Optimal Routing and Sustainable Operation Scheduling of Large Ships with Integrated Full-Electric Propulsion

Epameinondas K. Koumaniotis and Fotios D. Kanellos ()
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Epameinondas K. Koumaniotis: School of Electrical and Computer Engineering, Technical University of Crete, 73100 Chania, Greece
Fotios D. Kanellos: School of Electrical and Computer Engineering, Technical University of Crete, 73100 Chania, Greece

Sustainability, 2024, vol. 16, issue 23, 1-18

Abstract: The continuously intensified pursuit to reduce emissions related to human activity and the increased competition in maritime sector calls for sustainable and well-planned solutions to conform with environmental constraints and maximize profit, respectively. In a sector that is very critical for human activities, such as the maritime industry, it is essential to be able to reduce ship emissions without increasing the overall cost of operations and the time to transfer the cargo. All these parameters make ship routing and ship emission reduction very crucial. This work examines the effective routing of large ships with an integrated full-electric propulsion system and the optimal power generation scheduling of their generators to attain the minimum possible operational cost. To achieve this, the problem was formulated, modeled and solved in two stages, namely, ship routing and power generation scheduling, respectively. The first stage was solved using the Particle Swarm Optimization (PSO) method and the second one with a conventional optimization algorithm based on the steepest decent concept. The proposed ship routing method is based on the sea resistance concept and the minimization of total ship propulsion energy. The obtained results show that the optimal path is a combination of the minimum distance path and the minimum resistance path. Ship sustainability is reinforced with the reduction in ship operation cost and ship emissions. Ship emission reduction is achieved in the second optimization stage using a suitable emission index that complies with IMO regulations.

Keywords: ship routing; optimization; Particle Swarm Optimization; sustainability; emission reduction; power generation scheduling (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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