IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v372y2024ics0306261924012194.html
   My bibliography  Save this article

Online probabilistic energy flow for hydrogen-power-heat system based on multi-parametric programming

Author

Listed:
  • Zhou, Yijia
  • Peng, Hongyi
  • Yan, Mingyu

Abstract

The introduction of renewable energy introduces operational challenges for the modern multi-energy system. To accommodate the uncertainty, this paper proposes an online probabilistic energy flow for the hydrogen-power-heat system. First, a hydrogen-power-heat system model is established to depict the interdependency of multiple energy, in which hydrogen fuel cells interconnect hydrogen, power, and heat systems by converting the hydrogen into power and heat. The probabilistic energy flow is further built considering the uncertain wind power. An efficient algorithm based on multi-parametric programming (MPP) is proposed to enhance the computational performance of probabilistic multi-energy flow for online applications. The parameter region of the probabilistic multi-energy flow in MPP model is divided into multiple critical regions (CR). Each CR reveals a unique mapping relationship from uncertain wind power to system optimal solutions. Probabilistic energy flow could be quickly calculated based on mapping relationship rather than solving optimization problem. Therefore, the proposed method could be applied in online energy flow calculation. Numerical results tested on a 6–6-8 system and an improved 40–118 − 13 system validate the accuracy and efficiency of the proposed method in probabilistic energy flow calculation.

Suggested Citation

  • Zhou, Yijia & Peng, Hongyi & Yan, Mingyu, 2024. "Online probabilistic energy flow for hydrogen-power-heat system based on multi-parametric programming," Applied Energy, Elsevier, vol. 372(C).
    • Handle: RePEc:eee:appene:v:372:y:2024:i:c:s0306261924012194
    DOI: 10.1016/j.apenergy.2024.123836
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924012194
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.123836?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. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Lan, Liuhan & Zhang, Youzhong & Zhang, Xingping & Zhang, Xinyue, 2024. "Price effect of multi-energy system with CCS and P2G and its impact on carbon-gas-electricity sectors," Applied Energy, Elsevier, vol. 359(C).
    3. Lin, Yujun & Yang, Qiufan & Zhou, Jianyu & Chen, Xia & Wen, Jinyu, 2023. "A time-coupling consideration for evaluation of load carrying capacity in district multi-energy systems," Applied Energy, Elsevier, vol. 351(C).
    4. F. Borrelli & A. Bemporad & M. Morari, 2003. "Geometric Algorithm for Multiparametric Linear Programming," Journal of Optimization Theory and Applications, Springer, vol. 118(3), pages 515-540, September.
    5. Khalili, Reza & Khaledi, Arian & Marzband, Mousa & Nematollahi, Amin Foroughi & Vahidi, Behrooz & Siano, Pierluigi, 2023. "Robust multi-objective optimization for the Iranian electricity market considering green hydrogen and analyzing the performance of different demand response programs," Applied Energy, Elsevier, vol. 334(C).
    6. Fan, Feilong & Aditya, Venkataraman & Xu, Yan & Cheong, Benjamin & Gupta, Amit K., 2022. "Robustly coordinated operation of a ship microgird with hybrid propulsion systems and hydrogen fuel cells," Applied Energy, Elsevier, vol. 312(C).
    7. Gao, Fang & Xu, Zidong & Yin, Linfei, 2024. "Bayesian deep neural networks for spatio-temporal probabilistic optimal power flow with multi-source renewable energy," Applied Energy, Elsevier, vol. 353(PA).
    8. Yan, Mingyu & Teng, Fei & Gan, Wei & Yao, Wei & Wen, Jinyu, 2023. "Blockchain for secure decentralized energy management of multi-energy system using state machine replication," Applied Energy, Elsevier, vol. 337(C).
    9. 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).
    10. Ghaemi, Sina & Li, Xinyu & Mulder, Machiel, 2023. "Economic feasibility of green hydrogen in providing flexibility to medium-voltage distribution grids in the presence of local-heat systems," 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. Yi, Ji Hyun & Ko, Woong & Park, Jong-Keun & Park, Hyeongon, 2018. "Impact of carbon emission constraint on design of small scale multi-energy system," Energy, Elsevier, vol. 161(C), pages 792-808.
    2. Dominković, D.F. & Bačeković, I. & Sveinbjörnsson, D. & Pedersen, A.S. & Krajačić, G., 2017. "On the way towards smart energy supply in cities: The impact of interconnecting geographically distributed district heating grids on the energy system," Energy, Elsevier, vol. 137(C), pages 941-960.
    3. Lukas Kriechbaum & Philipp Gradl & Romeo Reichenhauser & Thomas Kienberger, 2020. "Modelling Grid Constraints in a Multi-Energy Municipal Energy System Using Cumulative Exergy Consumption Minimisation," Energies, MDPI, vol. 13(15), pages 1-23, July.
    4. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    5. Sayegh, M.A. & Danielewicz, J. & Nannou, T. & Miniewicz, M. & Jadwiszczak, P. & Piekarska, K. & Jouhara, H., 2017. "Trends of European research and development in district heating technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1183-1192.
    6. Matija Kostelac & Lin Herenčić & Tomislav Capuder, 2022. "Planning and Operational Aspects of Individual and Clustered Multi-Energy Microgrid Options," Energies, MDPI, vol. 15(4), pages 1-17, February.
    7. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    8. 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).
    9. Waibel, Christoph & Evins, Ralph & Carmeliet, Jan, 2019. "Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials," Applied Energy, Elsevier, vol. 242(C), pages 1661-1682.
    10. David Drysdale & Brian Vad Mathiesen & Henrik Lund, 2019. "From Carbon Calculators to Energy System Analysis in Cities," Energies, MDPI, vol. 12(12), pages 1-21, June.
    11. Bahl, Björn & Kümpel, Alexander & Seele, Hagen & Lampe, Matthias & Bardow, André, 2017. "Time-series aggregation for synthesis problems by bounding error in the objective function," Energy, Elsevier, vol. 135(C), pages 900-912.
    12. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    13. Wirtz, Marco, 2023. "nPro: A web-based planning tool for designing district energy systems and thermal networks," Energy, Elsevier, vol. 268(C).
    14. Theresa Liegl & Simon Schramm & Philipp Kuhn & Thomas Hamacher, 2023. "Considering Socio-Technical Parameters in Energy System Models—The Current Status and Next Steps," Energies, MDPI, vol. 16(20), pages 1-19, October.
    15. Capone, Martina & Guelpa, Elisa & Verda, Vittorio, 2023. "Potential for supply temperature reduction of existing district heating substations," Energy, Elsevier, vol. 285(C).
    16. Gao, Yang & Ai, Qian & He, Xing & Fan, Songli, 2023. "Coordination for regional integrated energy system through target cascade optimization," Energy, Elsevier, vol. 276(C).
    17. Shirizadeh, Behrang & Quirion, Philippe, 2022. "The importance of renewable gas in achieving carbon-neutrality: Insights from an energy system optimization model," Energy, Elsevier, vol. 255(C).
    18. Aurelia Rybak & Aleksandra Rybak, 2021. "Methods of Ensuring Energy Security with the Use of Hard Coal—The Case of Poland," Energies, MDPI, vol. 14(18), pages 1-25, September.
    19. Maroufmashat, Azadeh & Elkamel, Ali & Fowler, Michael & Sattari, Sourena & Roshandel, Ramin & Hajimiragha, Amir & Walker, Sean & Entchev, Evgueniy, 2015. "Modeling and optimization of a network of energy hubs to improve economic and emission considerations," Energy, Elsevier, vol. 93(P2), pages 2546-2558.
    20. Peixiao Fan & Jia Hu & Song Ke & Yuxin Wen & Shaobo Yang & Jun Yang, 2022. "A Frequency–Pressure Cooperative Control Strategy of Multi-Microgrid with an Electric–Gas System Based on MADDPG," Sustainability, MDPI, vol. 14(14), pages 1-20, July.

    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:appene:v:372:y:2024:i:c:s0306261924012194. 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.