With ABB Ability™ Marine Advisory System – OCTOPUS and robotic maintenance working together, windfarm vessels’ working hours could increase by over a third, analysis calculates
A desk study from ABB focusing on the ATLANTIS offshore test location, off the coast of Viana do Castelo, Portugal, concludes that the gains are available to operators prepared to commit to fast-emerging robotized maintenance technology.
The safe transfer of personnel between a support vessel and an offshore turbine platform is often the limiting factor in maintenance hours, where rough seas mean crews cannot land by walkway or from the air. In cases where maintenance can be carried out using robotics instead of personnel, the same restrictions would not apply.
ABB Marine & Ports is a key technology partner for the EU-funded ATLANTIS research project, which is exploring the use of remote offshore inspection and maintenance techniques for wind farms. The project also seeks to optimize offshore wind farm vessel uptime by expanding the understanding of the relationship between hydrodynamics and safe vessel availability. ABB’s contribution has been to develop a dedicated mission planning tool for offshore windmill parks, based on the ABB Ability™ Marine Advisory System – OCTOPUS.
OCTOPUS enables operations to be planned using safety limits based on acceptable vessel responses, rather than solely on the wave conditions. The new study calculates the extent to which vessels deploying robotics-based maintenance, rather than personnel, can work across a wider operational window.
“Accurate advice prevents costly last-minute cancellations in challenging but acceptable weather conditions, also providing clarity in situations where vessels can be idle in port when they should be working on site,” said said Antto Shemeikka, Vice President Digital Services, ABB Marine & Ports. “Planning precision also means that the OCTOPUS system helps reduce unnecessary fuel costs.”
The ABB study analyzed data at the ATLANTIS Offshore test center location, establishing that wave heights are on average below these limits 34 percent of the time. Acceptable wave heights for wind farm vessel maintenance personnel transfer are given as 1.5m. Deploying robotics-based maintenance solutions would allow a tighter acceptable safety margin, and operational wave heights to be raised to 2m. In this case, safe vessel operations could take place 46 percent of the time, raising workable vessel hours 35 percent over the original weather windows.
“For windfarm vessel owners and charterers, the opportunities which smart decision support technology creates for increased uptime are truly exciting,” said Dr. Andry Maykol Pinto, Project Coordinator, ATLANTIS. “We firmly believe that remote solutions will play a greater role in vessel operations in the future, with smart decision support systems such as our OCTOPUS suite of products increasing efficiency without any compromise on safety.”
The ATLANTIS research project is being staged at two monitoring testbeds in the Atlantic Ocean – one off the coast of Viana do Castelo, Portugal, and the other further out to sea. By better understanding how vessels and robots behave, researchers will identify opportunities to improve inspection and maintenance procedures. With funding from the biggest EU research and innovation program Horizon 2020, the project is targeting a more efficient, cost-effective and sustainable offshore ecosystem. The project results will be made available under EU’s Community Research and Development Information Service (CORDIS).
The ATLANTIS project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 871571. For further information about the ATLANTIS test center, research work and the partners, please visit https://www.atlantis-h2020.eu
The Community Research and Development Information Service (CORDIS) is the European Commission’s primary source of results from the projects funded by the EU’s framework programs for research and innovation. https://cordis.europa.eu/project/id/871571
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