BEGIN:VCALENDAR VERSION:2.0 METHOD:REQUEST PRODID:-//ddaysoftware//NONSGML DDay.iCal 1.0//EN BEGIN:VTIMEZONE TZID:Eastern Standard Time BEGIN:STANDARD DTSTART:20071102T020000 RRULE:FREQ=YEARLY;BYDAY=1SU;BYHOUR=2;BYMINUTE=0;BYMONTH=11 TZNAME:Eastern Standard Time TZOFFSETFROM:-0400 TZOFFSETTO:-0500 END:STANDARD BEGIN:DAYLIGHT DTSTART:20070301T020000 RRULE:FREQ=YEARLY;BYDAY=2SU;BYHOUR=2;BYMINUTE=0;BYMONTH=3 TZNAME:Eastern Daylight Time TZOFFSETFROM:-0500 TZOFFSETTO:-0400 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT DESCRIPTION:Jason Jonkman\, Senior Engineer\, NREL\n\nABSRACTFAST.Farm is a new mid-fidelity\, multi-physics engineering tool for modeling the power performance and structural loads of wind turbines within a wind farm\, inc luding wake and array effects. FAST.Farm is based on the principles of the Dynamic Wake Meandering (DWM) model\, but addresses many of the limitatio ns of previous DWM implementations. Previous calibration of the tunable mo del parameters of FAST.Farm has shown that its prediction of wake dynamics for a single wind turbine across different atmospheric stability conditio ns and nacelle-yaw errors matches well with high-fidelity large-eddy simul ation\, at a small fraction of the computational expense.This talk present s a validation of FAST.Farm against large-eddy simulation for a series of cases—independent from those used to support the calibration—considering s ingle turbine and small wind farm scenarios\, both subject to variations i n inflow and control.The validation has demonstrated that FAST.Farm accura tely predicts (1) thrust and power for individual turbines both in isolati on and down the row of the small wind farm\, (2) wake meandering behavior across different atmospheric conditions and (3) averaged wake-deficit adve ction\, evolution and merging effects. The validation also highlights pote ntial physics that could be improved in FAST.Farm in the future.\n\nBIOGRA PHYDr. Jason Jonkman is a Senior Engineer at NREL\, which he joined in 200 0\, and leads the wind turbine engineering tool development activities\, i ncluding the FAST software for modeling the dynamic response of land-based and offshore wind turbines. He also guides projects aimed at verifying\, validating\, and applying engineering tools to wind turbine design and ana lysis. Jason currently co-chairs an IEA Wind research task on developing\, verifying\, and validating simulation models for offshore wind turbines. He is the principal investigator for a DOE-funded project to improve the m odeling of offshore floating wind system dynamics. He also is a U.S. repre sentative on the IEC working group to develop an international technical s pecification for the design of floating offshore wind turbines. He holds a Ph.D. in Aerospace Engineering Sciences and an M.S in Mechanical Engineer ing from the University of Colorado\, and a B.S.E. in Mechanical Engineeri ng from Dordt College in Sioux Center\, Iowa\, United States.\n\n DTEND;TZID=Eastern Standard Time:20180920T113000 DTSTAMP:20181004T153205Z DTSTART;TZID=Eastern Standard Time:20180920T103000 LAST-MODIFIED:20181004T153205Z LOCATION:E6-4022 ORGANIZER;CN=Jessica Strickler via Waterloo Institute for Sustainable Energ y:MAILTO:b8504051-15bc-45ae-b0d0-3274854baec0.21@ca.igloosoftware.com SEQUENCE:4 SUMMARY:WISE Public Lecture - The New FAST.Farm: Wind Farm Design & Analysi s UID:b8504051-15bc-45ae-b0d0-3274854baec0 X-ALT-DESC;FMTTYPE=text/html;FMTTYPE=text/html:Jason Jonkman\, Senior Engin eer\, NREL\n\n
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ABSRACT
FAST.Farm is a new mid-fidelity\, multi-physics enginee
ring tool for modeling the power performance and structural loads of wind
turbines within a wind farm\, including wake and array effects. FAST.Farm
is based on the principles of the Dynamic Wake Meandering (DWM) model\, bu
t addresses many of the limitations of previous DWM implementations. Previ
ous calibration of the tunable model parameters of FAST.Farm has shown tha
t its prediction of wake dynamics for a single wind turbine across differe
nt atmospheric stability conditions and nacelle-yaw errors matches well wi
th high-fidelity large-eddy simulation\, at a small fraction of the comput
ational expense.
This talk presents a validation of FAST.Farm aga
inst large-eddy simulation for a series of cases—independent from those us
ed to support the calibration—considering single turbine and small wind fa
rm scenarios\, both subject to variations in inflow and control.
The validation has demonstrated that FAST.Farm accurately predicts (1) thr
ust and power for individual turbines both in isolation and down the row o
f the small wind farm\, (2) wake meandering behavior across different atmo
spheric conditions and (3) averaged wake-deficit advection\, evolution and
merging effects. The validation also highlights potential physics that co
uld be improved in FAST.Farm in the future.
BIOGRAPHY
Dr. Jason Jonkman is a Senior Engineer at NREL\, which he joined in 2000\, an d leads the wind turbine engineering tool development activities\, includi ng the FAST software for modeling the dynamic response of land-based and o ffshore wind turbines. He also guides projects aimed at verifying\, valida ting\, and applying engineering tools to wind turbine design and analysis. Jason currently co-chairs an IEA Wind research task on developing\, verif ying\, and validating simulation models for offshore wind turbines. He is the principal investigator for a DOE-funded project to improve the modelin g of offshore floating wind system dynamics. He also is a U.S. representat ive on the IEC working group to develop an international technical specifi cation for the design of floating offshore wind turbines. He holds a Ph.D. in Aerospace Engineering Sciences and an M.S in Mechanical Engineering fr om the University of Colorado\, and a B.S.E. in Mechanical Engineering fro m Dordt College in Sioux Center\, Iowa\, United States.