CSP vs PV DevelopingFrom a Solar Resource Perspective

Riaan Meyer

MD, GeoSUN Africa

1

Contents

• Solar Resource 101

• PV Developers

• CSP Developers

• Comparison

2

• Stellenbosch University spin-off, in partnership

with GeoModel Solar

• Solar Resource

– Solar Maps and GIS Layers

– Bankable Solar Resource Studies

– Yield Studies (PV)

• Instrumentation (Solar and Meteorological)

– Onsite measurements

– Supply and integration of equipment to solar

plants under construction

– Instrument Calibration

• Solar Forecasting

3

GeoSUN Africa

4

Global Horizontal Irradiance (GHI) Direct Normal Irradiance (DNI)

GHI applies to PV and SWH DNI applies to CSP and CPV

-20% -65%

Upington vs Durban: GHI

0

200

400

600

800

1000

1200

00

:00

04

:00

08

:00

12

:00

16

:00

20

:00

00

:00

GH

I [k

Wh

/m2/a

]

Upington

Durban

0

200

400

600

800

1000

1200

1400

139

77

11

515

319

122

926

730

534

338

141

945

749

553

357

160

964

768

572

376

179

983

787

591

395

198

910

27

10

65

11

03

11

41

11

79

12

17

12

55

12

93

13

31

13

69

14

07

14

45

14

83

15

21

15

59

15

97

16

35

16

73

17

11

17

49

17

87

18

25

18

63

19

01

19

39

19

77

Upington

Durban

A clear day in Upington and Durban

6

Precipitation vs Irradiance

7

900 1100 1300 1500 1700 1900 2100 2300 2500

Namibia

South Africa

KZN

Spain

Germany

Belgium

GHI [kWh/m2/a]

KZN’s solar (GHI) resource is as good, if not better, than that of Spain!

PV Developers

8

Solar Maps for

South Africa

9

10

Tracking?

11

1-axis – vertical axis at 30°

Satellite derived data

12

Comparison of Solar Resource Assessments for South Africa, (2009), TP Fluri

and TW von Backstrom, ISES Solar World Congress

GHI GTI DNI

SolarGIS satellite data uncertainty

DNI: ±4%

GHI: ±2.5%

Best

Achievable

uncertainty

currently

Source: GeoModel Solar, ESMAP Malawi project

Data Comparisons

Ground measured temperature are compared to Satellite SolarGIS –

temperatures from NWMs. Data of both time series have an hourly

temporal resolution.

Inter-annual variability

15

2000

2050

2100

2150

2200

2250

2300

GH

I [k

Wh

/m2/a

]

+4.9%

-4.4%

CSP Developers

16

17

DNI Solar Map: NREL data obtained from the SWERA website

DNI

18

Solar Map: NREL data obtained from the SWERA website

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DNI Measurement Stations in South Africa

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SAWS

21

www.sauran.net

CSP/CPV

• All CSP and CPV developers deploy on-site

measurements

• Mandated by RE-IPPPP (CSP) and banks (CSP

and CPV)

• Due to higher uncertainties of satellite derived data

22

23

DNI Measurements - pyrheliometer

Satellite derived data

24

Comparison of Solar Resource Assessments for South Africa, (2009), TP Fluri

and TW von Backstrom, ISES Solar World Congress

GHI GTI DNI

Satellite

Derived vs

Ground

Measured Data

2

3

4

5

6

1-J

un

-11

4-J

un

-11

7-J

un

-11

10-J

un-1

1

13-J

un-1

1

16-J

un-1

1

19-J

un-1

1

22-J

un-1

1

25-J

un-1

1

28-J

un-1

1

GH

I -

da

ily t

ota

l [k

Wh

/m2/d

ay]

GHI - Satellite HC-3 GHI - Ground measured GHI - Satellite SGIS

0.0

2.5

5.0

7.5

10.0

12.5

15.0

1-M

ay-1

1

4-M

ay-1

1

7-M

ay-1

1

10-M

ay-1

1

13-M

ay-1

1

16-M

ay-1

1

19-M

ay-1

1

22-M

ay-1

1

25-M

ay-1

1

28-M

ay-1

1

31-M

ay-1

1

DN

I -

da

ily t

ota

l [k

Wh

/m2/d

ay]

DNI - Ground measured DNI - Satellite

Data Comparisons

Ground measured DNI (pyrheliometer) is compared to Satellite derived

DNI (SolarGIS). Data of both time series have an hourly temporal

resolution.

Inter-annual variability

27

+14.3%

-7.8%

2000

2100

2200

2300

2400

2500

2600

2700

2800

2900

3000

DN

I [k

Wh/m

2/a

]

28

Other factors…………

You need water!

The land must be flat

The shape of the land is important

Limited technology suppliers

You need more people on site

Road Access

Photovoltaics

• GHI is the most common solar

map with relative good

accuracies – with other maps

also now available (GTI,

PVOut, PVTracking, etc.)

• GHI is the most commonly

measured solar data parameter

• The cost of a PV solar

measurement station is

significantly lower than that of

DNI

• Satellite derived GHI data is

available at a lower cost than

DNI data

• Satellite derived GHI data has

lower uncertainty than DNI

• Few DNI maps are available in

general with relative high

uncertainties

• Few DNI measurements are

available, especially in the

public domain

• The cost of a CSP solar

measurement station is

significantly higher than that of

a PV station

• Satellite derived DNI data is

more expensive than GHI/GTI

data

• Satellite derived DNI data has

higher uncertainties than

GHI/GTI29

Concentrating Solar

Power

World DNI Map (SolarGIS)

www.solargis.info/imaps30

Thank you for your attentionContact Details

Mr Riaan Meyer, 084 876 4816

Unit 1, CS Africa building, 1 Meson Street

Techno Park, Stellenbosch, 7600, South Africa

riaan.meyer@geosun.co.za www.geosun.co.za

GeoSUN Colaborators GeoSUN Clients