(729e) A Coupled Lagrangian-Eulerian Model for Numerical Simulation of Wind Turbines Performance Under Rainy Conditions
Wind Turbines power output is constantly influenced by their environmental conditions, including raining and icing. Therefore, understanding the effect of rain is necessary to enhance the efficiency of the wind turbines used in regions with considerable number of rainy days.
To obtain this understanding, we developed a new multiphase computational fluid dynamics (CFD) modele by coupling the conventional Lagrangian Discrete Phase Model (DPM) and the Eulerian Volume of Fluid (VOF) models to be able to simulate the rain and capture the resulting water layer formation over the turbine blades. In this study, we used National Renewable Energy Laboratory’s (NREL) S809 airfoil profile of a horizontal-axis wind turbine. In addition, we included the effect of surface tension as well as the surface property of the airfoil.
We used our model to run several simulations in order to identify the effect of each of the following factors: the momentum that rain droplets add to the water layer in addition to their mass, surface tension, and contact angle between water and airfoil.
Our simulation showed that, in general, the rain causes significant increase in drag coefficient compared to the no-rain condition. The more non-wettable the surface is, the larger this unfavorable increase in drag coefficient will be. In case of the lift coefficient, it was observed that for the most part, the rain favorably increases the lift coefficient and this increase was significant for wettable surfaces. We also found out that, the effect of surface tension between water and air on the lift and the drag coefficients is considerably more that the effect of the momentum of the rain droplets.
Based on our results, we can claim that a wind turbine with a wettable surface will suffer the least drag from a rainy atmosphere and, in certain conditions, might even benefit from it through the increase in lift force.
This paper has an Extended Abstract file available; you must purchase the conference proceedings to access it.
Do you already own this?
Log In for instructions on accessing this content.
|AIChE Graduate Student Members||Free|
|AIChE Undergraduate Student Members||Free|