The FLOW-CAM project addresses the supervision of dynamic energy cables in floating offshore wind farms. Increasing offshore wind installations is needed to meet Europe’s renewable electricity generation targets. For this, Europe should focus on Floating Offshore Wind (FOW): FOW holds the key to an inexhaustible resource potential: 80% of wind resource is located in waters 60m and deeper, where Bottom-Fixed Offshore Wind (BFOW) is not relevant; moreover, larger turbines can be installed on FOW substructures, making FOW more attractive.
The principal costs of offshore wind farms are the turbines, the foundations and the electrical connection to the shore. Construction costs are followed by maintenance costs.
Cable failures have a dramatic impact on both the availability of the energy and farms insurance costs. In 2015, subsea cable faults contributed to 77% of the financial losses of global offshore wind projects and led to insurance claims totaling 25% more than in 2014 (source: GCube Underwriting).
The FLOW-CAM project aims at studying new methods for the inspection, detection and structural health monitoring (SHM) of defects in the electrical interconnection system of FOW farms. The integration of this monitoring in a predictive maintenancestrategy can lead to a drastic reduction of maintenance and insurance costs. To reach this objective, the project will develop a multiphysicsmodel to connect the very fine damage mechanisms of the conductive wires (inter-wire sliding / friction, partial plasticity of one or more wires, etc.) to the physical properties (electrical and thermal). Based on this better understanding of the physics of failures, new SHM and defect detection methods will be studied, based on the use of multisensing systems, an underwater remotely operated vehicle and AI-based data analytics.
To reach this objective, the French and Turkish partners will develop a multi-physics model to link the very fine damage mechanisms of the conductive wires (inter-wire sliding / friction, partial plasticity of one or more wires, etc.) to the physical properties (electrical and thermal).
Based on this better understanding of the physics of failures, new Structural Health Monitoring (SHM) and defect detection methods will be studied, based on the use of multisensing systems (Optic Fiber sensors, Quantum-Resistive strain sensors, Reflectometry and Partial Discharge sensors), an underwater remotely operated vehicle and AI-based data analytics.
FLOW CAM is funded by the MarTERA partners French National Research Agency (ANR) and The Scientific and Technological Research Council of Turkey (TÜBITAK).
Mrs Marie-Bénédicte Jacques, CEA, France
CEA, Research institute, France
Université Gustave Eiffel (IFSTTAR), Research institute, France
TEKNOPAR, SME, Turkey
Desistek Robotik Ltd. Sti., SME, Turkey
MEDYSYS, SME, France