IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v314y2025ics0360544224039094.html

A stochastic Stackelberg problem with long-term investment decisions in Power-To-X technologies for multi-energy microgrids

Author

Listed:
  • Matamala, Yolanda
  • Das, Tapas K.
  • Feijoo, Felipe

Abstract

Technologies providing flexibility options to power systems, such as Power-To-X (PtX) technologies, have become more important with the increasing deployment of distributed energy resources, particularly microgrids. However, uncertainty in renewable resources creates ambiguity regarding the necessary PtX capacity to install. This paper proposes a two-stage stochastic Stackelberg approach for multi-energy microgrids, focusing on long-term investment decisions in PtX technologies and hourly operational strategies. The Stackelberg problem considers microgrids as leaders (upper level) and the independent system operator as a follower (lower level). In the first stage, investment levels for various PtX technologies are determined as one-time decisions. The second stage focuses on hourly operational decisions, including the integration of microgrids with the independent system operator with marginal endogenous prices. The results provide insights into how uncertainty in renewable generation and electric battery levels affect investment levels. Larger hydrogen and thermal storage volumes lead to more flexible and self-sufficient microgrid systems. In scenarios with higher flexibility, microgrids can: (1) satisfy up to 10% of the independent system operator demand using renewable electricity and (2) regulate supply variability by storing excess generation during peak periods and releasing it during low generation periods.

Suggested Citation

  • Matamala, Yolanda & Das, Tapas K. & Feijoo, Felipe, 2025. "A stochastic Stackelberg problem with long-term investment decisions in Power-To-X technologies for multi-energy microgrids," Energy, Elsevier, vol. 314(C).
    • Handle: RePEc:eee:energy:v:314:y:2025:i:c:s0360544224039094
    DOI: 10.1016/j.energy.2024.134131
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224039094
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.134131?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. Flores, Francisco & Feijoo, Felipe & DeStephano, Paelina & Herc, Luka & Pfeifer, Antun & Duić, Neven, 2024. "Assessment of the impacts of renewable energy variability in long-term decarbonization strategies," Applied Energy, Elsevier, vol. 368(C).
    2. Yang, Jun & Su, Changqi, 2021. "Robust optimization of microgrid based on renewable distributed power generation and load demand uncertainty," Energy, Elsevier, vol. 223(C).
    3. Xiang, Yue & Cai, Hanhu & Liu, Junyong & Zhang, Xin, 2021. "Techno-economic design of energy systems for airport electrification: A hydrogen-solar-storage integrated microgrid solution," Applied Energy, Elsevier, vol. 283(C).
    4. 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).
    5. Feijoo, Felipe & Kundu, Abhishake & Flores, Francisco & Matamala, Yolanda, 2024. "Photovoltaic sizing assessment for microgrid communities under load shifting constraints and endogenous electricity prices: A Stackelberg approach," Energy, Elsevier, vol. 307(C).
    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. Saeid Esmaeili & Amjad Anvari-Moghaddam & Shahram Jadid, 2019. "Optimal Operational Scheduling of Reconfigurable Multi-Microgrids Considering Energy Storage Systems," Energies, MDPI, vol. 12(9), pages 1-23, May.
    8. Matamala, Yolanda & Flores, Francisco & Arriet, Andrea & Khan, Zarrar & Feijoo, Felipe, 2023. "Probabilistic feasibility assessment of sequestration reliance for climate targets," Energy, Elsevier, vol. 272(C).
    9. Li, Bei & Roche, Robin & Paire, Damien & Miraoui, Abdellatif, 2017. "Sizing of a stand-alone microgrid considering electric power, cooling/heating, hydrogen loads and hydrogen storage degradation," Applied Energy, Elsevier, vol. 205(C), pages 1244-1259.
    10. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    11. K/bidi, Fabrice & Damour, Cedric & Grondin, Dominique & Hilairet, Mickaël & Benne, Michel, 2022. "Multistage power and energy management strategy for hybrid microgrid with photovoltaic production and hydrogen storage," Applied Energy, Elsevier, vol. 323(C).
    12. Feijoo, Felipe & Das, Tapas K., 2015. "Emissions control via carbon policies and microgrid generation: A bilevel model and Pareto analysis," Energy, Elsevier, vol. 90(P2), pages 1545-1555.
    13. Mashayekh, Salman & Stadler, Michael & Cardoso, Gonçalo & Heleno, Miguel, 2017. "A mixed integer linear programming approach for optimal DER portfolio, sizing, and placement in multi-energy microgrids," Applied Energy, Elsevier, vol. 187(C), pages 154-168.
    14. Wang, Xuejie & zhao, Huiru & Lu, Hao & Zhang, Yuanyuan & Wang, Yuwei & Wang, Jingbo, 2022. "Decentralized coordinated operation model of VPP and P2H systems based on stochastic-bargaining game considering multiple uncertainties and carbon cost," Applied Energy, Elsevier, vol. 312(C).
    15. Feijoo, Felipe & Das, Tapas K., 2014. "Design of Pareto optimal CO2 cap-and-trade policies for deregulated electricity networks," Applied Energy, Elsevier, vol. 119(C), pages 371-383.
    16. Bolívar Jaramillo, Lucas & Weidlich, Anke, 2016. "Optimal microgrid scheduling with peak load reduction involving an electrolyzer and flexible loads," Applied Energy, Elsevier, vol. 169(C), pages 857-865.
    17. Komušanac, Ivan & Ćosić, Boris & Duić, Neven, 2016. "Impact of high penetration of wind and solar PV generation on the country power system load: The case study of Croatia," Applied Energy, Elsevier, vol. 184(C), pages 1470-1482.
    18. Melendez, Kevin A. & Matamala, Yolanda, 2025. "Adversarial attacks in demand-side electricity markets," Applied Energy, Elsevier, vol. 377(PD).
    19. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    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. Xu, Lei & Luo, Xiaoyuan & Wen, Yintang & Wu, Tao & Wang, Xinyu & Chang, Shaoping & Guan, Xinping, 2025. "A Stackelberg game-based multi-time scale optimization for hybrid power ship and port," Energy, Elsevier, vol. 324(C).
    2. Duan, Fuyan & Luo, Yi & Huang, Zebo, 2026. "Coordinated operation framework for multi-integrated energy systems with electricity-carbon interaction based on Nash-Stackelberg-Nash game and distributionally robust chance-constraints," Renewable Energy, Elsevier, vol. 256(PF).

    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. 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).
    2. Matamala, Yolanda & Flores, Francisco & Arriet, Andrea & Khan, Zarrar & Feijoo, Felipe, 2023. "Probabilistic feasibility assessment of sequestration reliance for climate targets," Energy, Elsevier, vol. 272(C).
    3. Li, Bei & Roche, Robin & Paire, Damien & Miraoui, Abdellatif, 2018. "Optimal sizing of distributed generation in gas/electricity/heat supply networks," Energy, Elsevier, vol. 151(C), pages 675-688.
    4. Ali, Naghmash & Shen, Xinwei & Armghan, Hammad, 2025. "Multi-level control for shared hydrogen storage system based offshore DC microgrid cluster involving adaptive barrier function," Energy, Elsevier, vol. 332(C).
    5. Yan, Sizhe & Wang, Weiqing & Li, Xiaozhu & Zhao, Yi, 2022. "Research on a cross-regional robust trading strategy based on multiple market mechanisms," Energy, Elsevier, vol. 261(PB).
    6. Khaligh, Vahid & Ghezelbash, Azam & Mazidi, Mohammadreza & Liu, Jay & Ryu, Jun-Hyung, 2023. "P-robust energy management of a multi-energy microgrid enabled with energy conversions under various uncertainties," Energy, Elsevier, vol. 271(C).
    7. Melendez, Kevin A. & Matamala, Yolanda, 2025. "Adversarial attacks in demand-side electricity markets," Applied Energy, Elsevier, vol. 377(PD).
    8. Flores, Francisco & Feijoo, Felipe & DeStephano, Paelina & Herc, Luka & Pfeifer, Antun & Duić, Neven, 2024. "Assessment of the impacts of renewable energy variability in long-term decarbonization strategies," Applied Energy, Elsevier, vol. 368(C).
    9. Jani, Ali & Jadid, Shahram, 2023. "Two-stage energy scheduling framework for multi-microgrid system in market environment," Applied Energy, Elsevier, vol. 336(C).
    10. Förster, Robert & Kaiser, Matthias & Wenninger, Simon, 2023. "Future vehicle energy supply - sustainable design and operation of hybrid hydrogen and electric microgrids," Applied Energy, Elsevier, vol. 334(C).
    11. Wang, Yunqi & Qiu, Jing & Tao, Yuechuan, 2022. "Robust energy systems scheduling considering uncertainties and demand side emission impacts," Energy, Elsevier, vol. 239(PD).
    12. Ge, Haotian & Zhu, Yu & Zhong, Jiuming & Wu, Liang, 2024. "Day-ahead optimization for smart energy management of multi-microgrid using a stochastic-robust model," Energy, Elsevier, vol. 313(C).
    13. Amigo, Pía & Cea-Echenique, Sebastián & Feijoo, Felipe, 2021. "A two stage cap-and-trade model with allowance re-trading and capacity investment: The case of the Chilean NDC targets," Energy, Elsevier, vol. 224(C).
    14. Kim, H.J. & Kim, M.K., 2023. "A novel deep learning-based forecasting model optimized by heuristic algorithm for energy management of microgrid," Applied Energy, Elsevier, vol. 332(C).
    15. Xu, Jiazhu & Yi, Yuqin, 2023. "Multi-microgrid low-carbon economy operation strategy considering both source and load uncertainty: A Nash bargaining approach," Energy, Elsevier, vol. 263(PB).
    16. Zhang, Guodao & Ge, Yisu & Pan, Xiaotian & Zheng, Yun & Yang, Yanhong, 2023. "Hybrid robust-stochastic multi-objective optimization of combined cooling, heating, hydrogen and power-based microgrids," Energy, Elsevier, vol. 274(C).
    17. Zheng, Yi & Wang, Jiawei & You, Shi & Li, Ximei & Bindner, Henrik W. & Münster, Marie, 2023. "Data-driven scheme for optimal day-ahead operation of a wind/hydrogen system under multiple uncertainties," Applied Energy, Elsevier, vol. 329(C).
    18. Huang, Chunjun & Torres, José Luis Rueda & Zong, Yi & You, Shi & Jin, Xin, 2025. "A review of alkaline electrolyzer technology modeling and applications for decision-making optimization in energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 224(C).
    19. Feijoo, Felipe & Huppmann, Daniel & Sakiyama, Larissa & Siddiqui, Sauleh, 2016. "North American natural gas model: Impact of cross-border trade with Mexico," Energy, Elsevier, vol. 112(C), pages 1084-1095.
    20. Subramanian, Vignesh & Feijoo, Felipe & Sankaranarayanan, Sriram & Melendez, Kevin & Das, Tapas K., 2022. "A bilevel conic optimization model for routing and charging of EV fleets serving long distance delivery networks," Energy, Elsevier, vol. 251(C).

    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:314:y:2025:i:c:s0360544224039094. 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.