Evaluation of global wind power Cristina L. Archer Stanford University 5 October 2005 San Jose State University.

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Presentation transcript:

Evaluation of global wind power Cristina L. Archer Stanford University 5 October 2005 San Jose State University

Outline Introduction on wind energy Least Square (LS) Methodology Global wind maps at 80 m Validation Statistics Calculation of global wind power potential Benefits of networking

Introduction Wind turbines are: reliable non invasive Wind energy is: clean inexpensive abundant scalable increasingly popular More info: Archer and Jacobson (2003)

Some Examples of Wind Turbines 32 m rotor blade of a 1.5 MW turbine (~54 m) Vindeby (DK) Copenhagen (DK)

Problems with wind power Intermittency Unreliability Noise Aesthetics Animals and birds Solutions: Siting Networking  frequency of low wind speeds  standard deviation of wind speed

Least Squares (LS) methodology Power law:Log law: Friction coefficient (1/7) Roughness length (0.01 m)

Least Squares (LS) methodology Power law:Log law:

LS methodology: examples

Mean 80m Wind Speed at Sounding Locations

Mean 80m Wind Speed in North America

Mean 80m Wind Speed in Europe

Validation: KSC towers

Four-level towers

Statistics: Global Frequencies ClassN. of stations Percent Total Total ≥

Statistics: Global Mean 80m Speeds Station TypeMean V80Mean V80 for Class ≥3 (m/s) Surface over land Buoys Soundings All

Calculation of Global Wind Power P global = 72 TW =53,898 Mtoe P global = f x A land x  x P turb 12.7%1.3x10 8 km 2 6 km x /77 2 P turb = P rated x CF = P rated x (0.087V-P rated /D 2 )

Calculation of Global Wind Power

Problems with wind power Intermittency Unreliability Noise Aesthetics Animals and birds Solutions: Siting Networking  frequency of low wind speeds  standard deviation of wind speed

Methodology for hourly 80m- trends

Methodology for hourly 80m- patterns

The shear function (  )

The shear function (  ) at KSC

Networking – The arrays

Networking – Frequency Distributions

Networking - Statistics

Conclusions 1)~13% of world’s stations are in class ≥3 2)Mean wind speed is steady and reliable at “windy” locations 3)Data from KSC support LS methodology 4) Networking several wind farms virtually eliminates intermittency and reduces backups 5) Global wind power potential is 72 TW 6) More results at: