Optimal planning of operations at sea
Installation and maintenance operations at sea are costly and require significant material and human resources. Intervention windows, defined on the basis of metocean criteria, require reliable data and forecasts. Prior to the construction of the wind farms, it is crucial to optimally plan the installation and maintenance sequences and to estimate the project costs (CAPEX and OPEX). This requires the use of retrospective databases providing time series over long periods (CASSIOWPE project). During the operation phase of the farm, it is necessary to optimise the intervention windows and reduce the uncertainties in the forecasts. Probabilistic models are developed for this purpose in order to provide high-resolution forecasts on time scales of 5 min to 96 h (FLOWTOM project). A particular challenge has been identified in the Gulf of Lion in the Mediterranean, due to the significant temporal variability of the wind.
Proposing solutions for heavy maintenance at sea
For future commercial floating wind farms that will be far from the coast, it seems necessary to develop reliable solutions that allow heavy maintenance operations to be carried out at sea, such as the replacement of a major component of the rotor-nacelle assembly. Indeed, the strategy of returning to port seems to reach technical and economic limits in the case of large-scale development. One of the difficulties of heavy maintenance operations at sea is linked to the water depth at the sites envisaged, which exceeds the capacities of the self-elevating platforms currently used. It is therefore necessary to develop solutions based on floating supports and to meet the challenges associated with heavy lifting at height, with turbines of increasing size and load transfer between two floating means. A collaborative project has been initiated to contribute to the development of solutions adapted to this particular context (FLOWTOM project).
Monitoring during the operational phase
The development of in-service monitoring strategies including on-board sensors is essential to ensure the reliability of components over the farms lifetime and to optimise the ratio between performance and maintenance costs. A hybrid methodology is being studied to combine an on-board sensor network on an offshore system with a numerical simulation of the behaviour of this system using a model called a numerical twin. This approach makes it possible to go beyond the simple alert level by proposing system health diagnoses based on remotely monitored information and the results of the simulations. The first technological challenge is to assess the reliability, accuracy and redundancy requirements of in-service monitoring systems. The next step is to develop and validate the behaviour of digital twin models at the scale of a component or a system of components (SUBSEE 4D, DIONYSOS, DYNAMO projects). The calculation time and the estimation of the accuracy of these models constitute a second category of lock. At the farm level, it is important to define a sensor deployment strategy in line with the philosophy of operation, inspection and maintenance. Ultimately, the challenge is twofold: to ensure the highest possible system availability, while using the first floating wind turbine deployments as learning centres to optimise future designs and reduce the overall cost of energy.
Photo credit: Ian Dyball / AdobeStock
Characterising the atmosphere and sea surface interactions for the deployment of offshore wind in the Gulf of Lion
Floating offshore wind turbines operation and maintenance
A digital twin to facilitate the operation of floating wind farms
Digital intelligent operational network using hybrid sensors / simulations approach
Dynamic cable monitoring
Structural health monitoring strategy for FOWT in real-time
ORE Systems & Farms R&D Manager