Stochastic models are often used to evaluate the average power output of an oscillating-water-column (OWC) wave power plant equipped with a Wells turbine and for defining optimal control criteria of the system. The application of the stochastic model to OWC devices is based on the hypothesis that the dynamic behavior of the system can be modeled by a set of linear differential equations and that the sea surface elevation, acting as an input, has a Gaussian probability density function. Under such hypotheses, from the theory of the random processes of the linear systems, it comes that the outputs of the system, such as the pressure in the chamber and the turbine flow coefficient, have a gaussian distribution. Actually, there are several non-linear phenomena that can alter the linear behavior of a OWC device:
- minor and major losses of the unsteady flow of water and air;
- compressibility of air and heat exchange with the walls of the air chamber;
- non-linear characteristics of the turbine.
The stochastic model can be applied if such non-linearities have, on the whole, limited effects or if a specific procedure able to take them into account is adopted, as suggested by the authors in previous papers.
In the Authors’ knowledge, no experimental validation of the application of the stochastic model to OWC devices are present in the open literature.
This work, making use of data gathered during the experiment on a 1:10 scale model of a ocean OWC breakwater, put at the sea off the beach of Reggio Calabria, aims at verifying that the energy conversion process inside the OWC can be actually described as a gaussian process. To this purpouse, the frequency distribution of the main physical parameters, relevant to the system dynamics, are evaluated. Moreover, in order to characterize the behavior of the Wells turbine, the experimental values of the time averaged turbine torque and pressure drop are evaluated as a function of the variance of the flow coefficient. The results show a very high level of correlation and a very good agreement with those that can be obtained from the application of the stochastic model, using as an input the characteristic curves of the turbine, yelded in the unsteady flow.