Abstract
Oscillating water column (OWC) plants face power generation limitations due to the stalling phenomenon. This behavior can be avoided by an airflow control strategy that can anticipate the incoming peak waves and reduce its airflow velocity within the turbine duct. In this sense, this work aims to use the power of artificial neural networks (ANN) to recognize the different incoming waves in order to distinguish the strong waves that provoke the stalling behavior and generate a suitable airflow speed reference for the airflow control scheme. The ANN is, therefore, trained using real surface elevation measurements of the waves. The ANN-based airflow control will control an air valve in the capture chamber to adjust the airflow speed as required. A comparative study has been carried out to compare the ANN-based airflow control to the uncontrolled OWC system in different sea conditions. Also, another study has been carried out using real measured wave input data and generated power of the NEREIDA wave power plant. Results show the effectiveness of the proposed ANN airflow control against the uncontrolled case ensuring power generation improvement.
Highlights
Ocean energy is a more advantageous renewable resource compared to solar and wind
Converters of various types can be found across Europe, including oscillating water columns like Limpet in Scotland and NEREIDA in Spain [7], Sensors 2020, 20, 1352; doi:10.3390/s20051352
To evaluate the performance of the proposed control methodology, the Oscillating water column (OWC) wave power plant has been implemented by a complete wave-to-wire model on Matlab/Simulink, and a comparison between the uncontrolled and controlled cases has been performed
Summary
Ocean energy is a more advantageous renewable resource compared to solar and wind. It is more reliable since it is consistent throughout the day and night and more predictable, which can be foreseen several days in advance, and has significantly denser energy. Many ocean energy technologies have emerged to exploit this resource, especially for tidal and wave conversion systems. Both technologies are predicted to contribute the most to the European energy platform in the short to medium term (2025–2030) [4,5]. The majority of ocean energy-related industries are still in the early stage of development, ranging from theory, design, up to the demonstration phases [6]. Converters of various types can be found across Europe, including oscillating water columns like Limpet in Scotland and NEREIDA in Spain [7], Sensors 2020, 20, 1352; doi:10.3390/s20051352 www.mdpi.com/journal/sensors
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