Simulation of the atmospheric behavior for the environment of a small-scale wind turbine

Abstract

This study investigates a method using computational fluid dynamics (CFD) to model low-elevation atmospheric conditions. There are three goals in this research: to analyze the wind behavior downwind from buildings and trees, to validate the accuracy of the simulations by comparing wind measurements to the simulation for a specific site, and to find a relationship between the wind speed and the power output of a small-scale wind turbine. The first goal is to define a proper CFD model for buildings and trees. The trends in the Strouhal number are found to correlate to changes in building height and the wind resistance of a tree as supported in literature, with minor differences with the addition of a tree. The second goal of this study is to model an actual low-elevation environment to compare the energy output predictions for a small-scale wind turbine versus traditional methods. The simulations are compared to on-site wind measurements at a suburban wind turbine, recorded by the rotor and two anemometers installed on the wind turbine tower. The measurements and simulations presented in this study show an improvement in the accuracy in the estimation of the energy output of a wind turbine versus using traditional methods involving high-elevation wind maps. The third goal is to provide a relationship between the wind speed and the power output of a small-scale wind turbine. To accomplish this task, system identification is implemented. The traditional auto-regressive model with exogenous input variables (ARX), its moving average counterpart (ARMAX), and the output error (OE) model are compared in this study. It is found that the transfer function provided by the ARX model most sufficiently estimates the power output of the studied wind turbine, with power output accuracies of 83%. With all three goals addressed, the feasibility of small-scale wind turbines in different low-elevation environments is assessed. In accomplishing these tasks, the siting of a small-scale wind turbine can be optimized qualitatively and quantitatively.