ORIGINAL RESEARCH article
Front. Energy Res.
Sec. Process and Energy Systems Engineering
Volume 13 - 2025 | doi: 10.3389/fenrg.2025.1610648
This article is part of the Research TopicOcean and Offshore Systems Engineering for Renewable Energy ApplicationsView all 3 articles
An optimal scheduling strategy of port virtual power plant considering orderly berth allocation and green certificate-tiered carbon trading mechanism
Provisionally accepted
- 1Southeast University, Nanjing, China
- 2Hohai University, Nanjing, Jiangsu Province, China
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Ports serve as critical nodes within transportation networks and logistics chains, where the planning of ship berthing is intricately linked to energy utilization. Addressing challenges such as the allocation of port berths and insufficient integration of clean energy, we propose an optimal dispatch strategy for port virtual power plants, which incorporates orderly berth allocation and a green certificate-tiered carbon trading mechanism.The proposed model first examines the berth capacity issue by reallocating berths through a quantitative analysis of overall benefits. This approach enhances the flexibility of the energy network while ensuring adequate energy supply for ships. To facilitate the green transformation of ports, a green certificate-tiered carbon trading mechanism is embedded within the virtual power plant framework, leveraging economic incentives to guide the optimization of the port's energy structure. This strategy effectively promotes the consumption and utilization of renewable energy at ports. Finally, we constructed four simulation scenarios to compare results, which validate the effectiveness of the proposed strategy. The integration of orderly berth allocation and the green certificate-tiered carbon trading mechanism significantly improves the port's operational economic efficiency and environmental protection outcomes, offering a novel approach for berth planning and energy management in port operations.
Keywords: Port virtual power plant, Berth optimization, Carbon trading, Energy Management, Scheduling optimization
Received: 12 Apr 2025; Accepted: 24 Jul 2025.
Copyright: © 2025 Lu, Zheng, Mei, Ding, Xie and Gao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jianyong Zheng, Southeast University, Nanjing, China
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