Highlights We develop an optimization model that integrates spatial and temporal dimensions for strategic planning about whether and when to retrofit ships to use shore side electricity. We used an improved multi-objective genetic algorithm (NSGA-II) to solve the optimization model. We applied the proposed model to a case study of container ships calling at Dalian Port in China to support its effectiveness and applicability.

    Abstract Shore side electricity (SSE) is the use of electricity from the shore to power a ship’s system when it is berthing at ports. It is a solution to reduce the emissions of auxiliary engines at berth and to improve the local and regional air quality. This paper develops a multi-objective model that integrates spatial and temporal dimensions for strategic planning regarding whether and when to retrofit ships to use SSE. The strategic planning problem is to maximize the environmental benefit and to minimize the payback period of the investment over the entire planning horizon. By adopting an improved multi-objective genetic algorithm (NSGA-II), a series of retrofit strategies for container ships calling at Dalian Port in China are obtained under a projected annual visiting frequency of ships with different ship sizes and shipping lines. Depending on a selected retrofit strategy, the sum of the payback periods of ships that are determined to be retrofitted is 46 years (on average less than four years) and the environmental benefit of using SSE can be up to 128 million USD for Dalian Port in the planning horizon from 2020 to 2035. The results show that using SSE is an efficient method to decline emissions within the maritime sector and validate that the proposed methodology can be useful to ship owners to decide upon investing in SSE applications and to promote the development of green shipping and green ports.


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    Title :

    Strategy development for retrofitting ships for implementing shore side electricity


    Contributors:
    Yu, Jingjing (author) / Voß, Stefan (author) / Tang, Guolei (author)


    Publication date :

    2019-01-01


    Size :

    13 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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    Free access