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

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    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.
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    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. Saqib Iqbal & Kamyar Mehran, 2024. "Data-Driven Management Systems for Wave-Powered Renewable Energy Communities," Energies, MDPI, vol. 17(5), pages 1-19, March.
    3. 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).

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