Accelerating Wind Energy 1 A physical approach to monitor tower base fatigue loads using standard...

Accelerating Wind Energy1

Accelerating Wind EnergyA physical approach to monitor tower base fatigue loads using standard signals

Thesis presentationFreark Koopman

Committee:Gerard van Bussel

Dick VeldkampGijs van der Veen

Agenda

1. Wind Energy

2. Wind Turbines

3. Load monitoring

4. Physical approach

5. Results

6. Conclusions

Accelerating Wind Energy2

Wind Energy

Accelerating Wind Energy3

1

Wind Turbines

Accelerating Wind Energy4

2

Load monitoring

Accelerating Wind Energy5

23

• Gain insight in the load history

• Prevent breakdown

• Check your design

• Reduce cost of energy

• Find abnormal turbine behaviour

3

Load monitoring

Accelerating Wind Energy6

• Measure (Direct)

• Expensive

• Time consuming

Load monitoring

Accelerating Wind Energy7

• Estimate (Indirect)

• Already available signals

• No extra sensorsL

Load monitoring

Accelerating Wind Energy8

• Standard signals

• Wind speed

• Pitch angle

• Power output

• Rotor speed

• Nacelle acceleration

Load monitoring

Accelerating Wind Energy9

• Neural network

• Good results

• No insight in

underlying process

Physical approach

Accelerating Wind Energy10

L

4

Physical approach

Accelerating Wind Energy11

M(x,t)kev(x)EIv(L,t)

Physical approach

Accelerating Wind Energy12

Physical approach

Accelerating Wind Energy13

Time

Acc

eler

atio

n

v(L,t)a(L,t) ∬dtdt

Dis

plac

emen

t

Physical approach

Accelerating Wind Energy14

v(L,t)a(L,t) ∬dtdt

Time

Dis

plac

emen

t

~150 m

• Fourier

Physical approach

Accelerating Wind Energy15

• Fourier

Time

Am

plitu

de

Physical approach

Accelerating Wind Energy16

• Fourier

Frequency

Am

plitu

de

v(L,t)a(L,t) ∬dtdt v(L,t)a(L,t) ∬dtdtHigh-PassFilter(f>50mHz)

v(L,t)a(L,t) ∬dtdtHigh-PassFilter(f>50mHz)

Physical approach

Accelerating Wind Energy17

Time

Acc

eler

atio

nD

ispl

acem

ent

Physical approach

Accelerating Wind Energy18

vFA(L,t)aFA(L,t) ∬dtdtHigh-Pass Filter (f>50mHz)

P(t) ThrustΩ (t) θ (t)

1/KLow-Pass Filter (f<50mHz)+

U∞ (t)

Gαev-

vFA(L,t)aFA(L,t) ∬dtdtHigh-Pass Filter (f>50mHz)

P(t) ThrustΩ (t) θ (t)

1/KLow-Pass Filter (f<50mHz)+

U∞ (t)

Results

Accelerating Wind Energy19

5

vFA(L,t)aFA(L,t) ∬dtdtHigh-Pass Filter (f>50mHz)

P(t) ThrustΩ (t) θ (t)

1/KLow-Pass Filter (f<50mHz)+

U∞ (t)

Gαev

-

VSvFA(L,t)aFA(L,t) ∬dtdtHigh-Pass Filter (f>50mHz)

P(t) ThrustΩ (t) θ (t)

1/KLow-Pass Filter (f<50mHz)+

U∞ (t)

Gαev-

Results

Accelerating Wind Energy20

Time

Ben

ding

Mom

ent

Results

Accelerating Wind Energy21

Time

Ben

ding

Mom

ent

Results

Accelerating Wind Energy22

= 1

vFA(L,t)aFA(L,t) ∬dtdtHigh-Pass Filter (f>50mHz)

P(t) ThrustΩ (t) θ (t)

1/KLow-Pass Filter (f<50mHz)+

U∞ (t)

Gαev

-

Results

Accelerating Wind Energy23

0 5 10 15 20 250.6

0.8

1

1.2

1.4

1.6

Wind Speed [m/s]

Conclusions

Accelerating Wind Energy24

• From nacelle acceleration to tower bending moment

• High-pass filter to prevent drift

• Thrust estimator for low frequency compensation

• Gravity correction necessary

• The equivalent loads are underestimated by 8% with a standard deviation

of 6%

6

Accelerating Wind EnergyA Physical approach to monitor tower base fatigue loads using standard signals

Thank you for your attention

Accelerating Wind EnergyA Physical approach to monitor tower base fatigue loads using standard signals