Renewable energies are believed to play the key role in assuring a future of sustainable energy supply and low carbon emissions. Particularly, this thesis focus on wave energy, which is created by extracting the power stored in the waves of the oceans. In order for wave energy to become a commercialized form of energy, modular deployment of many wave energy converters (WECs) together will be required in the upcoming future. This design will thus allow to benefit, among others, from the modular construction, the shared electrical cables connections and moorings, the reduction in the power fluctuations and reduction of deployment and maintenance costs. When it comes to arrays, the complexity of the design process increase enormously compared with the single WEC, given the mutual influence of most of the design parameters (i.e. hydrodynamic and electrical interactions, dimensions, geometrical layout, wave climate etc.). Uppsala University has developed and tested WECs since 2001, with the first offshore deployment held in 2006. The device is classified as a point absorber and consists in a linear electric generator located on the seabed, driven in the vertical direction by the motion of a floating buoy at the surface. Nowadays, one of the difficulties of the sector is that the cost of electricity is still too high and not competitive, due to high capital and operational costs and low survivability. Therefore, one step to try to reduce these costs is the development of reliable and fast optimization tools for parks of many units. In this thesis, a first attempt of systematic optimization for arrays of the Uppsala University WEC has been proposed. A genetic algorithm (GA) has been used to optimize the geometry of the floater and the damping coefficient of the generator of a single device. Afterwards, the optimal layout of parks up to 14 devices has been studied using two different codes, a continuous and a discrete variables real coded GA. Moreover, the method has been extended to study arrays with devices of different dimensions. A deterministic evaluation of small array layouts in real wave climate has also been carried out. Finally, a physical scale test has been initiated which will allow the validation of the results. A multi--parameter optimization of wave power arrays of the Uppsala University WEC has been shown to be possible and represents a tool that could help to reduce the total cost of electricity, enhance the performance of wave power plants and improve the reliability.

One way to lower the levelized cost of energy for wave power plants and paving so the way for commercial success, is to increase the power absorption by use of advanced control algorithms. This thesis investigates the influence of the generator inertia, the generator damping and the layout on power absorption and presents a new model free strategy of controlling wave energy converters.

The evaluation of all control strategies was done in a numerical simulation and in experimental 1:10 model scale wave tank tests conducted in the COAST laboratory at the University of Plymouth. The WECs used are inspired by the wave energy concept developed at Uppsala University.

The influence of the generator inertia on the power absorption was tested with an uncontrolled WEC. Compared to a conventional WEC the power output could be significantly increased for small waves and high wave periods.   

As a simple and easy to implement control strategy, a WEC with sea state optimized generator damping was used to create a power matrix. The optimal damping factor depends on both, wave period and wave height. The power absorption increases with the wave height and when the wave period converges towards the oscillation period of the WEC.

A genetic algorithm was used to obtain the optimized layouts for wave energy farms, which suggest that the converter should be placed in rows parallel to the wave front, and the position in the array has nearly no influence on the optimal control parameter.

Then a collaborative learning approach using machine learning is presented, with several identical wave energy converters in a row to parallelise the search of the optimal control parameter. It was implemented to control the generator damping factor and the latching time. With the latter the power could be increased significantly.

Vågkraft kan bli en viktig del från framtidens elektriska energikälla. Men därför kostnaden per producerat energienheten måste minskas. En väg att minska kostnaden är att förbättra effektiviteten med ett avancerat styrsystem. Den här avhandlingen tester olika kontrollstrategier för att hitta en bra strategi för vågkraftverk i parker. Alla strategier testas med an numerisk simulering och ett fysiskt test med en 1:10 skalad modell i en våg bassäng.

Först är en elektrisk vågkraft konverter (WEC) med optimerad naturlig frekvens men utan styrsystem är testad. WECen absorberar hög effekt i ett litet område med de vanligaste vågklimatet. Storlek på området kan varieras med generatorns dämpning och bästa vågperiod kan ändras med WECens tröghet.

En generator med optimal dämpningsfaktor testas, för att en justerbar generator dämpning är relativt lätt att implementerar. Numerisk simulering visade att optimal dämpningsfaktor beror på vågperiod och minskar när våghöjden ökar. Beroende av effekten från våghöjd kan ses i numerisk simulation och fysiksals test, men beroende av effekten från vågperiod kan ses bara i numerisk simulation.

Därefter, en modell oberoende strategi (som kallas CL) för vågkraftkonverter i arrayer är presenterat och testad för att styra (1) generator dämpningsfaktor och (2) latching tid. Resultat är att den CL kontrollerade generatorn dämpning endast visar små fördelar med absorberat energi. Men med en CL optimerat latching tid, absorberat effekten ökas mer som 100\% i vissa vågklimat.

Many wave power conversion devices, especially point-absorbers, do not provide alone the necessary amount of converted electricity to be cost effective, instead they are designed to be deployed in arrays of many units. Such arrays, or parks, can satisfy a large-scale energy demand, reduce the costs of the produced electricity and improve the reliability of the system.

The performance of a wave energy park is affected by multiple and mutually interacting parameters, and the complex problem that arises during its design is called array optimization.

The scope of the present thesis is to study such systems and their design, by the development of an optimization routine able to predict the best layout of a wave energy park under fixed constraints. The wave energy converter considered is the point-absorber developed at Uppsala University, which consists of a linear electric generator located on the seabed and a floating buoy at the surface.

An optimization routine based on a genetic algorithm was created, which allows simultaneous optimization of the geometry of the buoys, the damping coefficient of the linear generators and the geometrical layout of the park.

Finally, an experimental campaign with a single device and three arrays of six devices was conducted in order to compare the theoretical results with experimentally acquired data.

The results identify optimal configurations of wave energy arrays, and highlight the effect of optimizing upon different objective functions, including economical ones. In the experiments, standard models and common assumptions used for wave energy park optimizations were tested against realistic conditions.