Solutions

Empirical Wind-to-Energy Conversion Algorithm

Empirical Wind-to-Energy Conversion Algorithm

Fig. 1 Diagram of the WRF domains used in the wind energy prediction system. The grid spacings are as follows: D1=30km, D2=10km, and D3=3.3km.
Fig. 1 Diagram of the WRF domains used in the wind energy prediction system. The grid spacings are as follows: D1=30km, D2=10km, and D3=3.3km.

In late December 2008, RAL began a collaborative project with Xcel Energy Services, Inc. to perform research and develop technologies to improve Xcel Energy's ability to increase the amount of wind energy in their energy generation portfolio. The agreement and scope of work was designed to provide highly detailed, localized wind energy forecasts to enable Xcel Energy to more efficiently integrate electricity generated from wind into the power grid. The wind prediction technologies will help operators make critical decisions about powering down traditional coal–and natural gas–powered plants when sufficient winds are predicted, enabling the increased reliance on alternative energy while still meeting the needs of its customers. The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) is also collaborating by developing algorithms to calculate the amount of energy that the turbines generate by winds blowing at various speeds for a broad spectrum of wind facilities. The wind prediction technologies have been designed to cover Xcel Energy wind farms in Colorado, Minnesota, New Mexico, Texas, and Wyoming. It is anticipated that wind energy forecasting companies in the United States and overseas may adopt the developed technologies to help utilities that need more accurate wind predictions to transition away from fossil fuels.

To generate wind energy forecasts, NCAR is incorporating observations of current atmospheric conditions from a variety of sources, including satellites, aircraft, weather radars, ground–based weather stations, and even sensors on the wind turbines. The information is utilized by three powerful NCAR–based tools:

  • The Weather Research and Forecasting (WRF) computer model, which generates finely detailed simulations of future atmospheric conditions
  • The Real–Time Four–Dimensional Data Assimilation System (RTFDDA), which continuously updates the simulations with the most recent observations
  • The Dynamic Integrated Forecast System (DICast®), which statistically optimizes the output based on recent performance

Wind predictions are made for each wind turbine and a sophisticated post–processing algorithm converts the hub–height wind predictions into energy predictions. The energy generation values for each turbine, wind facility and connection node are provided to Xcel Energy.

Fig. 2 Conceptual diagram of the wind energy prediction technology components that will be incorporated into the final configuration.
Fig. 2 Conceptual diagram of the wind energy prediction technology components that will be incorporated into the final configuration.

In the first six months of the agreement, NCAR successfully developed the initial capabilities and began providing wind energy predictions. By late September 2009, all (40+) wind facilities were included. Real–time information from Xcel Energy's largest wind facilities is utilized by the wind energy system to refine the power curve calculations and tune the forecasts.

The Real–Time Four Dimensional Data Assimilation (RTFDDA) and forecasting system, that has been developed by RAL to satisfy the meteorological needs of Army test ranges, has been adapted for wind–energy prediction. RAL implemented an operational RTFDDA system over the western and central states for supporting wind–power forecasting. This system contains three modeling domains with grid sizes of 30, 10 and 3.3 km (Fig. 1). The 3.3 km domain covers the Rocky Mountains from New Mexico to Montana, the High Plains states, and most areas of the Central Plains. The system runs with a 3–hour cycle. In each cycle, it produces 27–hour forecasts for the innermost domain and 72–hour forecasts for the two coarser domains. The inner domain (3.3 km) generates output at 15–minute time steps.

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