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http://hdl.handle.net/10397/113370
Title: | Tugboat electrification planning for container ports | Authors: | Chen, T Wu, L Wang, S Jia, S Liu, W |
Issue Date: | Feb-2025 | Source: | Transportation research. Part D, Transport and environment, Feb. 2025, v. 139. 104565 | Abstract: | Tugboat assistance is essential for port operations, supporting vessels during berthing, unberthing, and shifting operations. However, significant emissions and pollutants generated by these operations have prompted ports to adopt electrification measures. Electric tugboats have emerged as a promising solution, but their widespread adoption is hindered by the significant capital investment required for electric tugboat purchase and charging facility deployment. To address this problem, this study focuses on strategic planning for the purchase of electric tugboats and the deployment of charging facilities, considering the utilization of existing diesel tugboats, in order to achieve emissions reduction and lower investment costs for the port operator. Additionally, this study also designs the tugboat schedule for the operational phase to effectively meet the tugging demands of vessels. This schedule includes managing charging processes of electric tugboats and coordinating work shifts of both electric and diesel tugboats. A novel integer programming model is then developed to address the investigated problem of integrating strategic and operational phases. Extensive numerical experiments are conducted to demonstrate the applicability of the proposed model. The computational results indicate that introducing electric tugboats can significantly reduce the total emissions of CO2, SOx, NOx, and PM by 91.83%, compared to the scenario where only diesel tugboats are used. Furthermore, the study examines the impacts of various key factors on the emissions reduction and efficient operations to provide some managerial insights for the port operator. | Keywords: | Green port operations Integer programming Maritime transportation Tugboat electrification |
Publisher: | Elsevier Ltd | Journal: | Transportation research. Part D, Transport and environment | ISSN: | 1361-9209 | EISSN: | 1879-2340 | DOI: | 10.1016/j.trd.2024.104565 |
Appears in Collections: | Journal/Magazine Article |
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