ANN-based Wells turbine airflow estimation for airflow control in Oscillating Water Columns скачать в хорошем качестве

ANN-based Wells turbine airflow estimation for airflow control in Oscillating Water Columns

Paper submitted to the 11th International Renewable Energy Congress (IREC 2020) Abstract: This paper presents the design and development of an Artificial Neural Network (ANN) capable of estimating the required airflow speed for an airflow control strategy used to prevent the stalling phenomenon in Oscillating Water Columns (OWC) equipped with Wells turbines. The ANN is trained to recognize incoming waves susceptible to provoke the stalling behavior. The proposed control scheme will govern an air valve in the duct to regulate the incoming airflow. Performances of the designed ANNs have been analyzed to select the best model. The implemented ANN airflow control has been tested with two different wave conditions and results prove the effectiveness of avoiding the stall effect which enhanced the power generation.