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Enabling smart ports through the integration of microgrids: A two-stage stochastic programming approach

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  • Molavi, Anahita
  • Shi, Jian
  • Wu, Yiwei
  • Lim, Gino J.

Abstract

This paper explores microgrids’ application at ports and presents a systematic framework for evaluating the benefits of microgrid integration in creating sustainable value through purposeful planning. We focus on demonstrating how a set of Smart Port Index (SPI) metrics can be incorporated into the port microgrid planning process in the proposed framework to holistically improve the smartness of the port. A two-stage stochastic mixed-integer programming model is developed to explain how the use of microgrid at a port can effectively enhance the port’s performance in four key activity domains: operations, environment, energy, safety and security under operation uncertainty. The proposed model consists of an investment master problem on the first stage and a multi-objective operation planning subproblem on the second stage. Benders decomposition is implemented for solving the two-stage stochastic model, and Lexicographic Goal Programming is applied to the subproblem to deal with multiple objectives. Simulation results, compared with the minimum cost planning approach, indicate that the proposed framework is capable of guaranteeing an improvement in productivity, sustainability, and reliability of port operations.

Suggested Citation

  • Molavi, Anahita & Shi, Jian & Wu, Yiwei & Lim, Gino J., 2020. "Enabling smart ports through the integration of microgrids: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:appene:v:258:y:2020:i:c:s030626191931709x
    DOI: 10.1016/j.apenergy.2019.114022
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    References listed on IDEAS

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    Cited by:

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    12. Huiru Zhao & Hao Lu & Bingkang Li & Xuejie Wang & Shiying Zhang & Yuwei Wang, 2020. "Stochastic Optimization of Microgrid Participating Day-Ahead Market Operation Strategy with Consideration of Energy Storage System and Demand Response," Energies, MDPI, vol. 13(5), pages 1-16, March.
    13. 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).
    14. Zixiao Ban & Fei Teng & Huifeng Zhang & Shuo Li & Geyang Xiao & Yajuan Guan, 2023. "Distributed Fixed-Time Energy Management for Port Microgrid Considering Transmissive Efficiency," Mathematics, MDPI, vol. 11(17), pages 1-13, August.
    15. Molavi, Anahita & Lim, Gino J. & Shi, Jian, 2020. "Stimulating sustainable energy at maritime ports by hybrid economic incentives: A bilevel optimization approach," Applied Energy, Elsevier, vol. 272(C).
    16. Hokey Min, 2022. "Developing a smart port architecture and essential elements in the era of Industry 4.0," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 189-207, June.
    17. Zhang, Yue & Liang, Chengji & Shi, Jian & Lim, Gino & Wu, Yiwei, 2022. "Optimal Port Microgrid Scheduling Incorporating Onshore Power Supply and Berth Allocation Under Uncertainty," Applied Energy, Elsevier, vol. 313(C).
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    19. Xianfeng Xu & Ke Wang & Yong Lu & Yunbo Tian & Liqun Hu & Ming Zhong, 2023. "Research on Performance Evaluation Index System and Assessment Methods for Microgrid Operation in the Port Area," Sustainability, MDPI, vol. 15(20), pages 1-16, October.

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