9.2 Short-term Wind Energy Forecast Improvements resulting from the Wind Forecast Improvement Project (WFIP): Northern Study Area

Wednesday, 9 January 2013: 8:45 AM
Room 6A (Austin Convention Center)
Catherine A. Finley, WindLogics Inc., Grand Rapids, MN; and J. Wilczak and K. Orwig

Improving wind energy forecasts is an important component to integrating larger amounts of wind energy onto our electric grid system. Forecasting is also critical to almost all aspects of renewable energy operations, trading and financial planning. All wind energy forecasting activities in the U.S. rely in some way on weather forecast data provided by the NOAA forecast models. Thus to make significant strides in improving wind energy forecasts, it's critical to improve our fundamental weather forecasts.

The Wind Energy Forecast Improvement Project (WFIP) is a project funded by the Department of Energy in partnership with NOAA, private industry partners and DOE Labs. The goal of the project is to improve the accuracy of NOAA's short-term weather forecast models through additional data assimilation and increased model resolution, and then to evaluate the economic impact of the resulting improvements in wind energy forecasts on power grid systems operations. The Northern Study Area covers a large portion of the Midwest Independent System Operator (MISO) grid operations area in the northern plains. Team members in the Northern Study Area include: WindLogics, National Renewable Energy Laboratory (NREL), South Dakota State University, NextEra Energy Resources, and MISO.

We will present the results from the wind energy forecasting portion of the study which ran from late August 2011 to early September 2012. The analysis will include comparisons of error metrics between the operational short-term models and the ‘enhanced' short-term models in order to quantify wind energy forecast improvements. We will also present results from an analysis of large wind power forecast errors and wind ramp events which are of particular concern to power grid operators. The effects of geographic dispersion of the wind plants on the MISO system-wide wind power forecast accuracy will also be discussed.

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