Optimisation of Air turbines for OWC Wave Energy Converters: Sensitivity of Realistic Wave Climates
Keywords:Wave Energy, Oscillating Water Column, Air turbines, Optimisation, Genetic Algorithms, Wave Climates
Wave Energy, Oscillating Water Column, Air turbines, Optimisation, Genetic Algorithms, Wave climates.
Among all the Wave Energy Converter (WEC) technologies suggested in the last decades, the Oscillating Water Column (OWC) technology seems to be the most robust and reliable technology. Different are currently in operation, such as the Mutriku Wave Power Plant installed in a harbour, or are being developed, such as the MARMOK floating OWC device developed by IDOM and tested for over a year in the Biscay Marine Energy Platform (BIMEP). One of the key elements of the OWC technologies is the power take-off (PTO) system that converts the pneumatic energy trapped in the chamber into electrical energy. Such PTO system consists of an air turbine coupled to an electric generator, and has been the object of several studies, including numerical and experimental works that cover a wide range of different air turbine configurations, and some of the proposed research lines even reaching to combine both approaches. The most common turbine, mainly due to its relative simplicity both on the conceptual and
mechanical aspects, is the Wells monoplane turbine, including variations such as the biplane and the counter-rotating configurations. However, other configurations such as the impulse turbine or the more recent bi-radial turbine have also been analysed.
The preliminary design of these turbines usually relies on analytical models based on the blade element method, using dimensionless parameters for representing the behavioural charts of the different configurations. In fact, in order to better represent the behaviour of air turbines in realistic conditions with polychromatic waves, it is usual to consider the stochastic version of these dimensionless parameters so that they provide an overall indicator of their sea-state-related behaviour. However, the air turbines, regardless of their configuration, include a large number of different geometrical parameters, which complicates the optimisation procedure and leads to a decision-making process that relies on an expertise-based intuition. In this sense, suggests an optimisation method based on a Genetic Algorithm (GA) that enables the articulation of all the relevant parameters. This GA-based optimisation method articulates the information about the hydrodynamic behaviour of the WEC and the pneumatic conversion within the chamber. Hence, the optimisation is sensitive to the characteristics of the wave climate and, thus, the behaviour of the WEC in that specific wave climate.
However, in order to make wave energy economically viable, mass production of the WECs, including their PTO systems, is a crucial point. As a consequence, standard WEC floaters and PTO system elements may need to be used in the different locations under different resource conditions. In order to evaluate the sensitivity of the optimal air turbine designs to the characteristics of specific wave climates, the present study will define optimal air turbines for different locations worldwide, comparing the characteristics of the different designs.
How to Cite
Some rights reserved. Please see https://ewtec.org/proceedings/ for more details.