Wednesday, 9 January 2013: 9:00 AM
Room 6A (Austin Convention Center)
, AWS TruePower LLC, Albany, NY; and P. Beaucage, J. W. Zack, J. Manobianco, I. Flores, J. L. Schroeder, B. C. Ancell
, K. Brewster
, K. Orwig, V. Banunarayanan, S. Basu, J. Wilczak, J. W. Cline, M. Marquis, and L. K. Berg
The Wind Forecasting Improvement Project (WFIP) is a multi-year Department of Energy (DOE)/National Oceanographic and Atmospheric Administration (NOAA) sponsored study whose main purpose is to demonstrate the scientific and economic benefits of additional atmospheric observations and model enhancements on wind energy production forecasts. WFIP covers two geographical 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 AWS Truepower LLC, 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. Here, we present results focusing on the climatology of phenomena-instigated ramp events--excursions in wind power production exceeding threshold values as determined by the Electric Reliability Council of Texas (ERCOT), the partner balancing authority. Ramp events instigated by meteorological phenomena and identified in this study include, but are not limited to, rapidly moving frontal systems, the development and decay of low level jets, and convectively driven outflow boundaries.
The field deployment and forecast modeling campaign began in August 2011 and ended in September 2012. Additional Southern Study Area measurement platforms included three 915 MHz wind profilers, seven sodars, the TTU 200-m instrumented tower, three surface flux stations, and three surface met observation stations, In addition, data from 34 existing tall towers at Wind Resource Generator sites were made available to the project in real-time for input into the forecasting models Two NRG/Leosphere Wind Cube LiDARs were deployed during August and September 2012 at a participating wind farm to determine the additional benefits to forecasting using on-site remote sensing measurements and to ascertain deep array wake effects.
In addition to the phenomena-based analysis mentioned above, a brief synopsis of how lessons learned from the WFIP Southern Study Area can be articulated and applied to other regions of the country will be described. Analysis of the improved forecast ensembles, including data withholding sensitivity studies will be presented in another paper by team partners, as will results from the economic analysis of how more accurate deterministic and probabilistic forecasts of wind energy production result in cost of energy savings.
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