A SYSTEMATIC METHOD FOR QUANTIFYING FLOW MODEL UNCERTAINTY IN WIND RESOURCE ASSESSMENT

1. A SYSTEMATIC METHOD FOR QUANTIFYING FLOW MODEL UNCERTAINTY IN WIND RESOURCE ASSESSMENT ALEX CLERC, PETER STUART AND MIKE ANDERSON 16 APRIL 2012

2. CONTENTS • Background and motivation • Dataset and derivation of method • Example calculation

3. ENERGY YIELD – MAJOR COMPONENTS Reference Long Term Wind Resource Wind Flow Model Wakes Loss Turbine Model Electrical Loss Adjustment Factors Net Net Yield

4. EXAMPLE ENERGY YIELD Taken from “EWEA Comparison of Resource and Energy Yield Assessment Procedures” presented during EWEA Wind Resource Assessment Technology Workshop, Brussels, 11 May 2011

5. Taken from “EWEA Comparison of Resource and Energy Yield Assessment Procedures” presented during EWEA Wind Resource Assessment Technology Workshop, Brussels, 11 May 2011

6. COMBINED STANDARD UNCERTAINTY Combined Standard Uncertainty Annual Energy Production (AEP) Uncertainty in AEP due to flow model Number of flow predictions in Energy Yield Sensitivity of AEP to flow predictions (wind speed) Standard uncertainty of flow predictions Correlation of flow prediction errors,

7. DATASET AND METHOD 557 mast pairs • Dataset: mast pairs from Europe and North America, wind speed ratios calculated by 30° sector • Speed-ups taken from a flow model very similar to WAsP • The observed speed-up errors are used to study: • uncertainty of a speed-up prediction for a particular wind direction (u) • correlation of errors (ρ)

8. EFFECT OF DISTANCE ON SPEED-UP ERROR λ = 10%, L1 = 1km Log scale

9. EFFECT OF SPEED-UP ON SPEED-UP ERROR A = 0.5, S is the speed-up

10. EFFECT OF DIRECTION ON CORRELATION

11. EFFECT OF DISTANCE ON CORRELATION DTT is distance between turbines DMM is distance between masts

12. SUMMARY • Uncertainty (u) depends on: • distance from mast to turbine • speed-up predicted by the model • Correlation of errors (ρ) depends on: • wind direction • distance from turbine to turbine • distance from mast to mast if applicable • Sensitivity (c) mainly depends on the shape of the wind distribution and power curve

13. EXAMPLE CALCULATION Taken from “EWEA Comparison of Resource and Energy Yield Assessment Procedures” presented during EWEA Wind Resource Assessment Technology Workshop, Brussels, 11 May 2011

14. EXAMPLE CALCULATION With one mast flow model uncertainty is 3.14% With two masts flow model uncertainty is 2.00% original mast 3.14% with one mast 2.00% with two masts optimal second mast Modified from “EWEA Comparison of Resource and Energy Yield Assessment Procedures” presented during EWEA Wind Resource Assessment Technology Workshop, Brussels, 11 May 2011

15. CONCLUSIONS • The presented flow model uncertainty method is systematic and evidence-based • Easy to use and applicable to linear models such as WAsP and MS3DJH • Many possible applications • Optimisation of mast deployment • Optimisation of mast weight scheme • Quantify benefits of masts in financial terms • Open-source software “DeltaWindFlow” available from RES website • http://www.res-group.com/resources/download-area.aspx