Data-driven design optimisation of the mooring system for a multi-float wave energy converter using system identification techniques

Mooring designs are a critical concern for the offshore renewable industry. The common design processes for mooring systems involve multiple, lengthy cycles of simulation and experimentation to achieve suitable designs. In this paper, we propose, for the first time, a computationally efficient and physically transparent data-driven design optimisation approach using real measurements from only an initial estimated specification of the physical mooring system. This is applied to a complex renewable energy platform, the multiple float wave energy converter M4, by system identification with frequency response driven optimisation, computing the optimised design within an hour on a laptop. More specifically, although mooring force is highly nonlinear in relation to wave input, it is demonstrated by system identification that it is almost linear in relation to surge motion. Further, the low frequency force, separated from the linear wave frequency force by a wavelet filter, is modelled as a resonant mass spring damper. This approach thus effectively models the nonlinear mooring system using two linear models. Finally, the physical parameters, namely mass, damping ratio, and stiffness, are optimised and compared using parameter sweeping and convex optimisation methods to minimise fatigue loads. The results demonstrate that the proposed approach is cost-effective and computationally efficient for mooring system optimisation for complex floating systems.