07. guda 30

Fundashon Antiyano Pa Energia

Wind energy in Curaçao

Durable Energy Conference Curaçao

Margo Guda Manager & Senior Scientist,

Fundashon Antiyano Pa Energia Curaçao, March 30, 2012


Short historical overview

• Water pumping • Enthusiasts and hobbyists • UNA and FAPE • Kodela • Wind farms: Tera Kora and Playa

Kanoa


Wind energy in Curaçao: past barriers

• No wind resource assessment • No policy • No support • No financial incentives


Wind energy in Curaçao: successes

• Wind resource assessment • Development of local expertise • Wind farm development • Success builds success: from Tera Kora

to Playa Kanoa • Wind farm expansion (context:

worldwide and regional developmens)


Curaçao in the Caribbean context

• Curaçao, Barbados, Guadeloupe and Martinique

• Jamaica • Aruba, Republica Dominicana, Bonaire • Puerto Rico, Cuba • Guyana, Panama? • Grenada, St Vincent, Nevis • Suriname, Trinidad & Tobago

4/2/2012

Fundashon Antiyano Pa Energia 4/2/2012

Wind Energy Basics

How to harvest wind energy

Wind Energy Output = Wind Resource x Power Curve


wind resource:

• Global wind systems • Local effects


description of the wind resource:

• variability in time • Variability in space • Vertical profiles • Annual distributions of wind speed • Wind direction and its variation • turbulence


Wind characteristics • Power in the wind

– Depends on air density – Capture area – Cube of wind speed

vA21=P 3ρ


The Betz Maximum

• The theoretical maximum rotor efficiency is reached for:

• And has a value of 16/27. • This is better known as the Betz Maximum:

Cp = 16/27 = 0.593

13

ζ = 2

1

vv

ζ =


Wind resource assessment – Establish values for the most important

wind regime variables: – Average wind speed and direction – Distribution of observed/observable

averages – Description of variability


Wind resource

• Wind resources: a global view


Wind resource • Global wind resource map


Country wind map


A snapshot of a wind regime

Examples of variation: •diurnal variation •Seasonal variation •Annual distribution of wind speeds •turbulence intensity (not shown)

ANNUALIZED DIURNAL VARIATION:WINDSPEEDAirport site 01

TIME OF DAY (hours)

WIN

DS

PE

ED

(m/s

)

2.00

4.00

6.00

8.00

10.00

0 1 2 3 4 5 6 7 8 9 1011121314151617181920212223

ave=6.11

<v> at 10m

Long term average monthly windspeed (1964-1991)

win

dspe

ed (m

/s

2

3

4

5

6

7

8

9

10

jan feb mar apr may jun jul aug sep oct nov dec

average monthly windspeed period average

FREQUENCY DISTRIBUTION OF WINDSPEEDSAirport site 01

windspeed bin (m/s)

rela

tive

frequency

0

0.05

0.1

0.15

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

distribution at 10m calculated

MONTHLY DIURNAL VARIATION:WINDSPEEDAnnual average

TIME OF DAY (hours)

WIN

DSP

EED

(m/s

)

2.00

4.00

6.00

8.00

10.00

0 1 2 3 4 5 6 7 8 9 1011121314151617181920212223

airport Tera Kora Parera


A snapshot of a wind regime

6,00

6,20

6,40

6,60

6,80

7,00

7,20

7,40

7,60

7,80

WIN

DSP

EE

D (m

/s)

year

long term windspeed data airport annual average

avg spd

regression

Inter-annual variation at reference site


Calculating energy yield • Wind resource x turbine power curve

– Energy calculation equation

– Weibull frequency distribution

– Ideal wind turbine power curve

0

( ) ( )E T P v f v dv∞

= ∫

1( ) ( ) exp( ( ) )k kk v vf vc c c

−= −

3max

3max

1( ) ( ) (0 )21( ) ( ) (0 )2

p r

p out

P v A c v v v

P v A c v v v

ρ η

ρ η

= ≤ ≤

= ≤ ≤


Weibull distributions of different shapes

Weibull functions for different shape factors

k=2

k=1

k=1.5

k=2.5

k=4

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0 1 2 3 4 5 6 7 8 9 10Windspeed in m/s

freq

uenc

y (r

elat

ive)


Energy yield calculation

0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

0 5 10 15 20 25 30 35 Po

wer

out

put (

kW)

wind speed in m/s

Power curve

0.27 kW, 1.7m

0

50

100

150

200

250

300

350

0 10 20 30

Ann

ual e

nerg

y ou

tput

(kW

h)

wind speed in m/s

Annual energy 0

500

1000

1500

2000

2500

0 10 20 30

hour

s per

yea

r

wind speed in m/s

Wind regime

977 kWh

7m/s, k=4



0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

0 5 10 15 20 25 30 35 Po

wer

out

put (

kW)

wind speed in m/s

Power curve

0.27 kW, 1.7m

0

500

1000

1500

2000

2500

0 10 20 30

hour

s per

yea

r

wind speed in m/s

Wind regime

7m/s, k=2

0

50

100

150

200

250

300

350

0 10 20 30

Ann

ual e

nerg

y ou

tput

(kW

h)

wind speed in m/s

Annual energy

933 kWh



0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

0 5 10 15 20 25 30 35 Po

wer

out

put (

kW)

wind speed in m/s

Power curve

0.27 kW, 1.7m

0

500

1000

1500

2000

2500

0 10 20 30

hour

s per

yea

r

wind speed in m/s

Wind regime

7m/s, k=5.5

0

50

100

150

200

250

300

350

0 10 20 30

Ann

ual e

nerg

y ou

tput

(kW

h)

wind speed in m/s

Annual energy

981 kWh



0

500

1000

1500

2000

2500

0 10 20 30

hour

s per

yea

r

wind speed in m/s

Wind regime

7m/s, k=2

0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

0 5 10 15 20 25 30 35 Po

wer

out

put (

kW)

wind speed in m/s

Power curve

1.0 kW, 2.5m

0

50

100

150

200

250

300

350

0 10 20 30

Ann

ual e

nerg

y ou

tput

(kW

h)

wind speed in m/s

Annual energy

3694 kWh



0

0,2

0,4

0,6

0,8

1

1,2

1,4

0 5 10 15 20 25 30 35 Po

wer

out

put (

kW)

wind speed in m/s

Power curve

1.0 kW, 2.5m

0

500

1000

1500

2000

2500

0 10 20 30

hour

s per

yea

r

wind speed in m/s

Wind regime

7m/s, k=4

0

50

100

150

200

250

300

350

0 10 20 30

Ann

ual e

nerg

y ou

tput

(kW

h)

wind speed in m/s

Annual energy

3477 kWh



0

0,2

0,4

0,6

0,8

1

1,2

1,4

0 5 10 15 20 25 30 35 Po

wer

out

put (

kW)

wind speed in m/s

Power curve

1.0 kW, 2.5m

0

500

1000

1500

2000

2500

0 10 20 30

hour

s per

yea

r

wind speed in m/s

Wind regime

7m/s, k=5.5

0

50

100

150

200

250

300

350

0 10 20 30

Ann

ual e

nerg

y ou

tput

(kW

h)

wind speed in m/s

Annual energy

3328 kWh


Effects of going higher • Influence of

topography and geography – Vertical wind profile – Geostrophic and

surface winds – Terrain roughness

and topography • Buildings • Trees • Hill tops and ridges

– Thermal influences

logarithmic vertical profile

0

20

40

60

80

100

120

0 5 10 15

wind speed (m/s)

heig

ht a

bove

gro

und

zzu=v(z)0

* lnκ


Factors influencing wind regimes

• Topographical and geographical influences – Terrain roughness

and topography • Buildings • Trees • Hill tops and ridges

– Thermal influences


Types of wind systems

• HAWT and VAWT


Types of wind systems

• Upwind or downwind


Grid-connected system


Wind energy in Curaçao: new possibilties

• Small scale wind energy applications • The new energy policy


Wind energy in Curaçao: looking ahead

• Wind farms: larger than ever • Your own wind turbine…? • Community scale wind energy?


Thank you

Remember: the sun will still shine and the wind will still blow when the oil runs

out…

(free from Oliver Headley†)

4/2/2012

07. guda 30

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