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Peng Yun

Associate Professor
Supervisor of Master's Candidates

Academic Titles:
Alma Mater:大连理工大学
Degree:Doctoral Degree
Status:On the job
Discipline:Port, Coastal and Offshore Engineering
Business Address:综合实验三号楼410
Contact Information:041184707174
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Current position: Home >> Scientific Research >> Paper Publications

Optimal allocation of resources for yard crane network management to minimize carbon dioxide emissions

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Indexed by:Journal Papers

First Author:Peng, Yun

Correspondence Author:Wang, WY (reprint author), Dalian Univ Technol, Fac Infrastruct Engn, Dalian 116023, Peoples R China.

Co-authors:Wang, Wenyuan,Song, Xiangqun,Zhang, Qi

Date of Publication:2016-09-10


Included Journals:SCIE、EI、Scopus


Page Number:649-658

ISSN No.:0959-6526

Key Words:Container terminals; Container gantry crane; Energy replacement management; Carbon emission reduction

Abstract:Electric rubber tire container gantry cranes (ERTGs) have already been widely used to replace rubber tire container gantry cranes (RTGs) in many ports of the world, especially in China. ERTGs can reduce carbon dioxide emissions by shifting energy demand from diesel to electricity (energy replacement). It takes almost 6-12 months to change a RTG to an ERTG, and the changed yard cranes cannot work during the replacement phase due to the mechanical reformation and electrical power system construction etc. Therefore, the yard crane network will generate bottlenecks in the container flow and influence the service level when energy replacement happens. This paper focuses on the problem of allocating limited resources for yard cranes to reduce the carbon emissions. The main challenges are how to solve the energy replacement problem at a network level and how to cope with the high uncertainties in the container terminal transportation network. Therefore, we model the energy replacement problem with the purpose of minimizing the carbon emissions by combining an allocation resource mathematical model and a simulation model of the whole transportation network together. The first stage of the energy replacement problem is to make energy replacement decisions each year, while the second stage is to evaluate the value of a seaport's service level based on the realized decisions by running the simulation model. However, the service level indicator is a random variable dependent on the decisions in the mathematical model, which should be controlled to make the seaport work normally at a network level. As an example, the optimization and simulation procedures are applied to a major container terminal in China. The proposed model is general and can be applied to the energy replacement problem of any other seaport. (C) 2016 Elsevier Ltd. All rights reserved.