With the current trends towards higher levels of electric power produced using wind resources, the uncertainties and fluctuations of wind power output are increasingly challenging power grid operations and especially the so-called generation dispatch operations. Generation dispatch refers to scheduling traditional power plant output based on predicted demand, but this becomes difficult when wind energy becomes a major source of electric power. This is due to the unpredictability of wind as a resource. To seamlessly integrate wind energy to the power grid, it is imperative to improve the modeling of wind power output at the scale of wind farms, from seconds up to a day ahead. The quantitative characterization of wind fluctuations from the atmosphere and those induced by turbine-turbine interactions is a central component towards accurately predicting wind power output. Even with such predictions available to grid operators, the benefits associated with enhanced power system operations have neither been fully understood nor exploited. This problem is a fundamental issue of sustainable energy infrastructure related to the integration of fluctuating wind power into the power grid. This research aims to develop fundamental knowledge and guidelines to close the gap between atmospheric flow and wind farm electric power output, and to integrate this linkage to efficiently and reliably operate power grids. The holistic approach has the potential to allow the electric power grid to embrace higher levels of wind energy penetration. It will ultimately aid in decreasing the cost of wind power and help it become an attractive and viable option for the nation's renewable energy portfolio. The project will also fund the educational development of both graduate and undergraduate students, and significant efforts will be made to disseminate the results to the general public, the wind energy engineering community, and to the K-12 education.
The research project aims to develop a holistic framework to close the gap between atmospheric turbulence and wind farm electric power output to increase the efficiency of power grid operations. To achieve this goal, an interdisciplinary team will synergize their analytical, experimental, and numerical expertise to address the foundational problems of improving wind power prediction and power grid operations. High-performance computing will be used to characterize and quantify the variations of the turbulence dynamics occurring over the diurnal cycle (i.e., 24 hour day/night cycle) and their ability to modulate power fluctuations at the wind-farm level. Furthermore, a generic approach to wind-farm power output parametrization will be developed to account for temporal power output variability over a range of time scales (from seconds to hours), along its variance and spectral structure. The state-of-the-art wind power predictions will be integrated to design advanced control and operational tools for power grids. The ultimate goal is to achieve higher levels of wind energy that can be integrated to the electric power systems, and to contribute towards a future sustainable energy infrastructure. The potentially transformative aspects of the research include the development of a general parametrization of wind farm power output, and robust and economic frequency control designs. The work will integrate the physical processes involved in wind energy systems, the power grid and the associated interface between the two, including i) uncertainties in wind power modeling associated with the atmospheric stability state and diurnal cycle; ii) short-term and hourly-ahead forecasting of electrical power output fluctuations at the wind farm scale; and iii) enhancing power grid operations using the wind output prediction. The facilities at UIUC and PSU as well as the diverse expertise of the PIs provide an ideal environment for conducting this research.
