offshore wind resources and forecastingweb.mit.edu/windenergy/windweek/presentations/p2 -...
TRANSCRIPT
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Headquarters: Albany, NY
• Mapping• Energy Assessment• Project Engineering• Performance Evaluation• Forecasting
Industry Leader & Consultant for 25 YearsFull spectrum of wind plant design, development
and evaluation servicesProject roles in over 60 countries
Offices in Austin, TX and Barcelona, Spain; 100 employees
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Topics
• Contrasting Land & Offshore Winds
• Extreme Winds
• Wind Measurement
• Wind Modeling
• Measurement Approaches for Wind Farms
• Wind Forecasting
• Future Needs & Trends
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WINDPOWER 2008 - Houston© 2007 AWS Truewind Confidential
Source: NREL
Dynamic External Environment
Wind and waves are the primary external conditions affecting the design and cost of offshore wind turbines
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Offshore Contrasts With Land
• Stronger Winds:– Very little surface roughness– No terrain– Fetch dependent
• Spatially consistent• Lower average wind shear (.08‐.16 typical)• Lower turbulence intensity (.05‐.10 typical)• Sea/lake breeze & stability issues
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Sea/Lake Breezes
• Sea Breezes Are 3‐Dimensional
• Favor Spring & Summer Seasons
• Offshore Extent Is Variable
• Wind Intensity is Variable
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Sea Breezes & Load MatchingAvg. Peak Day:1999-2003
Coastal NJ Utility Load & Plant Net Capacity Factor
Based on Ambrose Light Station Wind Data
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Role of Atmospheric Stability• Fall‐Winter
– Water warmer than air unstable atmosphere– Promotes vertical mixing and stronger surface winds
• Lake effect snow squalls
• Spring‐Summer– Water cooler than air stable atmosphere
• Lake/sea breezes– Suppresses mixing and winds
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Stability Effects on Wind ShearH
eigh
t
Wind Speed
Stable with low level jet
Unstable
Neutral
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Extreme Winds
Strong Fronts/ Thunderstorm Lines
Hurricanes(large waves too)
Slow Moving Intense Coastal Storms – Nor’easters(large waves too)
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Hurricane RisksSaffir‐Simpson Hurricane Scale
Category 1: 74‐95 mphCategory 2: 96‐110 mphCategory 3: 111‐130 mphCategory 4: 131‐155 mphCategory 5: 156+ mph
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Conventional Sources of Wind Data• Surface
• Buoys and Coastal Marine Automated Network Stations (C‐MAN) ‐ NDBC
• Coastal met. stations
• Ships (seasonal, moving)• Voluntary observing ships
• Commercial aircraft
• Remote Sensing• Weather balloons from
land
• Satellite (QSCAT, SAR)
C-MANNDBC
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Satellite ImageryWind friction over sea creates wavelets
of few cm-scale when wind speed is several m/s.
Radar signal is related to sea waves by Bragg resonant scattering
λs = n λr / (2*sinθ)
Speed Accuracy ~1.5-2.0 m/s
Source: P. Beaucage
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QuikSCAT Wind Climatology
Source: NASA/JPL
1999 - 2007
Winter
Summer
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Weaknesses of Conventional Data• Low elevation measurement (<10 m)
• Low number and density of stations– Some buoys removed in winter
• Ship data – limited value
• Balloon trajectory is wind dependent
• Satellite coastal resolution (QuikScat)
• Accuracy (typically 1‐2 m/s)
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Wind Modeling• Wind maps developed from 3‐D mesoscale numerical weather models (WRF, MM5, MASS)
• Combine boundary layer properties & atmospheric data to simulate all physics of the atmosphere
• Widely used for mapping & forecasting• Key Inputs:
– Global Reanalysis Data (NCEP/NCAR) ‐ synthesis of data sources– NCEP or MODIS/Pathfinder Sea Surface Temperatures– Sea Ice– National Elevation Data; Landsat Land Cover– Differential Vegetation Index
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Wind Resource Mapping
Validation Results
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Regional Wind Maps
• Funded by NREL & States
• 50 nautical miles from shore
• Annual, monthly, diurnal
• Six heights: 10, 30, 50, 90, 150, 300 m
• Power density, speed averages & distributions, wind roses
New England
Funded by NREL & Massachusetts Technology
Collaborative
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Texas/Louisiana
Funded by NREL, TX State Energy Conservation Office, LA Dept. of Natural Resources
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Great LakesFunded by NREL, Indiana Office of Energy & Defense
Development, Michigan Energy Office, NY State Energy Research & Development Authority, Ohio Dept. of
Development, Ontario Ministry of Natural Resources
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Desired Data for Siting & Design of Offshore Wind Plants
• Wind Speeds – annual, monthly, hourly, sub‐hourly (including hub ht)
• Speed Frequency Distribution
• Wind Shear
• Turbulence Intensity
• Wind Direction Rose
• Extreme Gusts & Return Periods
• Air Temp., RH, Pressure, Density, Solar
• Coincident Sea‐State Conditions– Including sea surface temp
0100200300400500600700800900
1000110012001300
0 2 4 6 8 10 12 14 16 18 20 22 24 26
Wind Speed (m/s)
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Assessment Approaches• Tall Met. Mast(s)
– Most credible & widely accepted– Multiple heights; rugged sensors
• Complemented by:– Lidar/sodar– Project weather buoys– Ocean data (temp., waves)
• Regional Weather Obs• Height & Climatological
Adjustment (MCP) • Mesoscale Modeling
Cleveland Crib
FINO-1 Mast – Germany
NaiKun Mast – B.C.
Cape Wind Mast
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Energy Production Projections• Application of Wind Statistics to Turbine Power Curves
• Assumptions for Loss Factors and Availability
• Wake Effects
• Hourly Production Statistics– Load matching and energy pricing
– Sub‐hourly variability & forecast‐ability
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Wind Forecasting
Minutes to Days in Advance
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How Forecasts Are Produced
Physics‐based models
Statistical models
Forecast ensembles
Diverse set of input data with widely
varying characteristics
Importance of specific models and data types vary with look‐ahead
period
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Desired Outcome
Hour of Month - August
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Modeling Turbine Wakes• Perturbations in marine flow
propagate long distances
• Turbine wakes take longer to decay than over land• Low TI and high stability
reduce wake decay
• Traditional wind farm models over predict energy output for large arrays
• Model adjustments & refinements in progress
South Sandwich Islands Cloud Wakes (NASA)
R. Barthelmie IU/UE
Horns Rev, Denmark
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Future Needs & Trends• Special Purpose Offshore Monitoring Masts
– Vertical wind structure and stability
– Coincident sea state conditions
• Use of Lidar (vertical and side scan) or Sodar– Including units mounted on special spar buoys
• Reliance on Remote Sensing & Models
• Improved Wind Farm Modeling Tools
• Collaboration w/Government Agencies & Research Initiatives
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Thank You!