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contributor authorWilczak, James
contributor authorFinley, Cathy
contributor authorFreedman, Jeff
contributor authorCline, Joel
contributor authorBianco, Laura
contributor authorOlson, Joseph
contributor authorDjalalova, Irina
contributor authorSheridan, Lindsay
contributor authorAhlstrom, Mark
contributor authorManobianco, John
contributor authorZack, John
contributor authorCarley, Jacob R.
contributor authorBenjamin, Stan
contributor authorCoulter, Richard
contributor authorBerg, Larry K.
contributor authorMirocha, Jeffrey
contributor authorClawson, Kirk
contributor authorNatenberg, Edward
contributor authorMarquis, Melinda
date accessioned2017-06-09T16:45:29Z
date available2017-06-09T16:45:29Z
date copyright2015/10/01
date issued2014
identifier issn0003-0007
identifier otherams-73567.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4215695
description abstracthe Wind Forecast Improvement Project (WFIP) is a public?private research program, the goal of which is to improve the accuracy of short-term (0?6 h) wind power forecasts for the wind energy industry. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that included the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models and, second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the United States (the upper Great Plains and Texas) and included 12 wind profiling radars, 12 sodars, several lidars and surface flux stations, 184 instrumented tall towers, and over 400 nacelle anemometers. Results demonstrate that a substantial reduction (12%?5% for forecast hours 1?12) in power RMSE was achieved from the combination of improved numerical weather prediction models and assimilation of new observations, equivalent to the previous decade?s worth of improvements found for low-level winds in NOAA/National Weather Service (NWS) operational weather forecast models. Data-denial experiments run over select periods of time demonstrate that up to a 6% improvement came from the new observations. Ensemble forecasts developed by the private sector partners also produced significant improvements in power production and ramp prediction. Based on the success of WFIP, DOE is planning follow-on field programs.
publisherAmerican Meteorological Society
titleThe Wind Forecast Improvement Project (WFIP): A Public–Private Partnership Addressing Wind Energy Forecast Needs
typeJournal Paper
journal volume96
journal issue10
journal titleBulletin of the American Meteorological Society
identifier doi10.1175/BAMS-D-14-00107.1
journal fristpage1699
journal lastpage1718
treeBulletin of the American Meteorological Society:;2014:;volume( 096 ):;issue: 010
contenttypeFulltext


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