Logo: to the web site of Uppsala University

Wave energy conversion technology has gained popularity due to its potential to be-come one of the most preferred energy sources. Its high energy density and low car-bon footprint have inspired the development of many wave energy converter (WEC) technologies, few of which have made their way to commercialisation, and many are progressing.

The Floating Power Plant (FPP) device is a combined floating wind and wave converter. The company, Floating Power Plant, was established in 2004 and has developed and patented a floating device that consists of a semi-submersible that serves as a foundation for a single wind turbine and hosts four wave energy converters (WECs). Each WEC consists of a partially submerged wave absorber whose pitching motion generates energy from incoming waves. The wave absorbers are connected to an oil hydraulic power take-off system located in a dry “engine room” above the free water surface, where the mechanical energy in the absorber is converted to electricity. When undergoing pitching movements, there are interactions between individual wave absorbers and the surrounding platform. This thesis focuses on developing methods to improve the FPP WEC’s hydrodynamic interactions.

The first part of this thesis optimises the wave absorber (WA) ballast. An ana-lytical model is developed to enable systematic selection of WA ballast combination with significantly less computational effort when compared with the more conven-tional means, such as using CAD software. The study suggests an algorithm with which the absorbed power and resonance frequency can be improved and adjusted by manipulating the ballasts’ mass, the position of its centre of gravity, placement and inclination of the WA. The proposed method is generic and can be applied to other WEC concepts or submerged bodies in general. The results show the feasibility of designing the absorber ballast to offer passive control for increased wave absorption. It demonstrates the effect of ballast on the WA inclination, resonance frequency and response amplitude operator (RAO).

The second part focuses on the optimisation of the FPP platform geometry. The genetic algorithm optimisation technique is implemented to maximise the annual en-ergy produced by the relative pitch motion of the WA to the floating platform. The optimised variables are characteristic lengths of the floating platform, most of which are part of the immediate surrounding walls of the absorber. The objective function is a function of the WA’s annual energy production (AEP) and RAO. Results show the feasibility of improving the hydrodynamic interaction between the floating platform and its integrated wave absorbers for a given wave climate by using a heuristic search technique. The number of iterations to convergence tends towards increased values when considering more optimised variables. It is also observed that the computational time appears to be independent of the number of variables but is significantly impacted by the computational power of the machine used.

This thesis contains interrelated studies aimed at increasing annual energy produc-tion and enhancing the hydrodynamic interaction within hybrid wind–wave energy converter systems. The first stage investigates how the mass distribution and posi-tion of a wave absorber can be adjusted to enable passive motion control, thereby improving wave energy capture. Following this, a geometric optimization framework is developed for a semi-submersible platform, employing genetic algorithm to identify design parameters that maximize power generation by optimizing the relative motion between the platform and integrated wave absorbers. The research further emphasizes the importance of reliable wave absorber models, demonstrating how robust forecast-ing, using machine learning, methods can be applied to adapt the system for varied oceanic conditions. The study extends the optimization framework to a multi-source offshore renewable energy park that includes wind turbines, floating photovoltaics, and wave converters. A permutation-based aggregator logic, inspired by a 3–8 line decoder and optimized using a genetic algorithm, allows for partial or full curtailment of individual energy sources in discrete steps. This strategy minimizes energy losses at the point of common coupling and balances the capacity factor. Finally, the study examines the impact of the wind turbine’s aerodynamic forces on the performance of the wave absorbers, revealing that steady wind conditions enhance wave energy capture, while turbulent wind introduces variability in absorber motion, slightly re-ducing efficiency. Collectively, the findings show an integrated approach, combining analytical models, numerical simulations, and advanced optimization techniques, that can substantially improve wave energy extraction, system stability, and overall annual energy yield.