Tuesday, October 13, 2020

Technology Aimed at Reducing Ferry Emissions by Targeting Efficient Vessel Operation

Optimising Trim, Speed and Other Variables Now Possible with Data Analysis
Shipping News Feature

DENMARK – Last month ferry group DFDS set out its long term plans for the reduction of its environmental footprint, principally cutting carbon emissions. Now the company has upscaled its existing partnership with vessel performance specialist GreenSteam to co-develop and supply an enhanced performance platform to reduce the shipping firm's greenhouse gas emissions by 25-35% over the next decade.

DFDS and GreenSteam have been collaborating for over five years and already have performance optimisation systems installed on 18 vessels. The first service which will be rolled out on the new enhanced performance platform across DFDS’ full fleet is Dynamic Trim Optimiser (DTO). DTO captures high frequency performance data from on-board sensors and integrates this with the vessel’s digital model to calculate optimal trim settings that will maximise efficiency. It has been shown to reduce annual fuel consumption by up to 6%.

The object is to overcome one of the long standing problems when it comes to reducing harmful emissions, quantifying how much fuel has been wasted due to controllable factors, such as trim, speed and fouling, and taking remedial action in real-time, has historically been unfeasible. This is due to the vast amounts of vessel and environmental data that needs to be analysed in order to present accurate findings in a timely manner.

The two companies believe that by harnessing machine learning, GreenSteam’s software is able to address these challenges, making it possible to build vessel specific models for each vessel that creates a platform for real-time decision support to make live changes. This begins by creating a digital performance model of the vessel based on data across 13 different variables, encompassing ship performance and environmental conditions. GreenSteam’s AI platform identifies the impact each factor has on fuel usage.

The technology outfit’s Dynamic suite of services converts this information into operational recommendations while the vessel is in transit. These insights enable the crew to make fuel-saving decisions in real time, saving time and money while reducing emissions. Tools from this Dynamic suite will form the basis of DFDS’ unique enhanced performance platform. Shaun Gray, Executive Chairman, GreenSteam, commented:

“This partnership signifies the next step in our work with DFDS to deliver long term and widespread benefits to their operations. Together, we have demonstrated that a dynamic, machine learning-driven approach can support crews to make the most fuel-efficient decisions for any given voyage.

“As DFDS has recognised, reducing emissions doesn’t have to be at the cost of profitability, and in fact, both can be achieved and enhanced with machine-learning driven optimisation of vessel operations. We look forward to continuing to develop our enhanced performance platform to help DFDS continue to lead in environmental standards and drive down bottom-line costs.”

The rollout of the hardware across DFDS’ fifty strong fleet of freight and passenger ships will commence at the beginning of Q4 2020 and is expected to run through into early 2021. Jacob Pedersen, Head of Projects and Implementation, DFDS, said:

“After trialling and testing GreenSteam over many years, we have been impressed by the reduction in fuel consumption that can be achieved by applying machine learning to optimise even one aspect of vessel operations. Prior to signing our latest partnership agreement, we evaluated vendors from across the globe and are satisfied that our original partner, GreenSteam, is still significantly ahead of the curve with its real-time decision support service.”

“We are committed to driving down our greenhouse gas emissions across the fleet, while continuing to provide our award-winning service. Our partnership with GreenSteam will allow us to identify and cut down on unnecessary fuel consumption across our entire fleet.”