Publications       Rudy Negenborn
Full Professor, Head of Section
Team & Themes

Title:A novel dynamical collaborative optimization method of ship energy consumption based on a spatial and temporal distribution analysis of voyage data
Authors:K. Wang, H. Xu, J. Li, L. Huang, R. Ma, X. Jiang, Y. Yuan, N.A. Mwero, P. Sun, R.R. Negenborn, X. Yan

Abstract:It is of significant importance to optimize the energy consumption of ships in order to improve economy and reduce CO 2 emissions. However, the energy use of ships is affected by a series of navigational environmental parameters, which have certain spatial and temporal difference s and variability. Therefore, the dynamic collaborative optimization method of sailing route and speed, which fully considers the spatial and temporal distribution characteristics of those factors is of great importance. In this paper the spatial and temporal distribution characteristics of the environmental factors and their related ship energy consumption profiles are first analyzed. Subsequently, a ship energy consumption model considering various environmental factors is established to realize the prediction of energy use of ships within the navigation region. Then, a novel dynamic collaborative optimization algorithm, which adopts the Model Predictive Control MPC strategy and swarm intelligence algorithm is proposed to further improve the ship's energy consumption optimization. Finally, a case study is conducted to demonstrate the effectiveness of the proposed method. The results show that the newly developed dynamic collaborative optimization method which fully considers the continuously time varying characteristics of environment al and operational parameters could effectively reduce the energy consumption in comparison to the original operational mode. In addition, the adoption of the MPC strategy produces better performance results compared to the optimization method without the MPC strategy.

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