CSP vs PV Developing From a Solar Resource Perspective. Riaan Meyer MD, GeoSUN Africa
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1 CSP vs PV Developing From a Solar Resource Perspective Riaan Meyer MD, GeoSUN Africa 1
2 Contents Solar Resource 101 PV Developers CSP Developers Comparison 2
3 GeoSUN Africa 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
4 Global Horizontal Irradiance (GHI) Direct Normal Irradiance (DNI) GHI applies to PV and SWH -20% -65% DNI applies to CSP and CPV 4
5 00:00 04:00 08:00 12:00 16:00 20:00 00:00 GHI [kwh/m 2 /a] Upington vs Durban: GHI Upington Durban Upington Durban A clear day in Upington and Durban
6 Precipitation vs Irradiance 6
7 Belgium Germany Spain KZN South Africa Namibia GHI [kwh/m 2 /a] KZN s solar (GHI) resource is as good, if not better, than that of Spain! 7
8 8 PV Developers
9 9 Solar Maps for South Africa
10 10
11 Tracking? 11 1-axis vertical axis at 30
12 Satellite derived data GHI GTI DNI Comparison of Solar Resource Assessments for South Africa, (2009), TP Fluri and TW von Backstrom, ISES Solar World Congress 12
13 SolarGIS satellite data uncertainty Best Achievable uncertainty currently DNI: ±4% GHI: ±2.5% Source: GeoModel Solar, ESMAP Malawi project
14 Data Comparisons Ground measured temperature are compared to Satellite SolarGIS temperatures from NWMs. Data of both time series have an hourly temporal resolution.
15 GHI [kwh/m 2 /a] Inter-annual variability % %
16 16 CSP Developers
17 DNI DNI Solar Map: NREL data obtained from the SWERA website 17
18 Solar Map: NREL data obtained from the SWERA website 18
19 19
20 DNI Measurement Stations in South Africa SAWS 20
21 21
22 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 23 DNI Measurements - pyrheliometer
24 Satellite derived data GHI GTI DNI Comparison of Solar Resource Assessments for South Africa, (2009), TP Fluri and TW von Backstrom, ISES Solar World Congress 24
25 1-May-11 4-May-11 7-May May May May May May May May May-11 DNI - daily total [kwh/m 2 /day] 1-Jun-11 4-Jun-11 7-Jun Jun Jun Jun Jun Jun Jun Jun-11 GHI - daily total [kwh/m 2 /day] 6 GHI - Satellite HC-3 GHI - Ground measured GHI - Satellite SGIS Satellite Derived vs Ground Measured Data DNI - Ground measured DNI - Satellite
26 Data Comparisons Ground measured DNI (pyrheliometer) is compared to Satellite derived DNI (SolarGIS). Data of both time series have an hourly temporal resolution.
27 DNI [kwh/m 2 /a] Inter-annual variability % %
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 28
29 29 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 Concentrating Solar Power 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/GTI
30 World DNI Map (SolarGIS) 30
31 Thank you for your attention Contact Details Mr Riaan Meyer, Unit 1, CS Africa building, 1 Meson Street Techno Park, Stellenbosch, 7600, South Africa riaan.meyer@geosun.co.za GeoSUN Colaborators GeoSUN Clients
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