Results of Solar Resource Assessments in the UNEP/SWERA Project

Dave RennéRay GeorgeBill Marion

National Renewable Energy Laboratory1617 Cole Boulevard

Golden, CO 80401-3393e-mail: david_renne@nrel.gov

Richard PerezAtmospheric Sciences Research CenterState University of New York/Albany

Albany, NYe-mail: perez@asrc.cestm.albany.edu

Christoph Schillings and Franz Trieb German Aerospace Center (DLR),

Institute of Technical Thermodynamics,Stuttgart, Germany

Richard MeyerGerman Aerospace Center (DLR),Institute of Atmospheric Physics,

Oberpfaffenhofen, Germany

Enio B. PereiraFernando R Martins

Instituto Nacional de Pesquisas Espaciais(INPE), São Jose Dos Campos, SP, Brazil

Samuel Luna de AbreuSergio Colle

LabSolarUniversidad Federal de Santa Catarina

Florianopolis, Brazil

Mahesh VipradasThe Energy Resources Institute (TERI)

New Delhi, India

Paul StackhouseNASA/Langley Research Center

Langley, Virginia

Christian A. GueymardSolar Consulting Services

New Smyrna Beach, FL 32168, USA

Tom HamlinSWERA Project Manager, UNEP/DTIE

TourMirabeau - 39-43, Quai André Citroen75739 Paris Cedex 15

France

ABSTRACT

This paper provides a summary of the solarresource information that has been developed todate for the 13 countries participating in theUnited Nations Environment Programme’s(UNEP’s) Solar and Wind Energy ResourceAssessment (SWERA) project. The solarassessments include country-specific maps aswell as maps of large regions encompassingthese countries. In addition, solar time series andTypical Meteorological Year (TMY) data setsare developed for selected stations within eachcountry.

Besides these solar resource products developedby the SWERA international technical team,information on validation of the results, andintercomparison of the various approaches, hasbeen done in collaboration with country partnersworking with the international team. Theseproducts are being used by government andindustry to facilitate the development of

renewable energy technologies in thesedeveloping countries.

1. INTRODUCTION

The United Nations Environment Programme(UNEP), through funding from the GlobalEnvironment Facility (GEF), has beensupporting the Solar and Wind Energy ResourceAssessment Project for 13 countries around theworld, shown in Fig. 1. The countries areGuatemala, Nicaragua, El Salvador, Honduras,Cuba, Brazil, Ghana, Ethiopia, Kenya, SriLanka, Bangladesh, Nepal, and China. SWERAis providing high quality wind and solar resourceinformation in Geographic Information Systems(GIS) format for these 13 countries, a GeospatialToolkit to allow users to analyze the resourcedata in context with other geospatial data sets(such as roads, transmission lines, protectedareas, demographic centers, etc.), and a web-based data archive that makes the informationavailable to the entire world. An internationaltechnical team has been assembled to develop

the resource information, and country partnershave been identified to work with the team andassist in the development and validation of theresource data sets. The project began in 2002,and will be completed by the end of 2005.

Fig. 1: Location of the 13 SWERA participatingcountries

Several members of the SWERA internationalteam have been conducting solar resourceassessments. These include the NationalRenewable Energy Laboratory (NREL), and theAtmospheric Sciences Research Center at theState University of New York (SUNY)/Albanyin the U.S., the German Aerospace Center (DLR)in Germany, The Energy Resources Institute(TERI) in New Delhi, India, the InstitutoNacional de Pesquisas Espaciais (INPE) in SaoJose dos Campos, Brazil, and LABSOLAR at theUniversity of Santa Catarina (UFSC) inFlorianópolis, Brazil. An overview of theirrespective approaches for producing solarresource data was published in 2002 (1).

In the following sections, preliminary results ofthe various solar resource assessment approachesare provided. A robust set of products, alongwith validation and cross-model intercomparisonstudies, will be made available. SUNY/Albany,DLR, INPE/LABSOLAR, and TERI aredeveloping high resolution (approx. 10 km x 10km) data sets for specific countries or smallerregions, while NREL and INPE/LABSOLAR areproducing medium-resolution data sets (approx.40 km x 40 km) for large regions. The U.S.National Aeronautics and SpaceAdministration’s (NASA’s) Surface SolarEnergy (SSE) “Low Resolution” (10 x 10) globalsolar energy data set represents an overlay forthe entire project; these data are on the NASAweb site http://eosweb.larc.nasa.gov/sse/. Alldata are archived at the UNEP GRID (GlobalResource Information Database) Sioux Falls

facility in South Dakota, USA, and willultimately be available on the SWERA archivethrough the site http://swera.unep.net.

2. MEDIUM-RESOLUTION REGIONALSOLAR MAPS

NREL has developed medium-resolution (40-km) climatological (1985-1991) solar data setsfor four regions around the world: CentralAmerica/Cuba and the Caribbean region,Asia/South Asia, Africa, and South America.The technique uses the 40-km resolution griddedcloud cover data (Real-Time Nephanalysis)provided by the U.S. National Climatic DataCenter (NCDC) as input to NREL’sClimatological Solar Radiation (CSR) model (2).The model uses an updated gridded aerosoloptical depth data set developed specifically forthis project (3). This aerosol data set is based ona combination of various satellite-deriveddatasets and ground-based sun photometricspectral measurements. The CSR model outputsmonthly and annual average daily total solarradiation values for fixed flat plate collectorsoriented at latitude tilt (for photovoltaicsystems), direct normal values (forconcentrators) and diffuse sky values (fordaylighting analysis).

At the time of this writing, results for CentralAmerica and for the Asia/south Asia region arecompleted. The regional analyses for Africa andfor South America will be completed bysummer, 2005.

Fig. 2 provides an example of a regionalanalysis, showing the annual average daily totalsolar resource for fixed flat plate collectorsoriented at latitude tilt for the CentralAmerica/Caribbean region. Fig. 3 provides thesame information for the four Central Americancountries in SWERA.

Fig. 2: Solar resource for fixed plate collectorsat latitude tilt (NREL’s CSR model); CentralAmerica/Caribbean region.

Fig. 3: Solar resource for fixed plate collectorsat latitude tilt (NREL’s CSR model); SWERACentral America countries.

INPE/LABSOLAR have also developed 40-kmregional solar data sets for South America, usingthe BRASIL-SR model. The BRASIL-SR modelis a spectral physical model that combines theutilization of the “two-stream” method to solvethe radiative transfer equation using satellite dataand climatological information. It was developedfirst in Germany (GKSS, Geesthacht) and, later,adapted and improved in Brazil by means of anagreement between LABSOLAR and INPE (4).This information has been incorporated into asolar atlas for Brazil.

3. HIGH-RESOLUTION SOLAR MAPS

High resolution (10-km) site-time specific solardata covering a 4 or 5-year period has beendeveloped by the State University of New York(Albany) for Central America, Cuba and portions

of Brazil, using imagery from two GeostationaryOperational Environmental Satellites (GOES 8and 10) positioned over the equator in twowestern Hemisphere locations (5). Fig 4.provides DNI information derived fromtheapplication of this methodology in CentralAmerica.

Fig 4: High-resolution DNI for Central America(SUNY/Albany method)

DLR (Germany) has developed similar data setsfor the countries of Ghana, Kenya, Ethiopia, SriLanka, Bangladesh, Nepal, and western Chinacovering a 3-year period. In addition, hourlytime series for selected sites for each country areprovided. The DLR-method is based on datafrom two METEOSAT geostationary satellites,both located over the equator, one at 00

Longitude, and one at 690E Longitude. Themethod calculates accurate hourly solar directnormal irradiance (DNI) with high spatialresolution independently from groundmeasurements (6). Fig. 5 is an example of ahigh-resolution map for western China using theDLR method.

Fig. 5: High-resolution (10-km) map of annualaverage daily total sum of direct normalirradiance (DNI) in kWh/m_/day for westernChina (year 2000) based on DLR-methodology.

The SUNY/Albany method was originallydesigned to produce global horizontal irradiance(GHI) values, while DLR’s method originallyfocused on DNI (for Concentrating Solar Powerapplications). The two organizations are nowworking in collaboration through SWERA sothat each has the capability to provide both GHIand DNI resource information from theirrespective methodologies.

In addition to their 40-km methodology,INPE/LABSOLAR have developed high-resolution solar resource data for Brazil usingtheir physically-based BRASIL-SR model forGHI and DNI. Fig. 6 shows an example of aGHI map using this approach.

Fig. 6: Annual average global horizontal solarresource, BRASIL-SR high-resolution (10-km)model

Because the data record available to the SWERAteam from the geostationary satellites coversonly a few years, tools will also be developed toallow the user to generate longer-term time seriesdata at any location based on adjusting time-series solar data, either measured or estimatedfrom weather observations at ground stations, tothat specific point.

TERI (India) is also engaged in the high-resolution solar resource work for countriescovered by the Indian Geostationary Satellite(INSAT). They have recently adapted theBRASIL-SR model to the Indian subcontinent,and will post the results to the SWERA archiveby the end of the project.

4. SOLAR TIME SERIES AND TMY DATA

Using the methods developed in (7) and (8),NREL is providing solar resource time series andTMY data for a number of select ground stationswithin each of the 13 countries. Themethodology incorporates the reported cloudcover observations from national weatherservices in each country into the METSTATmodel. These cloud cover observations, alongwith other key meteorological parameters, areavailable from NCDC’s DATSAV3 globalweather archive. The period of record for mostof the stations in this data set typically exceeds20 years; however, careful screening of the datais required in order to determine if sufficient dataare available to produce a reliable TMY. Insome countries, only a few stations ultimatelywere available for the analyses, while in others(such as China) nearly 50 stations wereavailable. All of the time series and TMY datasets are available through the SWERA archive.

5. MODEL CROSS-COMPARISON ANDVALIDATION STUDIES

NREL, SUNY, DLR and INPE/LABSOLAR areengaged in a model cross-comparison study overnortheastern Brazil to establish the relativeuncertainties of the various approaches. Thisregion is unique because it is “seen” by both theeastern GOES and the western METEOSATgeostationary satellites. A ground solarmeasurement station has been installed by INPEnear the city of Caicó in northeast Brazil, andintercomparisons among the various modelingtechniques are being conducted relative to thisreference station. Additional intercomparisonsof the BRAZIL-SR and the NREL CSR models

will be conducted at the Florianopolis andBalbina (Amazon region) Baseline SurfaceRadiation Network (BSRN) stations. In all casesthe NASA SSE data set is also incorporated as areference data set to the intercomparisons.

Partners from the 13 countries are also engagedin model validation exercises, using independentdata sets available from within their countries.For example, in Managua, Nicaragua data from ahigh quality solar measurement station at theUniversity of Central America (UCA), Managua,and maintained by Padre Lopez de la Fuentes,was made available to the SWERA team for theirmodel validation activities in the region. Apreliminary result of the comparisons of themodels with the surface data for the cellsimmediately over Managua is shown in Table 1.Data from the NASA SSE dataset for theManagua region is included in the table. Theresults show that all the models compare towithin 1-5% on an annual average basis.

TABLE 1: COMPARISON OF MODELEDANNUAL AVERAGE GHI WITHOBSERVATIONS AT UCA, MANAGUA,NICARAGUA

Method Period W-h-m-2-day-1

SUNY/A 1998-2002 5506UCA(MEAS.)

1998-2002 5547

NREL 1985-1991 5477UCA(MEAS.)

1985-1991 5378

NASA/SSE 1985-1991 5688

5. SUMMARY

The UNEP/SWERA project represents one of thefirst attempts ever to conduct a combined windand solar resource assessment for multipleregions around the world, and to incorporate thisinformation into a GIS framework and make thedata available through a well-established globalarchive. This project serves to remove keyinformation barriers and greatly facilitate thedevelopment of renewable energy technologiesworldwide. As more and more countries see thevalue that the SWERA products offer theoriginal 13 endorsing countries, other countriesare also expected to seek funding to have a

similar set of data products developed for theirown use.

6. REFERENCES

(1) Renné, D., R. Perez, C. Schillings, F. Trieb,R. Meyer, E. B. Pereira, M. Vipradas, T. Hamlin,Solar Resource Assessment Methods for theUnited Nations Environment Programme’s Solarand Wind Energy Resource Assessment(SWERA) Project, Proceedings, National SolarConference, American Solar Energy Society,2003(2) Maxwell. E. L., R. L. George, and S. M.Wilcox, A Climatological Solar RadiationModel. Proceedings, 1998 Annual Conference,American Solar Energy Society, Albuquerque,New Mexico, pp. 505-510, 1998(3) Gueymard, C. and R. George, GriddedAerosol Optical Depth Climatological Datasetsover Continents for Solar Radiation Modeling,Proc. Solar World Congress, International SolarEnergy Society, 2005(4) Colle, S. and E. Pereira, Atlas of SolarIrradiation in Brazil (in Portuguese). BrazilianNational Institute of Meteorology, INMET Press,1998, 57 pp.(5) Perez, Richard, Kathy Moore, MarekKmiecik, Cyril Chain, Pierre Ineichen, RayGeorge, and Frank Vignola, A New OperationalSatellite-to-Irradiance Model: Description andValidation. Proceedings, Solar 2002, Reno,Nevada, USA, 2002(6) Schillings C., H. Mannstein and R. Meyer,Operational method for deriving high resolutiondirect normal irradiance from satellite data. SolarEnergy 76(4): 475-484, 2004(7) Marion, W. and R. George, Calculation ofsolar radiation using a methodology withworldwide potential, Solar Energy 71(4):275-283, 2001(8) Marion, W. and K. Urban, User’s manual forTMY-2s-typical meteorological years derivedfrom the 1961-1990 National Solar RadiationData Base, NREL/SP-463-7668, NationalRenewable Energy Laboratory, Golden,Colorado USA, 1995