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Power Management of Wind Turbines

Power Management of Wind Turbines. presented by: Barry Rawn MASc Candidate University of Toronto. Wind Power Generation Symposium- February 20th, 2004 SF1105 1-5pm. Power Management of Wind Turbines. motivation modelling control potential. motivation. motivation.

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Power Management of Wind Turbines

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  1. Power Management of Wind Turbines presented by: Barry Rawn MASc Candidate University of Toronto Wind Power Generation Symposium- February 20th, 2004 SF1105 1-5pm

  2. Power Management of Wind Turbines motivation modelling control potential

  3. motivation

  4. motivation Improving the flexibility and power quality provided by wind generation can enable the spread of wind power.

  5. motivation what are the main differences between conventional generators and wind turbines?

  6. motivation I. The power available in the wind varies on several time-scales. This could impact: -power planning -power quality

  7. motivation II. Wind turbines are systems having nonlinear dynamics and oscillatory modes. This can affect considerations of grid stability where controlled wind turbines are present.

  8. motivation Modern turbines run at variable speeds and interface to the grid through power electronic converters. An exploration can be made of the extent to which a controlled turbine can act as a more stable-looking generator.

  9. modelling

  10. 0.8 0.4 λ modelling -blades The blades of a turbine transfer momentum from the wind like the wings of an aircraft. The character of the flow depends on an effective angle of attack

  11. UNSTABLE STABLE FAST SLOW power torque hub speed modelling -blades Aerodynamic stall has two important effects: -dictates an optimal power extraction -defines a division between two dynamical regimes

  12. modelling -spinning blades irregular wind field forces system both periodically and randomly disturbance at the blade passing frequency may occur due to: • tower shadow • wind shear • rotational sampling

  13. modelling -spinning blades blade passing frequency present in spectrum of blade forces, but not in spectrum of wind averaging force signals associated with rotor angle reveals periodic components less significant for variable speed systems

  14. modelling -mechanical modes flexible structure has many mechanical modes of oscillation these must be considered in structural designs

  15. modelling -mechanical modes for control and power system studies, capturing the two main inertias and their flexible coupling is sufficient

  16. modelling

  17. control

  18. several degrees of freedom available to control energy flow within the system • power in must balance power out control

  19. different strategies exist control

  20. Tony Turbine Greg Grid control

  21. Tony Turbine uses control freedom to: - optimize power extraction - minimize torsional oscillations control

  22. Greg Grid Left with responsibility to balance power Can partially influence how power is delivered to the grid control

  23. Tony Turbine feeds Greg Grid a power that's best for the wind turbine, and Greg accommodates. control

  24. control tasks are decoupled in some sense • influence on grid is a shared responsibility between both Tony Turbine and Greg Grid control

  25. let's consider a different division of tasks: one based on energy management control

  26. Cool Clara Fast Freida control

  27. Fast Freida maintains power balance and minimizes torsional oscillations using energy from the turbine control

  28. Cool Clara sets a smooth power extraction, and reacts to grid changes appropriately using full freedom control

  29. Cool Clara requests a power that is least harmful to the grid. Fast Freida conveys it and attempts to contain wind disturbances. control

  30. The success of such a control scheme places trust in two main assumptions. control

  31. Fast Freida has to trust that Cool Clara will always demand a power that is achievable. control

  32. Cool Clara has to trust that Fast Freida will manage the capacitor voltage within tolerances, and limit mechanical resonance control

  33. appropriate control design makes both assumptions valid control

  34. control

  35. control

  36. control

  37. potential

  38. Assuming such control could be practically realized, this methodology: • further reduces potentially troublesome influence of wind variation • frees the converter interface to make the system appear more robust over short time scales • allows the possibility of shifting between optimal and conservative power extraction, based on grid conditions potential

  39. Future investigation would further characterize the properties of such a controlled system. Examples include: • controls based on inference of hub energy could eliminate need for accurate wind speed measurement and reduce stall recovery incidents • some potential may exist for a kind of dispatchability of energy on short time scales between turbines in a wind farm potential

  40. Power Management of Wind Turbines presented by: Barry Rawn MASc Candidate University of Toronto thanks!

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