92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Wednesday, 25 January 2012
The Wind Forecasting Improvement Project (WFIP): Description, Goals, and Preliminary Results From the Southern Study Area
Hall E (New Orleans Convention Center )
Jeffrey M. Freedman, AWS Truepower LLC, Albany, NY; and D. E. Hanley, J. W. Zack, J. Manobianco, C. D'Annunzio, J. M. Wilczak, J. L. Schroeder, B. C. Ancell, K. A. Brewster, S. Basu, V. Banunarayanan, and K. Orwig

The Wind Forecasting Improvement Project (WFIP) is a two-year Department of Energy (DOE)/National Oceanographic and Atmospheric Administration (NOAA) sponsored study whose main purpose is to demonstrate the value of additional atmospheric observations and model enhancements on wind energy production forecasts. WFIP geographically covers two regions of the U.S.: 1) the upper Great Plains, or Northern Study Area, and 2) most of Texas--the Southern Study Area. The Southern campaign is being led by AWST, and includes a team of private, government, and academic partners with collective experience and expertise in all facets required to ensure a successful completion of the project.

The project will take a comprehensive approach to meet the DOE's goal of improving 0- to 6-hour wind forecasts by demonstrating the “value of additional atmospheric observations and model enhancements on wind forecasts at turbine height.” A key component in meeting this objective is to determine what kind of additional measurements will be most effective in aiding model forecast improvement and where these instruments can be deployed most efficiently.Team members and their roles include:

The Electric Reliability Council of Texas (ERCOT), the balancing authority (BA) partner, is providing necessary data and support for the evaluation of systems operations benefits and will guide the team in determining the economic savings attributable to the improved short-term wind energy forecasts.

MESO, Inc. is performing the principal forecast modeling work, specifically a number of analyses and multi-model (ensemble) sensitivity studies.

Texas Tech University (TTU) is deploying, operating, and maintaining various measurement systems, including a 200-m instrumented tower and wind profiler, at its Reese Technology Center in Lubbock, TX. TTU will also contribute a subset of model runs as part of a hindcast sensitivity studies using an ensemble Kalman filter in a version of the Rapid Refresh/High Resolution Rapid Refresh (RR/HRRR) model.

North Carolina State University (NCSU) has deployed a sodar at the Reese Technology Center and will also be tuning and applying automated algorithms based on statistical learning theory for quality control of sodar and profiler data. The University of Oklahoma (OU) Center for Analysis and Prediction of Storms (CAPS) is running a version of the Advanced Regional Prediction System (ARPS) at 2-km horizontal resolution with enhanced vertical resolution to assimilate all available data including any measurements collected during the field campaign.

ICF International (ICF) is performing the majority of the economic analyses to assess benefits resulting from improved short-term wind energy forecasting.

THe National Renewable Energy Laboratory (NREL): is assisting ICF on part of the economic analysis as well as providing an independent technical review of the work.

The anticipated results of the project include:

A quantitative analysis of how additional atmospheric observations affect wind power production forecasts, and how this leads to improvements in forecasting the timing, magnitude, and persistence of wind ramp events.

Development of improved economic metrics to demonstrate cost savings for utilities and operators from improved short-term (0 – 6 hour) wind power forecasts.

A demonstration of how the improved economic and forecast performance metrics better reflect the manner in which operators and other wind forecast users are sensitive to wind power production forecast errors on electric power systems.

Results showing improved state-of-the-science short-term forecasting methods will be disseminated to interested stakeholders, and the study will be used to define the necessary spatial and temporal characteristics of a nation-wide mesonet observation system devoted to wind energy applications. More in-depth descriptions and preliminary results of this project will be presented here and in companion presentations by other team members.

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