As the interest in reducing carbon emissions continues, wind energy has become a prominent component of a carbon-free electrical supply. However, as wind continues to grow its presence in the electrical grid, a better understanding of its potential contributions is needed. One of the components that is required for this understanding is deeper knowledge of the physics of wind farms to improve physics-based modeling and more accurately predict the wind farm power output. Another component is discovering the extent to which wind farms can dynamically respond to the needs of the grid through power tracking where the wind farm tracks a power reference signal controlled by the grid operator.
In this work, we first present a coupled physics-based model for a wind farm to predict the total power out of wind farms of arbitrary geometry. The model combines two reduced order models, the first with a smaller scale on the order of individual turbines, and the other with a larger scale on the order of the scale of the whole farm. By coupling these two models, and the physics that they capture, the coupled model is able to provide insight and information on the behavior of the wind farm and predict the power output for multiple wind farm configurations. The results are verified with multiple large eddy simulation (LES) wind farm codes.
This work also presents a control-oriented wind farm model and its application to active power control. This control-oriented model uses a graph theory approach to represent the wind farm and the interactions between the turbines. This enables the model to represent dynamic changes that affect the wind farm, such as a change in wind direction or a dynamic yaw change. The effect of such changes is challenging to represent with conventional wake models. The model was validated for both representing a dynamic wind direction change and a dynamic yaw change. This model was incorporated into an inner and outer loop control framework where the outer loop consists of a yaw model-constrained optimal control and the inner loop consists of a pitch control. The controller was applied to an LES wind farm plant and showed the potential of dynamic yaw control in different wind farm operating conditions
