Abstract
With the extensive electrification introduced into the shipboard power systems, the navigation routine has become more important in an electric propulsion and solar power integrated ships since various sailing paths and speeds will lead to different operation performances. Unlike traditional navigation, which solves the shortest path problem, a data-driven optimization scheme is developed in this article for a photovoltaic (PV)-dependent navigation routing. In order to minimize the total cost and greenhouse gas emissions of an all-electric ship (AES), a new coordinated optimization framework is proposed to jointly optimize the energy storage system (ESS) sizing and voyage scheduling while considering solar power variations. Several cases are compared to verify the proposed method on a cargo ship, and numeral results reveal that the deep-learning-based forecasting method can better characterize the onboard solar power variations, and the proposed joint optimization framework can well accommodate the onboard PV generation.
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