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I Workshop Wind GlobalGeo e 3TIER - Matt

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  • 1. How to reduce riskPresented by:Matthew Hendrickson, Sr. Director Of Assessment
  • 2. 3TIER is Focused on Understanding the Fuel» Founded in 1999» Headquarters in Seattle, WA» Offices in Panama, India, and Australia» Focused on renewable energy information services  39,000 MW wind energy forecasting  7,400 MW hydropower forecasting  Extensive international wind & solar resource assessment
  • 3. Pre-construction servicesI. Spatial mappingII. Climate variability analysisIII. Comprehensive net report A. Spatial B. Climate C. Wake D. Other losses E. Uncertainty
  • 4. What is Numerical Weather Prediction? INPUTS WRF ANALYSIS OUTPUTS Global Weather Archive1960-present Understanding of wind characteristics High Resolution Long-term variability Terrain, Soil, assessmentsand Vegetation Data (up to 50 years) Spatial wind maps OPTIONAL: Onsite Observations
  • 5. The Value of Higher Resolution Wind Mapping 5km resolution 1.5km resolution 500m resolution8.0 Look at the two locations marked on each map… Sweetwater Nearby Mountain At 5km resolution = ~7.1m/s ~7.5m/s At 1.5km resolution = ~6.9m/s ~7.7m/s7.0 At 500m resolution = ~6.8m/s ~8.0m/s6.0
  • 6. The Value of High Resolution Wind Mapping 5km resolution 1.5km resolution 500m resolution8.0 . . . and understand the spatial variability of the wind7.0 90m resolution resource, better than with simple statistical ~9.0 m/s at mountain extrapolations and/or6.0 interpolations of on-site observations
  • 7. Avoid Wind Holes!
  • 8. Options for Understanding Long-term Variability
  • 9. Using Nearby 3rd Party Station Data Measure-Correlate-Predict (MCP)
  • 10. Traditional MCPMeasure-Correlate-Predict Reference ✪ Site ws=m*wsr+b Uses a statistical relationship between on-site obs data and a longer ‘reference’ site to understand the variability of the wind resource and determine a long-term adjustment
  • 11. Traditional MCPMeasure-Correlate-Predict » Reference site needs to be a consistent, long-term time series located within a similar flow regime as the project site » For robust results, MCP requires high correlation between reference site and on-site, project data » What to do if suitable long-term reference data are not available?
  • 12. Using Synthetic Reference Data Numerical Weather Prediction Models
  • 13. Synthetic Reference Data – Using NWP Models» Unlike MCP analysis, Numerical Weather Prediction (NWP) models do not require off-site reference data.» Over 50 years of historic wind resource data at hourly resolution can be generated utilizing NWP models» Synthetic reference data are provided at the project-site
  • 14. Numerical Weather Prediction Framework Input OutputGlobal Weather Understanding Archive of Wind1948-present Characteristics Numerical WeatherHigh Resolution Long-Term Prediction ModelTerrain, Soil, and VariabilityVegetation Data (NWP) Assessments On-Site Spatial Observations Wind Maps
  • 15. NWP Output – Annual-mean Variability NWP wind speed Observed wind speed Long-term mean Operational wind speed
  • 16. NWP Output – Monthly-mean VariabilityCapacity Factor Based on single year of observations, compared to 40 year analysis
  • 17. Validation of 3TIER NWP Time Series Comparison Against Reanalysis
  • 18. Skill of Reanalysis Data 287 QC’d Tall Towers Average R=0.53 Median R=0.55 STD R=0.19
  • 19. Skill of 3TIER Data 287 QC’d Tall Towers Average R=0.70 Median R=0.71 STD R=0.08
  • 20. Skill of 3TIER Data - Independent Validation Wind energy index comaprison Wind energy index comaprison 200 200 y = 0,9692x + 2,6531 180 180 R² = 0,8772 160 160 y = 0,5507x + 44,931 R² = 0,6706 140 140 120 120 3Tier 20m NCAR 100 100 80 80 60 60 40 40 20 20 0 0 0 20 40 60 80 100 120 140 160 180 200 0 20 40 60 80 100 120 140 160 180 200 ElZayt NW 24,5m ElZayt NW 24,5m "Our preliminary findings show that 3TIER wind data can significantly reduce long-term correction error compared to using NCAR/NCEP data, which is often the only option due to a lack of reliable long-term ground measurements. Per Nielsen - EMD Manager
  • 21. Incorporating On-site Observational Data with Numerical Weather Prediction Models Model Output Statistics (MOS)
  • 22. Incorporating Observational DataAt any particular location the best way todetermine the wind resource is through directmeasurement.3TIER incorporates observational data intowind assessments whenever suitable on-sitedata are available for • Validation • Statistical correction
  • 23. Incorporating Observational Data - MOS• MOS (Model Output Statistics) is a statistical technique to remove bias & adjust the variance of NWP model data to better match the on-site observed data• NWP models simulate the full structure and time evolution of the atmosphere. MOS relates the observed wind speed to the leading NWP predictors to improve the quality of the long-term estimate of the wind resource.• The output of the MOS algorithm is a multi-linear equation that is applied to all times of the analysis on an hourly basis (windspeed_97m * 1.25) + (windspeed_200m * 0.51) + (u_200m * 0.07) + (temperature_0m * -0.06) + 18.93
  • 24. MOS-Corrected Output – Monthly-mean Variability
  • 25. Validation of MOS-Corrected Time Series Influence of observational record length
  • 26. Skill at Monthly-mean Timescale Raw Model Data MOS-Corrected Model Data Analysis performed with Horizon Wind Energy utilizing 299 tall towers MOS-corrected standard deviation of error for an individual month = 7.8%
  • 27. Skill at Annual-mean Timescale Raw Model Data MOS-Corrected Model Data Analysis performed with Horizon Wind Energy utilizing 299 tall towers MOS-corrected standard deviation of error for an individual year = 3.4%
  • 28. MOS skill utilizing short observational records A single month of observational data helps to remove bias MOS-corrected errors decrease throughout first year of observed record
  • 29. MOS skill utilizing short observational records MOS-corrected errors decrease throughout first year of observed record
  • 30. Comparing Skill of3TIER MOS & MCP Results based on 23 met towers each with 5 years of obs data Obs data and MCP analysis provided by Horizon Wind Energy 3TIER MOS MCP
  • 31. Wake Modeling• 3TIER’s super computing capabilities allow unique ability to model wakes in time series across all climatic conditions.• Classical engineering solutions require climatic conditions to be condensed into distributions, disguising important features like performance in atmospheric stable conditions
  • 32. Other losses» Turbulence» Shear» Inflow angle» Electrical system» Availability» Turbine performance» Environmental» Blade degradation» Icing» Wind sector management» High speed start/stop hysteresis
  • 33. Comprehensive Assessment• 3TIER’s most complete solution, provides finance quality energy assessment• Project-wide, net energy assessment based on the last 40+ years of MOS-corrected NWP model data• Adds a site-visit, quality control of obs data, full uncertainty analysis, and gross-to-net analysis to a FullView Project Resource Assessment• Uses 3TIER’s proprietary time-varying wake modeling analysis to understand diurnal and seasonal variability of wakes, wind speed deficits, and turbulence intensity
  • 34. Comprehensive Assessment Full, time series simulation at every turbine across historic record
  • 35. Comprehensive AssessmentMulti-staged observation QC process
  • 36. Comprehensive Assessment
  • 37. Comprehensive Assessment Comprehensive uncertainty analysis highlights risk associated with measurements, shear, spatial modeling, temporal modeling, generation, wake modeling, etc…
  • 38. Other Services • Power Performance Testing – per IEC 61400- 12-1 standards • Operational reforecast services – reassess the long term production of a plant after operational data is available • Operational forensic services – root cause analysis to “deep dive” into SCADA data and attempt to explain variations on production against expectations. • Etc… 3TIER’s Advanced Applications group positioned to tackle any challenges in need of scientific solution.