Energy-Efficient Speed Planning Considering Delay and Dynamic Waterway Conditions for Inland Vessels

S. Slagter*, Y. Pang, R.R. Negenborn

*Corresponding author for this work

Research output: Contribution to journalConference articleScientificpeer-review

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Abstract

The inland waterway transport sector is facing increasingly stringent legislation to reduce emissions and improve energy efficiency. Speed planning methods are an attractive option as they provide energy-efficient, timely and emission-reducing voyage planning for ships. However, current methods do not consider dynamic conditions of waterways and traffic. Due to these dynamic navigational conditions the static speed planning methods do not guarantee optimality, nor do they satisfy the constraints of the optimization problem throughout the journey. In this paper we propose an optimization structure that is based on the Model Predictive Control algorithm, which uses the most current information on water depth, water speed and expected delays to re-optimize the speed planning throughout the journey. Through a use case we show a 4.31% energy reduction compared to other speed planning strategies. Additionally, we show that the constraints regarding desired arrival times and safety are satisfied throughout the journey. Therefore, the method proves useful from a logistical, energy, emissions, and safety perspective. Modelling of uncertainties, lock interactions and predictions of waterway conditions will make our method an even more attractive option for speed planning.

Original languageEnglish
Article number11161
Number of pages12
JournalProceedings of the International Ship Control Systems Symposium
DOIs
Publication statusPublished - 2024
Event17th International Naval Engineering Conference and Exhibition, incorporating the International Ship Control Systems Symposium, INEC/iSCSS 2024 - Liverpool, United Kingdom
Duration: 5 Nov 20247 Nov 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Inland shipping
  • Model predictive control
  • Non-linear control systems
  • Voyage optimization

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