IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i10p4621-d1658464.html
   My bibliography  Save this article

Optimizing Grid Integration of Power-Generating Ships

Author

Listed:
  • Motab Almousa

    (Department of Electrical Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia)

  • Talal Alharbi

    (Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah 52531, Saudi Arabia)

Abstract

Power-generating ships (PGSs)are considered some of the largest mobile energy resources. A novel model is proposed in this work to evaluate the integration of PGSs into power grid operations. The proposed model optimally coordinates the ships to enhance grid objectives, providing optimal variables for generation resource scheduling and routing of the ships. Two case studies were used to simulate the system and validate the effectiveness of the proposed model. The proposed model significantly contributes to the field of applied mathematical modeling by developing complex algorithms for scheduling energy generation and addressing the logistical challenges of routing mobile power sources. This dual aspect emphasizes the model’s robustness in handling multidimensional optimization problems inherent in integrating mobile energy resources with static grid systems. Integrating PGSs into power grid operations represents a practical implementation of complex engineering solutions designed to enhance the flexibility and reliability of energy networks. The model not only improves the operational efficiency of the grid but also contributes to the resilience of the energy infrastructure by providing a mobile and adaptable energy resource. This approach exemplifies the potential for innovative engineering solutions to address contemporary challenges in energy distribution, ultimately leading to more sustainable and resilient power systems.

Suggested Citation

  • Motab Almousa & Talal Alharbi, 2025. "Optimizing Grid Integration of Power-Generating Ships," Sustainability, MDPI, vol. 17(10), pages 1-28, May.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:10:p:4621-:d:1658464
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/10/4621/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/10/4621/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mwasilu, Francis & Justo, Jackson John & Kim, Eun-Kyung & Do, Ton Duc & Jung, Jin-Woo, 2014. "Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 501-516.
    2. Trinklein, Eddy H. & Parker, Gordon G. & McCoy, Timothy J., 2020. "Modeling, optimization, and control of ship energy systems using exergy methods," Energy, Elsevier, vol. 191(C).
    3. AGRA, Agostinho & ANDERSSON, Henrik & CHRISTIANSEN, Marielle & WOLSEY, Laurence A., 2013. "A maritime inventory routing problem: discrete time formulations and valid inequalities," LIDAM Reprints CORE 2584, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    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. 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).
    2. Chaouachi, Aymen & Bompard, Ettore & Fulli, Gianluca & Masera, Marcelo & De Gennaro, Michele & Paffumi, Elena, 2016. "Assessment framework for EV and PV synergies in emerging distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 719-728.
    3. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    4. 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.
    5. Mutlu, Fatih & Msakni, Mohamed K. & Yildiz, Hakan & Sönmez, Erkut & Pokharel, Shaligram, 2016. "A comprehensive annual delivery program for upstream liquefied natural gas supply chain," European Journal of Operational Research, Elsevier, vol. 250(1), pages 120-130.
    6. Jean-Michel Clairand & Paulo Guerra-Terán & Xavier Serrano-Guerrero & Mario González-Rodríguez & Guillermo Escrivá-Escrivá, 2019. "Electric Vehicles for Public Transportation in Power Systems: A Review of Methodologies," Energies, MDPI, vol. 12(16), pages 1-22, August.
    7. Géremi Gilson Dranka & Paula Ferreira, 2020. "Electric Vehicles and Biofuels Synergies in the Brazilian Energy System," Energies, MDPI, vol. 13(17), pages 1-22, August.
    8. Agra, Agostinho & Christiansen, Marielle & Delgado, Alexandrino & Simonetti, Luidi, 2014. "Hybrid heuristics for a short sea inventory routing problem," European Journal of Operational Research, Elsevier, vol. 236(3), pages 924-935.
    9. Fridgen, Gilbert & Keller, Robert & Körner, Marc-Fabian & Schöpf, Michael, 2020. "A holistic view on sector coupling," Energy Policy, Elsevier, vol. 147(C).
    10. Nagel, Niels Oliver & Jåstad, Eirik Ogner & Martinsen, Thomas, 2024. "The grid benefits of vehicle-to-grid in Norway and Denmark: An analysis of home- and public parking potentials," Energy, Elsevier, vol. 293(C).
    11. Elsinga, Boudewijn & van Sark, Wilfried G.J.H.M., 2017. "Short-term peer-to-peer solar forecasting in a network of photovoltaic systems," Applied Energy, Elsevier, vol. 206(C), pages 1464-1483.
    12. Shi, Ruifeng & Li, Shaopeng & Zhang, Penghui & Lee, Kwang Y., 2020. "Integration of renewable energy sources and electric vehicles in V2G network with adjustable robust optimization," Renewable Energy, Elsevier, vol. 153(C), pages 1067-1080.
    13. Rahman, Imran & Vasant, Pandian M. & Singh, Balbir Singh Mahinder & Abdullah-Al-Wadud, M. & Adnan, Nadia, 2016. "Review of recent trends in optimization techniques for plug-in hybrid, and electric vehicle charging infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1039-1047.
    14. Shi You & Junjie Hu & Charalampos Ziras, 2016. "An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †," Energies, MDPI, vol. 9(11), pages 1-18, November.
    15. Riccardo Iacobucci & Benjamin McLellan & Tetsuo Tezuka, 2018. "The Synergies of Shared Autonomous Electric Vehicles with Renewable Energy in a Virtual Power Plant and Microgrid," Energies, MDPI, vol. 11(8), pages 1-20, August.
    16. Pla, Benjamín & Bares, Pau & Aronis, André Nakaema & Anuratha, Sanjith, 2024. "Leveraging battery electric vehicle energy storage potential for home energy saving by model predictive control with backward induction," Applied Energy, Elsevier, vol. 372(C).
    17. Asaad, Mohammad & Ahmad, Furkan & Alam, Mohammad Saad & Sarfraz, Mohammad, 2021. "Smart grid and Indian experience: A review," Resources Policy, Elsevier, vol. 74(C).
    18. Ellen De Schepper & Steven Van Passel & Sebastien Lizin & Thomas Vincent & Benjamin Martin & Xavier Gandibleux, 2016. "Economic and environmental multi-objective optimisation to evaluate the impact of Belgian policy on solar power and electric vehicles," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 5(1), pages 1-27, March.
    19. Nunes, Pedro & Farias, Tiago & Brito, Miguel C., 2015. "Day charging electric vehicles with excess solar electricity for a sustainable energy system," Energy, Elsevier, vol. 80(C), pages 263-274.
    20. Hemmati, Ahmad & Hvattum, Lars Magnus & Christiansen, Marielle & Laporte, Gilbert, 2016. "An iterative two-phase hybrid matheuristic for a multi-product short sea inventory-routing problem," European Journal of Operational Research, Elsevier, vol. 252(3), pages 775-788.

    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:4621-:d:1658464. 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.