IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v259y2020ics0306261919318422.html
   My bibliography  Save this article

Stochastic scheduling of an electric vessel-based energy management system in pelagic clustering islands

Author

Listed:
  • Sui, Quan
  • Zhang, Rui
  • Wu, Chuantao
  • Wei, Fanrong
  • Lin, Xiangning
  • Li, Zhengtian

Abstract

The pelagic clustering islands (PCIs) can be developed into the resource rich islands (RRIs) and load center island (LCI) using the electric vessel (EV) to achieve interisland energy flow. However, energy balance between the supply and demand cannot be directly achieved, resulting in crucial need for effective day-ahead energy management for PCIs. To address this issue, this paper proposes a novel scenario-based energy management system (EMS) to optimize the operation of PCIs. To ensure the EMS performance, the comprehensive impact of environmental factors including wind, solar radiation and ocean currents on energy supply, transmission and demand is analysed in detail. The dynamic energy transmission channel and power flow balance relationship are modelled by evaluating the location and charging/discharging power of the EV. Considering the forecasting inaccuracies in environmental factors using refined stratified sampling (RSS) and scenario reduction methods, a stochastic optimization model is proposed to maximize the operational economy and reliability of PCIs, followed by a 2-stage solution consisting of preprocessing and group-search optimization with multiple producers (GSOMP). Simulation studies on Taiping Island, Hongma Island, Bolan Reef and Anda Reef in the South China Sea show that the proposed EMS is feasible and economical to describe the energy supply of PCIs.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:appene:v:259:y:2020:i:c:s0306261919318422
    DOI: 10.1016/j.apenergy.2019.114155
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919318422
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2019.114155?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Shields, Michael D. & Teferra, Kirubel & Hapij, Adam & Daddazio, Raymond P., 2015. "Refined Stratified Sampling for efficient Monte Carlo based uncertainty quantification," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 310-325.
    2. Morales, J.M. & Mínguez, R. & Conejo, A.J., 2010. "A methodology to generate statistically dependent wind speed scenarios," Applied Energy, Elsevier, vol. 87(3), pages 843-855, March.
    3. He, Lifu & Yang, Jun & Yan, Jun & Tang, Yufei & He, Haibo, 2016. "A bi-layer optimization based temporal and spatial scheduling for large-scale electric vehicles," Applied Energy, Elsevier, vol. 168(C), pages 179-192.
    4. Li, Yanfu & Zio, Enrico, 2012. "Uncertainty analysis of the adequacy assessment model of a distributed generation system," Renewable Energy, Elsevier, vol. 41(C), pages 235-244.
    5. Sarabi, Siyamak & Davigny, Arnaud & Courtecuisse, Vincent & Riffonneau, Yann & Robyns, Benoît, 2016. "Potential of vehicle-to-grid ancillary services considering the uncertainties in plug-in electric vehicle availability and service/localization limitations in distribution grids," Applied Energy, Elsevier, vol. 171(C), pages 523-540.
    6. 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.
    7. Zhang, Bingying & Li, Qiqiang & Wang, Luhao & Feng, Wei, 2018. "Robust optimization for energy transactions in multi-microgrids under uncertainty," Applied Energy, Elsevier, vol. 217(C), pages 346-360.
    8. Kou, Peng & Liang, Deliang & Gao, Lin, 2017. "Distributed EMPC of multiple microgrids for coordinated stochastic energy management," Applied Energy, Elsevier, vol. 185(P1), pages 939-952.
    9. Jian, Linni & Zheng, Yanchong & Shao, Ziyun, 2017. "High efficient valley-filling strategy for centralized coordinated charging of large-scale electric vehicles," Applied Energy, Elsevier, vol. 186(P1), pages 46-55.
    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. Zhou, Dezhi & Wu, Chuantao & Sui, Quan & Lin, Xiangning & Li, Zhengtian, 2022. "A novel all-electric-ship-integrated energy cooperation coalition for multi-island microgrids," Applied Energy, Elsevier, vol. 320(C).
    2. 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).

    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. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    2. Diptish Saha & Najmeh Bazmohammadi & Juan C. Vasquez & Josep M. Guerrero, 2023. "Multiple Microgrids: A Review of Architectures and Operation and Control Strategies," Energies, MDPI, vol. 16(2), pages 1-32, January.
    3. Li, Qiang & Gao, Mengkai & Lin, Houfei & Chen, Ziyu & Chen, Minyou, 2019. "MAS-based distributed control method for multi-microgrids with high-penetration renewable energy," Energy, Elsevier, vol. 171(C), pages 284-295.
    4. Aghajani, Saemeh & Kalantar, Mohsen, 2017. "Optimal scheduling of distributed energy resources in smart grids: A complementarity approach," Energy, Elsevier, vol. 141(C), pages 2135-2144.
    5. Jani, Ali & Jadid, Shahram, 2023. "Two-stage energy scheduling framework for multi-microgrid system in market environment," Applied Energy, Elsevier, vol. 336(C).
    6. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    7. 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.
    8. 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.
    9. Zahid Ullah & Arshad & Jawad Ahmad, 2022. "The Development of a Cross-Border Energy Trade Cooperation Model of Interconnected Virtual Power Plants Using Bilateral Contracts," Energies, MDPI, vol. 15(21), pages 1-16, November.
    10. Álex Omar Topa Gavilema & José Domingo Álvarez & José Luis Torres Moreno & Manuel Pérez García, 2021. "Towards Optimal Management in Microgrids: An Overview," Energies, MDPI, vol. 14(16), pages 1-25, August.
    11. Pan Wu & Wentao Huang & Nengling Tai & Zhoujun Ma & Xiaodong Zheng & Yong Zhang, 2019. "A Multi-Layer Coordinated Control Scheme to Improve the Operation Friendliness of Grid-Connected Multiple Microgrids," Energies, MDPI, vol. 12(2), pages 1-21, January.
    12. Muhammad Huda & Tokimatsu Koji & Muhammad Aziz, 2020. "Techno Economic Analysis of Vehicle to Grid (V2G) Integration as Distributed Energy Resources in Indonesia Power System," Energies, MDPI, vol. 13(5), pages 1-16, March.
    13. Villanueva-Rosario, Junior Alexis & Santos-García, Félix & Aybar-Mejía, Miguel Euclides & Mendoza-Araya, Patricio & Molina-García, Angel, 2022. "Coordinated ancillary services, market participation and communication of multi-microgrids: A review," Applied Energy, Elsevier, vol. 308(C).
    14. Chiron, Marie & Genest, Christian & Morio, Jérôme & Dubreuil, Sylvain, 2023. "Failure probability estimation through high-dimensional elliptical distribution modeling with multiple importance sampling," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    15. 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.
    16. Zhang, Jiyuan & Tang, Hailong & Chen, Min, 2019. "Linear substitute model-based uncertainty analysis of complicated non-linear energy system performance (case study of an adaptive cycle engine)," Applied Energy, Elsevier, vol. 249(C), pages 87-108.
    17. Da Li & Shijie Zhang & Yunhan Xiao, 2020. "Interval Optimization-Based Optimal Design of Distributed Energy Resource Systems under Uncertainties," Energies, MDPI, vol. 13(13), pages 1-18, July.
    18. Wang, Zhiwen & Shen, Chen & Liu, Feng, 2018. "A conditional model of wind power forecast errors and its application in scenario generation," Applied Energy, Elsevier, vol. 212(C), pages 771-785.
    19. 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).
    20. Popović, Željko N. & KovaÄ ki, Neven V. & Popović, Dragan S., 2020. "Resilient distribution network planning under the severe windstorms using a risk-based approach," Reliability Engineering and System Safety, Elsevier, vol. 204(C).

    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:259:y:2020:i:c:s0306261919318422. 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.