Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint

Research output: Contribution to conferencePaper

Abstract

The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S.Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh(HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.
Original languageAmerican English
Number of pages8
StatePublished - 2012
Event11th Annual International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants Conference - Lisbon, Portugal
Duration: 13 Nov 201215 Nov 2012

Conference

Conference11th Annual International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants Conference
CityLisbon, Portugal
Period13/11/1215/11/12

NREL Publication Number

  • NREL/CP-5500-56258

Keywords

  • economic value
  • forecasts
  • grid operations
  • measurements
  • National Renewable Energy Laboratory (NREL)
  • NREL
  • numerical weather prediction
  • wind variability

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