Multiscale Modeling of Wind Turbine Wake Effects on Short-term Wind Power Forecasting and Wind Farm Layout Planning

点击翻译按钮获取中文摘要

Owing to growing concerns over global warming caused by increasing concentrations of greenhouse gases (e.g., carbon dioxide, methane) resulting from human activity and to rapidly growing demand in energy capacity, there is an urgent need to exploit new resources. In this respect, environmental concerns favour renewable and clean energy sources such as wind energy (extracted using wind turbines). Wind energy is expected to play a significantly increasing role in the generation of electrical power worldwide owing to the fact that it is the most developed and cost effective of the renewable energy sources. However, improving the current power production from wind farms (clusters of wind turbines) requires predictive tools, but unfortunately the current state-of-the-science does not allow tools based on proper physics or theory to be developed. This should not be surprising because the aerodynamics of a wind turbine is extremely complicated, and this complication is further amplified when a number of wind turbines are located close to each other in a wind farm (or, park). To address this deficiency, the objective of this proposal is to develop a high-resolution multiscale numerical modeling framework, in which effects arising from wind shear, from atmospheric turbulence and stratification, and from complex terrain will be included, and effects from wind turbine wakes will also be accounted for by using a new aeroelastic actuator line model. The outputs of the modeling system will be used for short-term (the next 48~72 hours) wind power forecasting for wind farms. In addition, the software system can also be used to maximize power production (or, energy capture) through an optimal wind farm layout design, including environmental impacts from various factors such as noise, shadow flicker and turbulence intensity, and reduce fatigue loading of components of wind turbines in a wind farm under realistic atmospheric conditions. It will be demonstrated how the foundational knowledge base compiled from results produced in the project can be utilized to improve the overall design of wind turbines and wind farms, which we anticipate will be of importance for the future development and utilization of wind energy. In addition, the increase in wind energy utilization impacts the use of other power generation assets (e.g., nuclear, hydro, natural gas) and to properly manage the portfolio of electricity generation assets will require more detailed, accurate and timely information and prediction of wind energy.