Analysis and control of wind turbine generators

Transcription

1 Analysis and control of wind turbine generators Eolica Expo 2004 Roma,, September 30 October 2, 2004 Carlo L. Bottasso, Lorenzo Trainelli, Alessandro Croce, Walter Sirchi, Barbara Savini Dipartimento di Ingegneria Aerospaziale

2 Summary Introduction and motivation: Design requirements for modern wind turbine generators (WTGs). Multi-Body Dynamics (MBD): Key facts, basic features and potential applicability to WTG modeling and simulation; Examples of WTG modeling; Our background: rotary-wing applications. WTG active control: Design of adaptive model-predictive controllers; Potential benefits (fatigue, efficiency, safety). Conclusions and future work

3 Introduction and motivation The design of modern large WTGs poses new challenges in the areas of aeroelasticity and control: Long span blades, tall flexible towers, individual blade pitch control; Increase efficiency, reduce fatigue, ensure safety.

4 Introduction and motivation Non-conventional geometry/topology:

5 Finite element based multibody dynamics A modern approach to the modeling of wind turbines: WTG is viewed as a complex flexible mechanism. Model novel configurations of arbitrary topology by assembling basic components chosen from an extensive library of elements. This approach is that of the finite element method which has enjoyed, for this very reason, an explosive growth. This analysis concept leads to simulation software tools that are modular and expandable. Simulation tools are applicable to configurations with arbitrary topologies, including those not yet foreseen.

6 Finite element based multibody dynamics Definition of multibody: a finite element model, where the elements idealize rigid and deformable bodies (beams, shells, etc.) and mechanical constraints. Systems with complex topologies, where each body undergoes large displacements and finite rotations (but only small strains). Idealization process: Virtual prototype.

7 Finite element based multibody dynamics Body models: geometrically exact, composite ready beams and shells; rigid bodies. Lower pairs: Other models: Flexible joints; Unilateral contacts; Sensors; Actuators, controls. Solution procedures Solution procedures: stationary/periodic, transient (start-up, shut-down, etc.), stability analysis.

8 Finite element based multibody dynamics Multi-disciplinary/ disciplinary/multi-field integration; Hierarchical modeling: Global behavior with environmental interactions; Zoom at the sub-system level (contact/impact, loads, fatigue, sensors, etc.).

9 Wind turbine generator dynamics Off-design aeroelastic analysis of a 1.2 MW class generator: asymmetrical blade pitch command during start-up maneuver. Blade-1 root loads time history.

10 Wind turbine generator dynamics Off-design aeroelastic analysis of a 1.2 MW class generator. Pitch actuator failure during an emergency stop maneuver after grid loss. (top: tower tip displacements; bottom: blade root internal forces)

11 Our background: rotary wing applications Helicopter on a rolling frigate flight deck: run-up up and run-down in a gust with multiple impacts at the droop and flap stops. Similar aeroelastic issues with respect to a wind turbine generator during start-up and shut-down maneuvers.

12 Our background: rotary wing applications Whirl-flutter aeroelastic instability of a tilt-rotor:

13 Advanced control of WTGs Non-linear model-predictive control (NMPC): predict dynamic behavior of the system and find the controls that minimize a suitable objective function while satisfying possible constraints and bounds.

14 Advanced control of WTGs Highligths of NMPC for WTGs: Superior performance with respect to conventional controllers; Adaptive neural-network based NMPC: no tuning or adjustments necessary, the controller automatically recognizes environmental changes, local morphological characteristics of the terrain, etc.; Systematic design of smart controllers aware of system non-linearities linearities.

15 NMPC vs. conventional PI Substantially enhanced fatigue life: rainflow fore-aft (right, top) and side-side (right, bottom) equivalent bending moments for Category A turbulence. Reduced rotor angular velocity fluctuations; Smoother behavior, higher output power

16 Conclusions and future work Multibody based WTG modeling allows for: Maximum modeling generality/modularity Multidisciplinary integration for detailed studies, sensitivity analysis, modeling of complex interaction phenomena, controller optimization, etc.; Extensive experience gained on rotary wing problems, can be transferred to WTG applications. NMP control of WTGs: Potential for substantial gains in fatigue life; Neural adaption promises optimal behavior and self-tuning to changing environmental conditions; Need for testing and validation on the field.