Turbulent wind wake models are used to predict the impact of the wind wakes created by upstream wind turbines on downstream turbines in a wind farm. These models are important tools for the design and optimization of wind farm layouts, as they can help to estimate the reduction in energy production caused by wind wakes. This information can be used to make financial projections for a wind project, and to assess the project's potential profitability.
In the United States, wind energy is a rapidly growing industry, and accurate wake models are becoming increasingly important for the successful development and operation of wind farms. There are several types of wake models, including actuator disk models, vortex models, and Reynolds-averaged Navier-Stokes (RANS) models. Actuator disk models are the simplest and most widely used wake models. They assume that a turbine acts as a disk that generates a downstream wake, while vortex models represent the wake as a series of vortices. RANS models are the most complex and computationally intensive, but they can provide the most accurate predictions of wake behavior.
The National Renewable Energy Laboratory (NREL) is among the many instations or corporations that has developed a number of wake models, including the Wind Farm Performance Model (WFPM) and the Wake Steering and Optimization Model (WakeSOM). Wind farm models can be used to simulate the performance of a wind farm under various conditions and optimize its layout.
The use of wake models can also help to reduce the levelized cost of energy (LCOE) for wind projects. LCOE is a measure of the average cost of electricity over the lifetime of a project, and is an important metric for evaluating the economic viability of a wind project. The layout of wind farms can be optimized by using wake models, which will thus reduce the reduction in energy production caused by wind wakes and lower the LCOE.
Another important aspect of wind project financial projections is the estimation of the capacity factor of a wind farm. The capacity factor is the ratio of actual energy output to the theoretical maximum output. Accurate wake models can be used to forecast the capacity factor of a wind farm, which is crucial for financial projections. A 2016 study by the National Renewable Energy Laboratory (NREL) found that wake modeling can increase a wind farm's capacity factor—the measure of its ability to generate electricity at maximum production levels over time—by up to 14% and power output by 6%.
This result in cost savings for the project and increase in returns on investment.
In addition, wake models can be used to estimate the reduction in energy production caused by wind wakes, which can be used to estimate the revenue loss caused by wake losses. This information can be used to estimate the value of wake loss mitigation measures, such as active wake steering or turbine spacing optimization.
In the United States, wind energy is a rapidly growing industry, with over 100 GW of installed capacity and over 60,000 wind turbines. The US Department of Energy (DOE) has set a goal of generating 20% of the nation's electricity from wind energy by 2030. Accurate wake models are becoming increasingly important for the successful development and operation of wind farms in the United States, as they can help to optimize the layout of wind farms and increase the energy production and profitability of projects.
As a result, the wind-wake model is an important tool in financial projections and project results for U.S. wind farms. They are used to optimize the layout of wind farms, to estimate the reduction in energy production caused by wind wakes, to estimate the capacity factor of a wind farm, and to estimate the revenue loss caused by wake losses. Accurate wake models can help to reduce the LCOE of wind projects and improve the financial viability of wind projects.
List of Common Wind Energy Wake Models
1. Simple Wake Model uses a thrust coefficient to calculate the wind speed deficit at each turbine due to wake effects of the upwind turbines.
2. Park Equation The Park wake model is a widely-used analytical model for estimating the wake effects of wind turbines. It describes the velocity deficit in the wake of a turbine in terms of the downstream distance, the turbine's thrust coefficient, and the ambient wind velocity.
3. The Dynamic Wake Meandering (DWM) model is a wake model developed by Larsen which describes the meandering behavior of a wind turbine wake and its effect on the downstream turbine's power production. It's a complex model that considers the wake's meandering behavior, turbulence and the atmospheric stability.
4. The Eddy-viscosity model, developed by Ainslie, is a wake model that describes the velocity deficit in the wake of a wind turbine using the concept of eddy viscosity. It's a popular model that describes the wake flow based on the turbine's thrust coefficient, the ambient wind velocity, and the downstream distance.
5. Large-eddy simulation (LES) is a numerical method for simulating turbulent flows, including the wake of wind turbines. It's a complex method that requires specialized software and significant computational resources. It's different from the previous models mentioned, as it solves the Navier-Stokes equations directly to simulate the turbulent flow and its wake.
6. The Turbulence Optimized Park (TOP) model is a wake model developed by Orsted, which is an extension of the traditional Park wake model that accounts for the effect of turbulence on the wake's velocity deficit. The TOP model uses the thrust coefficient, the ambient wind velocity, the downstream distance and the turbulence intensity.
7. The Wind Farm Performance Model (WFPM) is a wake model developed by NREL, used to simulate the performance of wind farms. The model accounts for the wake effects between wind turbines and the interactions with the atmospheric boundary layer.
8. The Wake Steering and Optimization Model (WSOM) is a wake model developed by NREL used to simulate the wake effects of wind turbines and optimize the power output of a wind farm. It accounts for the wake effects between wind turbines and the interactions with the atmospheric boundary layer, it also takes into account the control of the yaw and tilt of the turbine blades in order to steer the wake and increase the power output.