Application of Global Weather and Climate Model Output to the Design and Operatio of Wind-Energy Systems

Award Information
Agency:
Department of Energy
Branch
n/a
Amount:
$150,000.00
Award Year:
2012
Program:
STTR
Phase:
Phase I
Contract:
DE-FG02-12ER86505
Award Id:
n/a
Agency Tracking Number:
98740
Solicitation Year:
2012
Solicitation Topic Code:
07 b
Solicitation Number:
DE-FOA-0000577
Small Business Information
845 Spring ST. NW #129, Atlanta, GA, 30308-1043
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
Y
Duns:
625305268
Principal Investigator:
Judith Curry
Dr.
(404) 803-2012
curryja@eas.gatech.edu
Business Contact:
Judith Curry
Dr.
(404) 803-2012
curryja@eas.gatech.edu
Research Institution:
Georgia Institute of Technology

311 Ferst Drive
Atlanta, GA, 30332-0340
() -
Nonprofit college or university
Abstract
Goals of 80% clean energy production for the United States by 2035 and 20% of the countrys power being supplied by wind energy by 2030 imply nearly a tenfold increase in wind power production. This means that the need for forecast information will extend to longer projection windows with increasing penetration of wind power into the grid and also with diminishing reserve margins to meet peak loads during significant weather events. In addition to more complex issues regarding maintenance planning, energy trading of oil and gas will be influenced increasingly by anticipation of wind generation on timescales of weeks to months, and on longer time scales, future scenarios on decadal time scales are needed to support assessment of wind farm siting, government planning, and the regulatory environment. CFAN will expand upon its hybrid statistical/dynamical forecasting scheme that delivers probabilistic wind forecasts on time scales from one day to seven months to deliver ensemble-based forecasts and extended range outlooks that corrects not only for model bias error, but improves the shape of the distribution to capture low wind and high wind events that are critical forecast targets for wind farms. Collectively, the Phase I evaluation and testing of forecasts on different time scales utilizing our techniques will provide an assessment of the ability to overcome the existing challenges with wind power forecasts on time scales of days to months, as well as provide a framework to improve placement of future wind farm locations. The resulting efforts of a full Phase II project will deliver a wind energy decision support tool solution that would address three key market needs: the ability to forecast reliably at ranges beyond two weeks and at high spatial resolution; better capacity planning forecasts related to extreme or ramp events on scales of days to weeks; effective planning forecasts at decadal time scales that translate accurately for localized sites. The short-term market potential of a resulting Phase II solution is estimated to be in excess of $5M.

* information listed above is at the time of submission.

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