IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v328y2025ics0360544225021139.html
   My bibliography  Save this article

A two-stage hybrid stochastic-robust policy of decentralized distributionally energy management for offshore oil and gas platform energy hub coupled with shared energy marine transport fleets

Author

Listed:
  • Fan, Jiayi
  • Ni, Yiyang
  • Qi, Liang
  • Yuan, Wei
  • Soh, Yeng Chai

Abstract

The sustainable operation of Offshore Integrated Energy Hubs (OIEHs) faces significant challenges, particularly in achieving energy self-sufficiency and enhancing resilience against complex operational interactions—issues compounded by the prevailing reliance on fossil fuel-based systems. This paper proposes a novel Decentralized Energy Management (DEM) strategy designed specifically for OIEHs, involving the integration of Shared Energy Marine Transport Fleets (SEMTFs) equipped with Mobile Electrical Storage Packs (MESPs) to facilitate decentralized power delivery. A major contribution of this research is the development of a Coordinated Linkage Energy Flow Model (CLEFM), enabling dynamic and efficient spatiotemporal energy exchange between the seaport and offshore hubs. Furthermore, the study introduces an innovative hybrid uncertainty management framework based on a two-stage methodology: scenario-based stochastic programming combined with robust optimization leveraging risk-averse decision-maker-based information gap decision theory. This dual approach addresses critical uncertainties associated with offshore renewable energy generation and fluctuating demand profiles. The resulting DEM problem is formulated as a Mixed-Integer Linear Programming (MILP) model and solved using the CPLEX solver within a GAMS environment. To evaluate the effectiveness of the proposed system, seven comprehensive case studies were conducted. Simulation results demonstrate considerable improvements in system flexibility, sustainability, and autonomy, as well as enhanced responsiveness to varying operational conditions. Notably, the proposed strategy achieved operational cost reductions ranging from 55 % to 81 %, with these savings explicitly attributed to optimized utilization of PEMFCs, BDGs, and SEMTFs—elements that represent the primary contributors to the system's operational expenditures. In addition, the model integrates Demand Response Programs (DRPs) and Seaport-Independent Centralized Clean Energy Sources (SICCESs), further improving the robustness and energy independence of OIEHs. Overall, the proposed approach offers a scalable, resilient, and economically viable framework that addresses critical gaps in offshore energy operations, thereby advancing the development of green synergy policies and promoting long-term sustainability in marine energy ecosystems.

Suggested Citation

  • Fan, Jiayi & Ni, Yiyang & Qi, Liang & Yuan, Wei & Soh, Yeng Chai, 2025. "A two-stage hybrid stochastic-robust policy of decentralized distributionally energy management for offshore oil and gas platform energy hub coupled with shared energy marine transport fleets," Energy, Elsevier, vol. 328(C).
  • Handle: RePEc:eee:energy:v:328:y:2025:i:c:s0360544225021139
    DOI: 10.1016/j.energy.2025.136471
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225021139
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.136471?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. Liu, Yang & Wang, Wei & Ghadimi, Noradin, 2017. "Electricity load forecasting by an improved forecast engine for building level consumers," Energy, Elsevier, vol. 139(C), pages 18-30.
    2. Sui, Quan & Zhang, Rui & Wu, Chuantao & Wei, Fanrong & Lin, Xiangning & Li, Zhengtian, 2020. "Stochastic scheduling of an electric vessel-based energy management system in pelagic clustering islands," Applied Energy, Elsevier, vol. 259(C).
    3. Obara, Shin’ya & Kawai, Masahito & Kawae, Osamu & Morizane, Yuta, 2013. "Operational planning of an independent microgrid containing tidal power generators, SOFCs, and photovoltaics," Applied Energy, Elsevier, vol. 102(C), pages 1343-1357.
    4. Hu, Mian & Wang, Yan-Wu & Xiao, Jiang-Wen & Lin, Xiangning, 2019. "Multi-energy management with hierarchical distributed multi-scale strategy for pelagic islanded microgrid clusters," Energy, Elsevier, vol. 185(C), pages 910-921.
    5. Zhang, Hongyu & Tomasgard, Asgeir & Knudsen, Brage Rugstad & Svendsen, Harald G. & Bakker, Steffen J. & Grossmann, Ignacio E., 2022. "Modelling and analysis of offshore energy hubs," Energy, Elsevier, vol. 261(PA).
    6. Georgilakis, Pavlos S. & Katsigiannis, Yiannis A., 2009. "Reliability and economic evaluation of small autonomous power systems containing only renewable energy sources," Renewable Energy, Elsevier, vol. 34(1), pages 65-70.
    7. Song, Tiewei & Fu, Lijun & Zhong, Linlin & Fan, Yaxiang & Shang, Qianyi, 2024. "HP3O algorithm-based all electric ship energy management strategy integrating demand-side adjustment," Energy, Elsevier, vol. 295(C).
    8. Paria Akbary & Mohammad Ghiasi & Mohammad Reza Rezaie Pourkheranjani & Hamidreza Alipour & Noradin Ghadimi, 2019. "Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 1-26, January.
    9. Latif, Abdul & Hussain, S. M. Suhail & Das, Dulal Chandra & Ustun, Taha Selim, 2021. "Double stage controller optimization for load frequency stabilization in hybrid wind-ocean wave energy based maritime microgrid system," Applied Energy, Elsevier, vol. 282(PA).
    10. Xuanxia Guo & Noradin Ghadimi, 2023. "Optimal Design of the Proton-Exchange Membrane Fuel Cell Connected to the Network Utilizing an Improved Version of the Metaheuristic Algorithm," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    11. Shadmani, Alireza & Nikoo, Mohammad Reza & Gandomi, Amir H., 2024. "Adaptive systematic optimization of a multi-axis ocean wave energy converter," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    12. Keyvan Karamnejadi Azar & Armin Kakouee & Morteza Mollajafari & Ali Majdi & Noradin Ghadimi & Mojtaba Ghadamyari, 2022. "Developed Design of Battle Royale Optimizer for the Optimum Identification of Solid Oxide Fuel Cell," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    13. Katsaprakakis, Dimitris Al. & Papadakis, Nikos & Kozirakis, George & Minadakis, Yiannis & Christakis, Dimitris & Kondaxakis, Konstantinos, 2009. "Electricity supply on the island of Dia based on renewable energy sources (R.E.S.)," Applied Energy, Elsevier, vol. 86(4), pages 516-527, April.
    14. Ana Cabrera-Tobar & Alessandro Massi Pavan & Giovanni Petrone & Giovanni Spagnuolo, 2022. "A Review of the Optimization and Control Techniques in the Presence of Uncertainties for the Energy Management of Microgrids," Energies, MDPI, vol. 15(23), pages 1-38, December.
    15. Senjyu, Tomonobu & Hayashi, Daisuke & Yona, Atsushi & Urasaki, Naomitsu & Funabashi, Toshihisa, 2007. "Optimal configuration of power generating systems in isolated island with renewable energy," Renewable Energy, Elsevier, vol. 32(11), pages 1917-1933.
    16. Lüth, Alexandra & Keles, Dogan, 2024. "Risks, strategies, and benefits of offshore energy hubs: A literature-based survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 203(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. Zhang, Meng & Guo, Huan & Sun, Ming & Liu, Sifeng & Forrest, Jeffrey, 2022. "A novel flexible grey multivariable model and its application in forecasting energy consumption in China," Energy, Elsevier, vol. 239(PE).
    2. Tanaka, Kenichi & Yoza, Akihiro & Ogimi, Kazuki & Yona, Atsushi & Senjyu, Tomonobu & Funabashi, Toshihisa & Kim, Chul-Hwan, 2012. "Optimal operation of DC smart house system by controllable loads based on smart grid topology," Renewable Energy, Elsevier, vol. 39(1), pages 132-139.
    3. Liu, Lijun & Qian, Jin & Hua, Li & Zhang, Bin, 2022. "System estimation of the SOFCs using fractional-order social network search algorithm," Energy, Elsevier, vol. 255(C).
    4. Wu, Chuantao & Zhou, Dezhi & Lin, Xiangning & Sui, Quan & Wei, Fanrong & Li, Zhengtian, 2022. "A novel energy cooperation framework for multi-island microgrids based on marine mobile energy storage systems," Energy, Elsevier, vol. 252(C).
    5. William López-Castrillón & Héctor H. Sepúlveda & Cristian Mattar, 2021. "Off-Grid Hybrid Electrical Generation Systems in Remote Communities: Trends and Characteristics in Sustainability Solutions," Sustainability, MDPI, vol. 13(11), pages 1-29, May.
    6. Wu, Cong & Li, Jiaxuan & Liu, Wenjin & He, Yuzhe & Nourmohammadi, Samad, 2023. "Short-term electricity demand forecasting using a hybrid ANFIS–ELM network optimised by an improved parasitism–predation algorithm," Applied Energy, Elsevier, vol. 345(C).
    7. Chua, K.J. & Yang, W.M. & Er, S.S. & Ho, C.A., 2014. "Sustainable energy systems for a remote island community," Applied Energy, Elsevier, vol. 113(C), pages 1752-1763.
    8. Kwon, Sunghoon & Won, Wangyun & Kim, Jiyong, 2016. "A superstructure model of an isolated power supply system using renewable energy: Development and application to Jeju Island, Korea," Renewable Energy, Elsevier, vol. 97(C), pages 177-188.
    9. Yang, Zixuan & Liu, Qian & Zhang, Leiyu & Dai, Jialei & Razmjooy, Navid, 2020. "Model parameter estimation of the PEMFCs using improved Barnacles Mating Optimization algorithm," Energy, Elsevier, vol. 212(C).
    10. Hou, Rui & Li, Shanshan & Wu, Minrong & Ren, Guowen & Gao, Wei & Khayatnezhad, Majid & gholinia, Fatemeh, 2021. "Assessing of impact climate parameters on the gap between hydropower supply and electricity demand by RCPs scenarios and optimized ANN by the improved Pathfinder (IPF) algorithm," Energy, Elsevier, vol. 237(C).
    11. Yuan, Zhi & Wang, Weiqing & Wang, Haiyun & Mizzi, Scott, 2020. "Combination of cuckoo search and wavelet neural network for midterm building energy forecast," Energy, Elsevier, vol. 202(C).
    12. Gioutsos, Dean Marcus & Blok, Kornelis & van Velzen, Leonore & Moorman, Sjoerd, 2018. "Cost-optimal electricity systems with increasing renewable energy penetration for islands across the globe," Applied Energy, Elsevier, vol. 226(C), pages 437-449.
    13. Lee, Taedong & Glick, Mark B. & Lee, Jae-Hyup, 2020. "Island energy transition: Assessing Hawaii's multi-level, policy-driven approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    14. Sun, Xianke & Wang, Gaoliang & Xu, Liuyang & Yuan, Honglei & Yousefi, Nasser, 2021. "Optimal estimation of the PEM fuel cells applying deep belief network optimized by improved archimedes optimization algorithm," Energy, Elsevier, vol. 237(C).
    15. Lu, Xiaohui & Yang, Yang & Wang, Peifang & Fan, Yiming & Yu, Fangzhong & Zafetti, Nicholas, 2021. "A new converged Emperor Penguin Optimizer for biding strategy in a day-ahead deregulated market clearing price: A case study in China," Energy, Elsevier, vol. 227(C).
    16. Li, Yalun & Gao, Xinlei & Feng, Xuning & Ren, Dongsheng & Li, Yan & Hou, Junxian & Wu, Yu & Du, Jiuyu & Lu, Languang & Ouyang, Minggao, 2022. "Battery eruption triggered by plated lithium on an anode during thermal runaway after fast charging," Energy, Elsevier, vol. 239(PB).
    17. Ren, Xiaojun & Wu, Yongtang & Hao, Dongmin & Liu, Guoxu & Zafetti, Nicholas, 2021. "Analysis of the performance of the multi-objective hybrid hydropower-photovoltaic-wind system to reduce variance and maximum power generation by developed owl search algorithm," Energy, Elsevier, vol. 231(C).
    18. Yin, Linfei & Sun, Zhixiang, 2021. "Multi-layer distributed multi-objective consensus algorithm for multi-objective economic dispatch of large-scale multi-area interconnected power systems," Applied Energy, Elsevier, vol. 300(C).
    19. Xu, Xiao & Hu, Weihao & Liu, Wen & Du, Yuefang & Huang, Rui & Huang, Qi & Chen, Zhe, 2021. "Look-ahead risk-constrained scheduling for an energy hub integrated with renewable energy," Applied Energy, Elsevier, vol. 297(C).
    20. Kamjoo, Azadeh & Maheri, Alireza & Putrus, Ghanim A., 2014. "Chance constrained programming using non-Gaussian joint distribution function in design of standalone hybrid renewable energy systems," Energy, Elsevier, vol. 66(C), pages 677-688.

    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:328:y:2025:i:c:s0360544225021139. 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.