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Stimulating sustainable energy at maritime ports by hybrid economic incentives: A bilevel optimization approach

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

Abstract

Over the past few decades, maritime ports have faced ever-increasing critiques regarding their significant production of air emissions resulting from their energy activities. To promote sustainability at ports, regulatory authorities have introduced the concept of regulations and economic incentives. In this paper, we analyze the process in which a regulatory authority defines regulations, incentives, and tax policies to motivate one or more ports in the region to initiate energy sustainability and emission-reduction efforts. We model the behaviors of both the regulatory authority and the participating ports in the form of a multi-objective mixed-integer nonlinear bilevel optimization problem to capture the hierarchy of the policy-making process and the existing competitions among the ports. The proposed model finds the optimal incentive and tax policies for the policy-maker in the upper-level and provides the ports in the region with the optimal choice of sustainable energy solutions and service prices in the lower-level. Simulation results show that the proposed approach can effectively reduce the region-wide emission from the port activities while ensuring port entities’ welfare, competitiveness, and sustainable growth as regional energy hubs.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:appene:v:272:y:2020:i:c:s0306261920307005
    DOI: 10.1016/j.apenergy.2020.115188
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    Cited by:

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    2. Wang, Lifen & Liang, Chengji & Shi, Jian & Molavi, Anahita & Lim, Gino & Zhang, Yue, 2021. "A bilevel hybrid economic approach for optimal deployment of onshore power supply in maritime ports," Applied Energy, Elsevier, vol. 292(C).
    3. 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).
    4. 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).
    5. Alaa Othman & Sara El-gazzar & Matjaz Knez, 2022. "A Framework for Adopting a Sustainable Smart Sea Port Index," Sustainability, MDPI, vol. 14(8), pages 1-26, April.
    6. Shanqing Liu & Shaolong Wang & Huwei Wen & Congxian He & Huan Liu, 2024. "Public support policies and entrepreneurship in less-developed areas: a study of China’s revolutionary base areas," Economic Change and Restructuring, Springer, vol. 57(4), pages 1-29, August.
    7. Yang, Bo & Guo, Zhengxun & Yang, Yi & Chen, Yijun & Zhang, Rui & Su, Keyi & Shu, Hongchun & Yu, Tao & Zhang, Xiaoshun, 2021. "Extreme learning machine based meta-heuristic algorithms for parameter extraction of solid oxide fuel cells," Applied Energy, Elsevier, vol. 303(C).
    8. Golmohamadi, Hessam, 2022. "Demand-side management in industrial sector: A review of heavy industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).

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