SAICA Presentation

7/27/2019 SAICA Presentation

1/44


2/44

Introduction

Increasing attention to wind power electricity generation

dependence of global economies on fossil fuels concern about the environment


3/44

Introduction



Prevailing goal of WT with rudimentary control systems

minimization of the cost

minimization of the maintenance

of the installation.


4/44

Introduction



Prevailing goal of WT with rudimentary control systems

minimization of the cost

minimization of the maintenance

of the installation.

Recently,

increasing size of the WT use of mechanical actuators

opened the door to active control of the captured power.


5/44

Introduction

There are two types of wind control for turbines

constant speed control

variable speed control


6/44

Introduction




Constant speed rotors

are designed to deflect high wind gust loads


7/44

Introduction




Constant speed rotors

are designed to deflect high wind gust loadsVariable wind turbines

are designed to control strong and gusty winds

Some WT are able to operate at variable pitch

A new control strategy for variable-speed, variable pitchhorizontal-axis wind turbines (HAWTs) is proposed in thiswork.


8/44

Introduction

Office of Energy Efficiency and Renewable Energy Copyright.


9/44

Introduction

Control strategy summary

nonlinear dynamic chattering torque control linear blade pitch angle control


10/44

Introduction



The proposed controllers allow

a rapid transition of the WT generated power betweendifferent desired set values

electrical power tracking with a high-performancebehavior for all other state variables


11/44

Introduction



The proposed controllers allow

a rapid transition of the WT generated power betweendifferent desired set values

electrical power tracking with a high-performancebehavior for all other state variables

The proposed controllers are validated using

the National Renewable Energy Laboratory (NREL) WTsimulator FAST (Fatigue, Aerodynamics, Structures, andTurbulence) code.


12/44

Brief simulator description (FAST)

NRELs National Wind Technology Center develops CAE tools

that support the wind industry with state-of-the-art designand analysis capability

that have become the industry standard for analysis anddevelopment

that are free, publicly available, open-source,professional-grade products


13/44


NRELs National Wind Technology Center develops CAE tools

that support the wind industry with state-of-the-art designand analysis capability

that have become the industry standard for analysis anddevelopment

that are free, publicly available, open-source,professional-grade products

In particular, the FAST code

is an aeroelastic simulator

was evaluated in 2005 by Germanischer Lloyd WindEnergie and found suitable for the calculation of onshoreWT loads for design and certification


14/44


FAST main features

Computes structural-dynamic and control-systemresponses as part of the aero-hydro-servo-elastic solution

Uses a combined 24-DOF modal and multi-body

representation

Control system modeling through subroutines, DLLs, orSimulink R with MATLAB R

Nonlinear time-domain solution for loads analysis

Linearization procedure for controls and stability analysis


15/44



16/44

Control strategy: Torque Control

The electrical power-tracking error is defined as

e = Pe Pref, (1)where Pe is the electrical power and Pref is the reference power.


17/44



e = Pe Pref, (1)where Pe is the electrical power and Pref is the reference power.Let us impose a first-order dynamic to this error [B. Boukhezzar etal., 2007], e = ae Ksgn(e) a, K > 0, (2)and let us take in account that the electrical power is given by

Pe = cg, (3)

where c is the torque control in the rotor side and g is thegenerator speed.


18/44



e = Pe Pref, (1)where Pe is the electrical power and Pref is the reference power.Let us impose a first-order dynamic to this error [B. Boukhezzar etal., 2007], e = ae Ksgn(e) a, K > 0, (2)and let us take in account that the electrical power is given by

Pe = cg, (3)

where c is the torque control in the rotor side and g is thegenerator speed.Substitution of(1) and (3) in (2) yields the torque control

c =1g

[c(ag + g) aPref + Ksgn(Pe Pref)].


19/44

Control strategy: Torque ControlTheorem

The proposed controller

c =1g

[c(ag + g) aPref

+K

sgn(Pe

Pref

)].

ensures finite time stability.

Moreover, the settling time can bechosen by properly defining the

values of the parameters a and K.


20/44



c =1g

[c(ag + g) aPref

+Ksgn(Pe

Pref

)].



values of the parameters a and K.Proof mainly based on

Lyapunov functions and S. P. Bhat andD. S. Bernstein, ACC, 1997.


21/44



c =1g

[c(ag + g) aPref

+Ksgn(Pe

Pref

)].



values of the parameters a and K.Proof mainly based on

Lyapunov functions and S. P. Bhat andD. S. Bernstein, ACC, 1997.

Pref

Asymptotically stable

Finite time stability

0 5 10

200

400

600

800

1000

1200

1400

1600


22/44


How can we approximate g?

1.- Use the one-mass model of a wind turbine

g

Jtg = Tang Ktg Tgng

Jt: Turbine total inertia, Kg m2

Kt: Turbine total external damping, Nm rad1 s

Ta: Aerodynamic torque, NmTg: Generator torque in rotor side, Nm

g: generator speed, rad s1

ng: gearbox ratio

[B. Boukhezzar et al., 2007]


23/44


How can we approximate g?

1.- Use the one-mass model of a wind turbine

g

Jtg = Tang Ktg Tgng

Jt: Turbine total inertia, Kg m2

Kt: Turbine total external damping, Nm rad1 s

Ta: Aerodynamic torque, NmTg: Generator torque in rotor side, Nm

g: generator speed, rad s1

ng: gearbox ratio

[B. Boukhezzar et al., 2007]

2.- Use the estimator (transfer function in the Laplace domain)s

0.1s + 1

[M. W. Spong, and M. Vidyasagar, John Wiley and Sons, 1989]


24/44

Control strategy: Pitch Controller

A pitch proportional controlleris added upon the rotor speed tracking error

= K(r n), K > 0,

where r is the rotor speed and n is the nominal rotor speed.


25/44

Control strategy: Pitch Controller

A pitch proportional controlleris added upon the rotor speed tracking error

= K(r n), K > 0,

where

r is the rotor speed and

n is the nominal rotor speed.As we want to disable this control when r < n the finalproposed controller is given by the following expression

=

1

2 K(r n) [1 + sgn(r n)] , K > 0.


26/44

Simulation results

The 1.5 MW WT used for numerical validation using FAST.Installation of a General Electric 1.5 MW WT at the NationalWind Technology Center (left), and comparison (scale inmeters) with the Statue of Liberty (right)


27/44

Simulation results

Wind speed profile

0 5 10 15 20 25 30 358

9

10

11

12

13

14

15

time (s)

wind(m/s)


28/44

Simulation results

Wind speed profile

0 5 10 15 20 25 30 358

9

10

11

12

13

14

15

time (s)

wind(m/s)

WT Characteristics

Number of blades 3

Height of tower 82.39 m

Rotor diameter 70 m

Rated power 1.5 MW

Nominal rotor speed (n) 20 rpm


29/44

Torque Control

0 5 10 15 20 25 30 350

200

400

600

800

1000

1200

1400

1600

time (s)

Pe(kW)

Pref

Boukhezzar

K=1.5 10

6


30/44

Torque Control

0 5 10 15 20 25 30 3520

25

30

35

40

45

50

time (s)

r

(rp

m)

Boukhezzar

K=1.5 10

6

d i h C l


31/44

Torque and Pitch Control

0 5 10 15 20 25 30 350

200

400

600

800

1000

1200

1400

1600

time (s)

Pe(k

W)

Pref

Boukhezzar

K=1.5 10

6

T d Pi h C l


32/44


0 5 10 15 20 25 30 3520

20.5

21

21.5

22

22.5

23

23.5

time (s)

r

(rp

m)

Boukhezzar

K=1.5 10

6

T d Pit h C t l


33/44


0 5 10 15 20 25 30 350

2

4

6

8

10

12

14

time (s)

(de

g)

Boukhezzar

K=1.5 10

6

C l i


34/44

Conclusions

A WT controller is presented for a turbulence windcondition.

C l i


35/44

Conclusions


The nonlinear torque control leads to a good powerregulation, however it generates large rotor speed

fluctuations.

Conclusions


36/44

Conclusions



fluctuations. When the pitch controller is added upon the torque

controller then a good performance is obtained in rotorspeed and electrical power regulation.

Conclusions


37/44

Conclusions



fluctuations. When the pitch controller is added upon the torque

controller then a good performance is obtained in rotorspeed and electrical power regulation.

The proposed controller is easily applicable to other WTs.


38/44

Chattering Control Design on aVariable-Speed Horizontal-Axis Wind Turbine

L. Acho, Y. Vidal, M. Zapateiro,

F. Pozo and N. LuoCoDAlab, www-ma3.upc.edu/codalabDepartament de Matematica Aplicada III

Escola Universitaria dEnginyeria Tecnica Industrial de BarcelonaUniversitat Politecnica de Catalunya, Barcelona, Spain

Department of Electrical Engineering, Electronicsand Automatic Control,

Institute of Informatics and Applications,University of Girona, Girona, Spain



39/44


Proof.

Let us take the Lyapunov function V=

1

2 e

2

. Then,

V= ee = e(ae Ksgn(e)) = ae2 K|e| < 0. (4)

That is, the equilibrium is globally asymptotically stable.

Moreover, finite time stability can be proven. From (4),

V K|e| = K

2

V.

Thus, from Theorem 1 in [S. P. Bhat and D. S. Bernstein, (1997)],

the origin is a finite time stable equilibrium and

ts 1K

2(V)1/2, ts e

K



40/44


ComparisonResistor-Capacitor circuit Error dynamic K = 0

Cv + vR = 0 e + ae = 0

v(t) = v0 exp(tRC ) e(t) = e0 exp(at)Capacitor discharged after 5 sec. Settling time after 5 sec.

where = RC where = 1/a



41/44


Objective

Choose the values of the parameters a and K in the proposedcontroller to obtain the desired value in just 0.2(5) seconds.



42/44


Objective

Choose the values of the parameters a and K in the proposedcontroller to obtain the desired value in just 0.2(5) seconds.

Assuming that in a neighborhood oft = 0 the error is boundedby |e| = |Pe Pref| < 1.5 106 (rated power of the WT)

ts e

K 1.5 106.

Torque Control


43/44

Torque Control

0 5 10 15 20 25 30 350

1

2

3

4

5

6

7

8

time (s)

c

(kNm)

Boukhezzar

K=1.5 10

6



44/44


0 5 10 15 20 25 30 350

1

2

3

4

5

6

7

8

time (s)

c

(kNm)

Boukhezzar

K=1.5 10

6

SAICA Presentation

Documents

Transcript of SAICA Presentation