Driving increased accuracy in sea state characterisation
Developed by researchers at the University of Hull, SmartWave is a remote monitoring tool that combines satellite data with Artificial Intelligence (AI) to provide sea state characterisation on a much greater degree of accuracy.
This leads to a reduction in health and safety risks and operational costs in offshore wind farms due to better informed scheduling of programme activities and O&M trips.
While Offshore Wind is now one of the cheapest forms of electricity generation, Operations and Maintenance (O&M) costs remain high, accounting for an estimated 25% of the lifetime cost of an Offshore Wind farm. As operators build ever larger wind farms, sited further out to sea, maintenance costs are escalating, not least due to the volume of maintenance trips that have to be aborted due to the unforeseen height of waves in the seas around the wind turbines.
The traditional method of simulating wave height relies on a numerical simulation of physics-based models, which provides one unified forecast for a large area. This method is not accurate enough to provide sea state characterization a more granular wind turbine level – which is a problem as the sea state can vary widely across a relatively small area. Turbine accessibility is a key determinant of a wind farm’s profitability as failed maintenance trips can limit turbine performance and ultimately the overall energy output of a wind farm.
By enabling sea state characterization at a much higher resolution, SmartWave provides more accurate analysis, leading to greater O&M efficiencies and much reduced costs and risk. An added benefit is that SmartWave is self-learning with continued observational data, and does so at a much lower cost than that required for equivalent numerical simulations.
By providing high resolution spatial sea state maps, routing of Crew Transfer Vehicles (CTVs) through calmer seas is also possible, which in turn may reduce the impact of physical fatigue, improving Health and Safety and working conditions for technicians undertaking essential offshore activities.
SmartWave’s innovative machine learning approach brings together integrated site-specific data (such as bathymetry and site configuration data) and remote monitoring data from the Synthetic Aperture Radar (SAR) on board European Space Agency satellites.
SmartWave processes data at satellite resolution, currently ~10m, and is applicable down to the practical spatial wave-length scale, ~100m, compared with the 1.5km scale of existing publicly available models.
This enables SmartWave to provide assessments of sea roughness and wave height that are very high resolution and enable sea state forecasting at a much more granular level.
And because SmartWave uses Artificial Intelligence, it can achieve a greater computational efficiency at lower cost, compared to traditional numerical models; once its neural networks have been trained it is computationally very efficient. Further accuracy improvements are also possible by adding additional data sources.
SmartWave is a tool that is readily deployable to any site around the world, as the satellite data is available globally. It can be used in a variety of settings with multiple advantages. As well as supporting Offshore Wind operators with their planning and O&M activities, there is potential for SmartWave to feed into the siting of new Offshore Wind developments. SmartWave can support other marine industries that rely on accurate metocean forecasting, including marine renewables, transport and marine construction, as well as the fishing and water leisure industries. SmartWave would also integrate easily with existing marine forecasting tools, increasing their accuracy and competitive advantage.
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