Eol

ica

Eol

ica

Exp

o 20

04E

xpo

2004

Rom

a, S

epte

mbe

r 30

R

oma,

Sep

tem

ber

30 ––

Oct

ober

2, 2

004

Oct

ober

2, 2

004

Analysis and control of Analysis and control of wind turbine generators wind turbine generators

Carlo L. Bottasso,Lorenzo Trainelli, Alessandro Croce,

Walter Sirchi, Barbara Savini

Dipartimento di Ingegneria AerospazialePolitecnico di Milano

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

SummarySummary

• Introduction and motivation:– Design requirements for modern wind turbine generators

(WTGs).

•• MultiMulti--Body DynamicsBody 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 controlactive control:– Design of adaptive model-predictive controllers;– Potential benefits (fatigue, efficiency, safety).

• Conclusions and future work

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Introduction and motivationIntroduction and motivation

The design of modern large WTGs poses new challenges in the areas of aeroelasticityaeroelasticity and controlcontrol:• Long span bladesblades, tall flexible towerstowers, individual blade pitch controlpitch control;• Increase efficiencyefficiency, reduce fatiguefatigue, ensure safetysafety.

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Introduction and motivationIntroduction and motivationNonNon--conventionalconventional geometry/topology:

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Finite element based multibody Finite element based multibody dynamicsdynamics

A modern approachmodern approach to the modeling of wind turbines:

• WTG is viewed as a complex flexible mechanismcomplex flexible mechanism.

• Model novel configurations of arbitrary topology by assembling basic componentsassembling basic components chosen from an extensive library of elementslibrary of elements.

This approach is that of the finite element methodfinite element method which has enjoyed, for this very reason, an explosive growth.

This analysis concept leads to simulation software tools that are modularmodular and expandableexpandable.

Simulation tools are applicable to configurations with arbitrary arbitrary topologiestopologies, including those not yet foreseennot yet foreseen.

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Finite element based multibody Finite element based multibody dynamicsdynamics

Definition of multibodymultibody: a finite element modelfinite element model, where the elements idealize rigid and deformable bodies (beams, shells, etc.) and mechanical constraints.

Systems with complexcomplex topologies, where each body undergoes large displacements and finite rotationslarge displacements and finite rotations (but only small strains).

Idealization process:

Virtual prototype.

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Finite element based multibody Finite element based multibody dynamicsdynamics

Lower pairsLower pairs:

Body modelsBody models: geometrically exact, composite ready beams and shells; rigid bodies.

• Sensors;

• Actuators, controls.

Other modelsOther models:

• Flexible joints;

• Unilateral contacts;Solution proceduresSolution procedures: stationary/periodic, transient (start-up, shut-down, etc.), stability analysis.

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Finite element based multibody Finite element based multibody dynamicsdynamics

• Multiulti--disciplinary/multidisciplinary/multi--field field integrationintegration;;• Hierarchical modeling:

– Global behavior with environmental interactions;– Zoom at the sub-system level (contact/impact, loads, fatigue,

sensors, etc.).

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Wind turbine generator dynamicsWind turbine generator dynamicsOffOff--design design aeroelasticaeroelastic analysis of a 1.2 MW class generator: asymmetrical blade pitch asymmetrical blade pitch commandcommand during start-up maneuver.

Blade-1 root loads time historytime history.

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Wind turbine generator dynamicsWind turbine generator dynamicsOffOff--design design aeroelasticaeroelasticanalysis of a 1.2 MW class generator.

Pitch actuator Pitch actuator failure failure during an emergency stop maneuver after grid lossgrid loss.

(top: tower tip displacements; bottom: blade root internal forces)

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Our background: rotary wing applicationsOur background: rotary wing applicationsHelicopter on a rolling frigate flight deck: runrun--upup and runrun--downdown in a gust with multiple impacts at the droopdroop and flapflap stops.

Similar Similar aeroelasticaeroelastic issuesissues with respect to a wind turbine generatorwind turbine generatorduring start-up and shut-down maneuvers.

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Our background: rotary wing applicationsOur background: rotary wing applications

WhirlWhirl--flutterflutter aeroelasticinstability of a tilt-rotor:

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Advanced control of Advanced control of WTGsWTGsNon-linear model-predictive control (NMPC): predictpredict dynamic

behavior of the system and find the controls that minimize a suitable objective functionobjective function while satisfying possible constraintsconstraintsand bounds.bounds.

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Advanced control of Advanced control of WTGsWTGs

HighligthsHighligths of NMPC for of NMPC for WTGsWTGs::• 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.;

•• SystematicSystematic design of “smart” controllers aware of system nonnon--linearitieslinearities.

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

NMPC vs. conventional PINMPC vs. conventional PI

• ReducedReduced rotor angular velocity fluctuations;

•• SmootherSmoother behavior, higher higher output poweroutput power

• Substantially enhancedfatigue lifefatigue life: rainflow fore-aft (right, top) and side-side (right, bottom) equivalent bending moments for Category A turbulence.

Pol

itec

nico

di M

ilano

Pol

itec

nico

di M

ilano

Eolica Expo 2004 Roma, September 30 – October 2 , 2004

Conclusions and future workConclusions 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.