design under uncertainty," Applied Energy, Elsevier, vol. 255(C).
    15. Karsten Neuhoff & Jörn C. Richstein & Mats Kröger, 2023. "Reacting to Changing Paradigms: How and Why to Reform Electricity Markets," DIW Berlin: Politikberatung kompakt, DIW Berlin, German Institute for Economic Research, volume 127, number pbk189.
    16. Mu, Yunfei & Wang, Congshan & Cao, Yan & Jia, Hongjie & Zhang, Qingzhu & Yu, Xiaodan, 2022. "A CVaR-based risk assessment method for park-level integrated energy system considering the uncertainties and correlation of energy prices," Energy, Elsevier, vol. 247(C).
    17. Tatiana Gabderakhmanova & Mattia Marinelli, 2022. "Multi-Energy System Demonstration Pilots on Geographical Islands: An Overview across Europe," Energies, MDPI, vol. 15(11), pages 1-26, May.
    18. Khaloie, Hooman & Anvari-Moghaddam, Amjad & Contreras, Javier & Siano, Pierluigi, 2021. "Risk-involved optimal operating strategy of a hybrid power generation company: A mixed interval-CVaR model," Energy, Elsevier, vol. 232(C).
    19. Khojasteh, Meysam & Faria, Pedro & Vale, Zita, 2022. "A robust model for aggregated bidding of energy storages and wind resources in the joint energy and reserve markets," Energy, Elsevier, vol. 238(PB).
    20. Shen, Weijie & Zeng, Bo & Zeng, Ming, 2023. "Multi-timescale rolling optimization dispatch method for integrated energy system with hybrid energy storage system," Energy, Elsevier, vol. 283(C).
    21. Skalyga, Mikhail & Amelin, Mikael & Wu, Qiuwei & Söder, Lennart, 2023. "Distributionally robust day-ahead combined heat and power plants scheduling with Wasserstein Metric," Energy, Elsevier, vol. 269(C).
    22. Jin, Xiaoyu & Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Yan, Zhiyu, 2022. "A Wasserstein metric-based distributionally robust optimization approach for reliable-economic equilibrium operation of hydro-wind-solar energy systems," Renewable Energy, Elsevier, vol. 196(C), pages 204-219.
    23. Fan, Wei & Ju, Liwei & Tan, Zhongfu & Li, Xiangguang & Zhang, Amin & Li, Xudong & Wang, Yueping, 2023. "Two-stage distributionally robust optimization model of integrated energy system group considering energy sharing and carbon transfer," Applied Energy, Elsevier, vol. 331(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. Silva-Rodriguez, Lina & Sanjab, Anibal & Fumagalli, Elena & Gibescu, Madeleine, 2024. "Light robust co-optimization of energy and reserves in the day-ahead electricity market," Applied Energy, Elsevier, vol. 353(PA).
    2. Fan, Guozhu & Peng, Chunhua & Wang, Xuekui & Wu, Peng & Yang, Yifan & Sun, Huijuan, 2024. "Optimal scheduling of integrated energy system considering renewable energy uncertainties based on distributionally robust adaptive MPC," Renewable Energy, Elsevier, vol. 226(C).
    3. Li, Weiwei & Qian, Tong & Zhao, Wei & Huang, Wenwei & Zhang, Yin & Xie, Xuehua & Tang, Wenhu, 2023. "Decentralized optimization for integrated electricity–heat systems with data center based energy hub considering communication packet loss," Applied Energy, Elsevier, vol. 350(C).
    4. Feng, Jie & Ran, Lun & Wang, Zhiyuan & Zhang, Mengling, 2024. "Optimal energy scheduling of virtual power plant integrating electric vehicles and energy storage systems under uncertainty," Energy, Elsevier, vol. 309(C).
    5. Khojasteh, Meysam & Faria, Pedro & Lezama, Fernando & Vale, Zita, 2023. "A hierarchy model to use local resources by DSO and TSO in the balancing market," Energy, Elsevier, vol. 267(C).
    6. Mohtavipour, Seyed Saeid, 2024. "Convex relaxation of two-stage network-constrained stochastic programming for CHP microgrid optimal scheduling," Energy, Elsevier, vol. 308(C).
    7. Luo, Yilun & Ahmadi, Esmaeil & McLellan, Benjamin Craig & Tezuka, Tetsuo, 2024. "A hybrid system dynamics model for power mix trajectory simulation in liberalized electricity markets considering carbon and capacity policy," Renewable Energy, Elsevier, vol. 233(C).
    8. Wang, Yuwei & Song, Minghao & Jia, Mengyao & Shi, Lin & Li, Bingkang, 2023. "TimeGAN based distributionally robust optimization for biomass-photovoltaic-hydrogen scheduling under source-load-market uncertainties," Energy, Elsevier, vol. 284(C).
    9. Sonnsjö, Hannes, 2024. "What we talk about when we talk about electricity: A thematic analysis of recent political debates on Swedish electricity supply," Energy Policy, Elsevier, vol. 187(C).
    10. Chaves, J. P. & Cossent, R. & Gómez San Román, T. & Linares, P. & Rivier, M., 2023. "An assessment of the European electricity market reform options and a pragmatic proposal," Cambridge Working Papers in Economics 2325, Faculty of Economics, University of Cambridge.
    11. Jimenez, I. Sanchez & Ribó-Pérez, D. & Cvetkovic, M. & Kochems, J. & Schimeczek, C. & de Vries, L.J., 2024. "Can an energy only market enable resource adequacy in a decarbonized power system? A co-simulation with two agent-based-models," Applied Energy, Elsevier, vol. 360(C).
    12. 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.
    13. Mei, Shufan & Tan, Qinliang & Liu, Yuan & Trivedi, Anupam & Srinivasan, Dipti, 2023. "Optimal bidding strategy for virtual power plant participating in combined electricity and ancillary services market considering dynamic demand response price and integrated consumption satisfaction," Energy, Elsevier, vol. 284(C).
    14. Fan, Wei & Fan, Ying & Yao, Xing & Yi, Bowen & Jiang, Dalin & Wu, Lin, 2024. "Distributed transaction optimization model of multi-integrated energy systems based on nash negotiation," Renewable Energy, Elsevier, vol. 225(C).
    15. Michał Pikus & Jarosław Wąs, 2024. "Predictive Modeling of Renewable Energy Purchase Prices Using Deep Learning Based on Polish Power Grid Data for Small Hybrid PV Microinstallations," Energies, MDPI, vol. 17(3), pages 1-12, January.
    16. Kim, Jun-Hyeok & Hwang, Jin Sol & Kim, Yun-Su, 2024. "An IGDT-WDRCC based optimal bidding strategy of VPP aggregators in new energy market considering multiple uncertainties," Energy, Elsevier, vol. 313(C).
    17. Hosseini Dolatabadi, Sayed Hamid & Bhuiyan, Tanveer Hossain & Chen, Yang & Morales, Jose Luis, 2024. "A stochastic game-theoretic optimization approach for managing local electricity markets with electric vehicles and renewable sources," Applied Energy, Elsevier, vol. 368(C).
    18. Cheng, Xiaobin & Liu, Pengfei & Zhu, Lei, 2024. "The impact of electricity market reform on renewable energy production," Energy Policy, Elsevier, vol. 194(C).
    19. Li, Junkai & Ge, Shaoyun & Liu, Hong & Zhang, Shida & Wang, Chengshan & Wang, Pengxiang, 2023. "Distribution locational pricing mechanisms for flexible interconnected distribution system with variable renewable energy generation," Applied Energy, Elsevier, vol. 335(C).
    20. Wang, Jian & Ilea, Valentin & Bovo, Cristian & Xie, Ning & Wang, Yong, 2023. "Optimal self-scheduling for a multi-energy virtual power plant providing energy and reserve services under a holistic market framework," Energy, Elsevier, vol. 278(PB).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:energy:v:327:y:2025:i:c:s0360544225020444. 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.journals.elsevier.com/energy .

    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.