Session: 09-09-01 Hybrid Energy: Hybrid Marine Renewables

Submission Number: 181077

Decision-Oriented Optimization of a Hybrid Wind–Wave Floating Platform: Sweep-Refined GA Screening and Most Time-Domain Validation 

Large-scale expansion of floating offshore wind into deeper waters must contend with resource variability, grid bottlenecks, and sustained cost pressure. Pairing wind turbines with wave energy converters on a shared platform offers practical relief: the wave resource can “top up” output when wind resources is weak, can shorten access delays by moderating local sea states, and shared moorings, export cables, and marine campaigns can lower system-level costs. The engineering challenge is that platform motions, wave-device hydrodynamics, turbine aerodynamics, and control behavior are tightly coupled, creating interacting objectives and constraints that must be treated together rather than in isolation. Design exploration must therefore resolve hydrodynamics and control interactions with sufficient fidelity while keeping the search computationally tractable and the decision process transparent. To address these challenges, a bilevel optimization is formulated and applied to a hybrid wind–wave platform, allowing rigorous exploration of the tightly coupled design space without compromising physical fidelity. The workflow first screens candidate designs with low-fidelity models, then carries the most promising cases forward to mid-fidelity time-domain analysis. At the outer level, the floating substructure of the Wind turbine coupled with the wave energy converter device are analyzed in the frequency domain using linear potential-flow hydrodynamics to obtain added mass, radiation damping, excitation, and response operators across wide sweeps of geometry and relative placement. The hybrid platform consists of a spar-type floating substructure integrated with a coaxial, torus-shaped heaving-buoy wave energy converter (point absorber), representative of the Spar–Torus Combination archetype. A genetic algorithm drives the global search and identifies non-dominated candidates against two primary objectives: maximizing energy capture and minimizing a levelized-cost proxy based on structural mass and fabrication surrogates. Constraint handling is embedded to limit platform motions and to preserve a minimum operating margin in the power-take-off (PTO). Promising designs are subsequently refined in the time domain. A multibody model implemented within the WEC-Sim/MOST environment represents the coupled spar–torus system with rigid bodies, kinematic joints and constraints, moorings, and a direct-drive electric PTO. The PTO is modeled using the WEC-Sim/PTO-Sim electric-generator formulation (direct-drive linear generator block), so that the electromagnetic reaction force and electrical power are computed consistently with generator constants and converter dynamics. Representative irregular seas are simulated to evaluate absorbed wave power, platform motions, generator force and current demand, and controller interactions along full time histories. This stage captures effects not visible in frequency-domain screening, including phase relationships between device and platform motions, transient electromechanical loading, and time-varying coupling between the wind turbine and the wave device. A transparent, decision-oriented screening is applied to the optimized set to select a final configuration. Sensitivity checks on the weights are performed to ensure that the top-ranked design remains stable under plausible shifts of priority between energy yield and cost-related metrics. The case study shows that global frequency-domain exploration guided by a genetic algorithm efficiently filters dominated layouts and reveals the governing trade-offs. Time-domain multibody refinement then consolidates energy gains while keeping motions and PTO demands within operational envelopes. The resulting hybrid platform design achieves simultaneous improvements in energy capture and motion performance relative to baseline configurations. The overall framework is reproducible, computationally tractable, and readily transferable to other hybrid archetypes and turbine classes, providing a clear path from broad parametric exploration to controller-aware, time-domain validation suitable for engineering decision making at the concept-selection stage.

Presenting Author: Ermando Petracca Politecnico di Torino

Presenting Author Biography: Ermando Petracca is a final-year PhD candidate in Mechanical Engineering at Politecnico di Torino, focusing on the optimization and control of hybrid offshore wind–wave energy platforms. His research combines hydrodynamics, aero-servo modelling, and techno-economic analysis to develop efficient and resilient marine renewable systems.

Authors:

Ermando Petracca Politecnico di Torino
Davide Issoglio Politecnico di Torino
Giuseppe Giorgi Politecnico di Torino
Giovanni Bracco Politecnico di Torino