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Rotor Design Approaches

Rotor Design Approaches. Michael S. Selig Associate Professor . Department of Aeronautical and Astronautical Engineering University of Illinois at Urbana-Champaign. Steady-State Aerodynamics Codes for HAWTs Selig, Tangler, and Giguère August 2, 1999  NREL NWTC, Golden, CO.

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Rotor Design Approaches

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  1. Rotor Design Approaches Michael S. Selig Associate Professor Department of Aeronautical and Astronautical Engineering University of Illinois at Urbana-Champaign Steady-State Aerodynamics Codes for HAWTs Selig, Tangler, and Giguère August 2, 1999  NREL NWTC, Golden, CO

  2. Outline • Design Problems • Approaches to Design • Inverse Design

  3. Design Problems • Retrofit Blades • Trade Studies and Optimization

  4. Approaches to Design • Design by Analysis - Working “Forward” • Example HAWT Codes: PROP, PROP93, WT_PERF, PROPID

  5. Inverse Design - Working “Backward” • Requires some knowledge of desirable aerodynamic characteristics • Example HAWT Code: PROPID

  6. Optimization • Example problem statement: Maximize the annual energy production subject to various constraints given a set of design variables for iteration • Example Code: PROPGA

  7. Design Variables  Desire a method that allows for the specification of both independent and dependent variables

  8. From an Inverse Design Perspective • Through an inverse design approach (e.g., PROPID), blade performance characteristics can be prescribed so long as associated input variables are given up for iteration. • Examples: • Iterate on: To achieve prescribed: Rotor radius  Rotor peak power Twist distribution  Lift coefficient distribution Chord distribution  Axial inflow distribution

  9. Caveats • Some knowledge of the interdependence between the variables is required, e.g. the connection between the twist distribution and lift coefficient distribution. • Not all inverse specifications are physically realizable. For example, a specified peak power of 1 MW is not consistent with a rotor having a 3-ft radius.

  10. Iteration Scheme • Multidimensional Newton iteration is used to achieve the prescribed rotor performance • Special "Tricks" • Step limits can be set to avoid divergence • Iteration can be performed in stages • Parameterization of the input allows for better convergence

  11. PROPID for Analysis • Traditional Independent Variables (Input) • Number of Blades • Radius • Hub Cutout • Chord Distribution • Twist Distribution • Blade Pitch • Rotor Rotation Speed (rpm) or Tip-Speed Ratio • Wind Speed • Airfoils

  12. Traditional Dependent Variables - Sample (Output) • Power Curve • Power Coefficient Cp Curve • Rated Power • Maximum Power Coefficient • Maximum Torque • Lift Coefficient Distribution • Axial Inflow Distribution • Blade L/D Distribution • Annual Energy Production • Etc • Each of these dependent variables can also be prescribed using the inverse capabilities of PROPID

  13. Aerodynamic Design Considerations • Clean vs. Rough Blade Performance • Stall Regulated vs. Variable Speed • Fixed Pitch vs. Variable Pitch • Site Conditions, e.g. Avg. Wind Speed and Turbulence • Generator Characteristics, e.g., Small Turbines, Two Speed

  14. Common Design Drivers • Generator  Peak Power • Gearbox  Max Torque • Noise  Tip Speed • Structures  Airfoil Thickness • Materials  Geometric Constraints • Cost

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