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Energy–Logistics Cooperative Optimization for a Port-Integrated Energy System

Author

Listed:
  • Aiming Mo

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    National Key Laboratory of Electromagnetic Energy, Naval University of Engineering, Wuhan 430033, China)

  • Yan Zhang

    (National Key Laboratory of Electromagnetic Energy, Naval University of Engineering, Wuhan 430033, China)

  • Yiyong Xiong

    (School of Electrical Engineering, Naval University of Engineering, Wuhan 430033, China)

  • Fan Ma

    (National Key Laboratory of Electromagnetic Energy, Naval University of Engineering, Wuhan 430033, China)

  • Lin Sun

    (National Key Laboratory of Electromagnetic Energy, Naval University of Engineering, Wuhan 430033, China)

Abstract

In order to achieve carbon peak and neutrality goals, many low-carbon operations are implemented in ports. Integrated energy systems that consist of port electricity and cooling loads, wind and PV energy devices, energy storage, and clean fuels are considered as a future technology. In addition, ports are important hubs for the global economy and trade; logistics optimization is also part of their objective, and most port facilities have complex logistics. This article proposes an energy–logistics collaborative optimization method to fully tap the potential of port-integrated energy systems. A logistics–energy system model is established by deeply examining the operational characteristics of logistics systems and their corresponding energy consumption patterns, considering ships’ operational statuses, quay crane distribution constraints, and power balances. To better represent the ship–energy–logistics optimization problem, a hybrid system modeling technique is employed. The case of Shanghai Port is studied; the results show that costs can be reduced by 3.27% compared to the traditional optimization method, and a sensitivity analysis demonstrates the robustness of the proposed method.

Suggested Citation

  • Aiming Mo & Yan Zhang & Yiyong Xiong & Fan Ma & Lin Sun, 2024. "Energy–Logistics Cooperative Optimization for a Port-Integrated Energy System," Mathematics, MDPI, vol. 12(12), pages 1-24, June.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:12:p:1917-:d:1419111
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    References listed on IDEAS

    as
    1. Giri, Binoy Krishna & Roy, Sankar Kumar, 2024. "Fuzzy-random robust flexible programming on sustainable closed-loop renewable energy supply chain," Applied Energy, Elsevier, vol. 363(C).
    2. Łukasz Skowron & Olena Chygryn & Marcin Gąsior & Vitaliia Koibichuk & Serhiy Lyeonov & Serhii Drozd & Oleksandr Dluhopolskyi, 2023. "Interconnection between the Dynamic of Growing Renewable Energy Production and the Level of CO 2 Emissions: A Multistage Approach for Modeling," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
    3. Davide Borelli & Francesco Devia & Corrado Schenone & Federico Silenzi & Luca A. Tagliafico, 2021. "Dynamic Modelling of LNG Powered Combined Energy Systems in Port Areas," Energies, MDPI, vol. 14(12), pages 1-18, June.
    4. Mao, Anjia & Yu, Tiantian & Ding, Zhaohao & Fang, Sidun & Guo, Jinran & Sheng, Qianqian, 2022. "Optimal scheduling for seaport integrated energy system considering flexible berth allocation," Applied Energy, Elsevier, vol. 308(C).
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