Resumen de Electricity generation with direct drive wave energy converters: resistive loading control, grid integration and wave prediction
There is a global consensus on the use of renewable energies. In this context, the sea has great energy potential to be exploited in different ways, and it has been the subject of many studies. A significant group of technologies is based on the conversion of the ocean wave energy into electricity by a Wave Energy Converter (WEC). This thesis is focused on the direct drive system of a point absorber converter, where a buoy is connected to a Power Take-Off (PTO) system on the seabed. The energy conversion in the PTO is made through a Linear Permanent Magnet Synchronous Generator (LPMSG). In general, a major challenge for the exploitation of renewable energies is to improve their efficiency. In electricity generation from the energy of ocean waves, not unlike other technologies, the converter must be optimised to make the energy harvesting economically feasible. This thesis proposes a resistive loading control strategy of a point absorber in which the generated power is maximised by controlling the electromagnetic force of the generator with a resistance emulation approach. As a power electronic interface is required for grid connection, the resistance emulation approach has been implemented by a current controller. It must be able to handle with large variations of voltage and current, and also with large periods where these variables present low values. Therefore, a current source with a space-vector hysteresis-band and a constant switching frequency has been developed to be used with surface-mounted LPMSG. Also, a traditional hysteresis-band controller and a space-vector PWM controller based on voltage oriented control are implemented. This work assesses the performance of the current controllers mentioned above from the point of view of the overall conversion efficiency and dynamic response. Most control strategies to maximise the captured power by wave energy converters depend on the knowledge of the incoming wave in a short-term future. However, the wave prediction may be unpractical in a wave farm, since many measurement systems would be required. As a part of a prediction system, this thesis presents an estimator of the spatial sea surface elevation in a wave farm based on a single measurement point. The approach is based on a time delay artificial neural network. This work also explores the performance of the estimation for a given farm and the sensitivity to different sea characteristics. On the other hand, renewable energy is steadily increasing its penetration level in electric power systems. Wind and solar energy have reached a high degree of maturity, and their impacts on the grid are well known. However, this is not the case for emerging sources like wave energy. In this sense, this work explores the impact of the fluctuating power injected by a wave energy converter on the distribution grid voltage and proposes a strategy for mitigating the induced voltage fluctuations. The proposed corrective action makes use of the hardware resources already available in the WEC, employing a control strategy on the reactive capability of the grid-side converter. The use of a STATCOM as additional reactive compensation equipment is also explored.
