Two-Stage Optimization on Marine Debris Collection by Hybrid Energy Vessels
The harm of marine debris (MD) to the environment and human beings has been paid more and more attention. At present, the most effective way to collect macro-MD floating on the sea is to send vessels. Our research framework is to use remote sensing to locate the initial location of debris, predict its drifting trajectory by GNOME software, and employ vessels equipped with a hybrid energy system (HES) composed of photovoltaic (PV), battery and diesel to carry out MD cleanup. In order to simplify the problem, we propose a two-stage optimization approach of vessel routing and energy management strategy. In the first stage, the vessel routing problem with floating time window is modeled to minimize the vessel travel time considering the continuous speed. The floating time window means that multiple time windows are set on the drifting trajectory of MD, which is used to depict its dynamic nature. Therefore, this problem is defined in a logistics space-time network. We propose an adaptive large neighborhood search algorithm considering elitist strategy coupled with speed optimization to solve this problem. In the second stage, a mixed integer linear programming model for energy management strategy is established to minimize the total cost, including the power generation cost of diesel and photovoltaic, the battery charge and discharge cost and the carbon tax cost. The model takes the power load balance, the power limit of each part of the hybrid energy system and the battery charge and discharge state as constraints. We analyze the power flow between HES and the vessel load through a numerical example, and compare the cost and carbon emissions under three illumination intensities. Even taking into account life cycle carbon emissions, vessels with HES have an overwhelming advantage in terms of both cost and carbon emissions compared to pure diesel vessels. The results also not only demonstrate that floating time window is superior to a single time window, but also reveal the importance of the selection of time window combination. Some suggestions on rational utilization of hybrid energy vessels with long and short trip are put forward
Year of publication: |
2023
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Authors: | duan, gang ; Zhang, Kaibin ; Ma, Junfeng |
Publisher: |
[S.l.] : SSRN |
Saved in:
freely available
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