Assessment and Evaluation

of Solar Resources

Luis Martín Pomares

IrSOLaV

Contents

Assessment and Evaluation of Solar Resources............................................................................1

1. Introduction.........................................................................................................................3

2. Solar Geometry....................................................................................................................3

3. Interaction of solar radiation with the atmosphere.............................................................9

4. Solar radiation estimated from satellite.............................................................................12

5. Measurement of solar radiation.........................................................................................14

6. Data quality assessment.....................................................................................................14

7. Databases of solar radiation...............................................................................................18

8. Using of solar radiation data for CSP technologies.............................................................27

9. References..........................................................................................................................27

1. Introduction

The solar radiation is a meteorological variable measured only in few measurement stations and during short and, on most occasions, discontinuous periods of times. The lack of reliable information on solar radiation, together with the spatial variability that it presents, leads to the fact that developers do not find appropriate historical databases with information available on solar resource for concrete sites. This lack provokes in turn serious difficulties at the moment of projecting or evaluating solar power systems. The next paragraphs are a summary of concepts and tools which can help to the solar community to evaluate their projects.

2. Solar Geometry

The trajectory which describes the sun in the vault of heaven varies for each day of the year. This way, the modeling and the solar irradiance measurements need to know with precision the position of this heavenly body in each instant of the day and each day of the year.

The Sun can be considered as a sphere of 1.39 106 km of diameter and 1.99 1032 kg of mass where thermonuclear reactions are produced which transform the hydrogen nucleus in helium nucleus. Due to these nuclear reactions, the temperature in the surface varies between 4700 and 7500 K, and its emissions belong to the spectrum of a black body. Supposing that the temperature and the Sun’s radiation spectrum are constant, the quantity of the energy which reaches the surface of the earth atmosphere can be established analytically from the relative positions of the Sun and the Earth. Due to the fact that the Earth has also a movement of rotation in its own axis and another of translation around the Sun, it is necessary to define previously a spatial and temporal reference system which places the Sun and the Earth, due to the fact that they are two bodies in motion.

Temporal reference systemThe solar day can be defined as the temporal interval in which the Sun cross two times the same local meridian. The longitude of the solar day is not constant, due to the fact that it changes along the year because the following reasons:

The distance Sun-Earth. The distance Sun-Earth, due to the elliptic orbit, which the Earth describes around the

Sun, and which varies along the year. The inclination of the Earth rotating axis (~23.5º) in relation to the translation plane

around the Sun known also as the elliptical plane.

True solar time (TSV) is defined as the time counted from the solar meridian. In another way, local official hour or mean local time (TLM) corresponds with the hour which we frequently use in our clocks and it is established by each count. The conversion from official time to local solar time needs two corrections:

The difference in terms of geographic longitude between the meridian of the observer and the reference meridian for which the official hour was defined (4 minutes for each geographic degree).

The effects which are expressed in the equation of time and are due to the eccentricity of the Earth, the constant in areolar speed (2º Law of Kepler) and the movements of the axis of the Earth.

The calculation of the time equation in minutes can be done using the following expression:

(1)

where Γ represents the daily angle; it is depenant of the Julian day ( ) and can be calcualted, in radians, as:

(2)

In certain occasions, it can be necessary a third temporal correction ( ) due to the hourly

changes to save energy as a policy of the country (in Spain =1 in winter and in summer =2). This way, para transformar el tiempo solar verdadero en hora decimal, se puede utilizar la siguiente expresión (ESRA 2000) :

(3)

being = The meridian longitude of the official hourly reference. = Local meridian longitude.

229.18 0.000075 0.001868cos 0.032077sin 0.014615cos2 0.040849sin 2ET

dJ

2 1 / 365.24dJ

Spatial reference system. Solar geometry.The dynamic of the Earth around the Sun needs the evaluation of certain geometric parameters which describes the position of the Sun respect to a certain location of the Earth to been able to do any calculation for that location.

Figure 1 Equation of time in minutes

The main parameters to determine the geometric relations of the Sun respect to an observer over a horizontal surface on the Earth are the following:

Latitude ( ). It is the angular position, North or South, respect to the equator, positive

in the North; .

Julian Day (Jd). It is defined as the day of the year (Jd=1~366). Being Jd=1 for the first of

January.

Declination ( ). It is defined as the angle between the equatorial plane and the

translation plane of the Earth, positive in the North; . The

declination ( ) can be obtained using the following approximation (in radians):

(4)

Hourly angle ( ). It is defined as the angular displacement of the Sun, East or West,

respect to the local meridian. It is due to the rotation of the Earth around its own axis.

It changes 15º per hour. In the morning it is positive, and after the Sun crosses the

local meridian, it is negative.

Solar Azimut (ψ). It is angle in the solar cenit between the meridian plane of the

observer and the plane of a big circle which goes through the cenit and the Sun. It is

measured positive in the East, negative in the West (near the South) and this way it

varies from 0º to ±180º

Solar cenit angle ( ). It can be defined as the incoming angle of the beam solar rays

over a horizontal ground surface where the observer is located. The cenital solar angle

is expressed using the following equation:

(5)

Solar elevation (α). It is defined as the angle between the point of the ground observer

and the position of the Sun, with the horizontal plane tangent to the ground surface.

This angle is complementary to the solar cenit angle (θz+α=π/2).

Figure 2 Solar angles

The cenital and azimutal angles can be calculated using the following equation:

(6)

(7)

Variation of extraterrestrial irradianceThe outgoing solar radiation and its spatial relation show and intensity approximately fixed out of the earth’s atmosphere. The value of the solar irradiance on a flat surface normal to the vector of the position of the Sun, is located in the upper limit of the earth’s atmosphere and it is known as the solar constant (ISC). The value accepted for this constant has changed on several measurements done during the last years. However, the value currently more accepted is 1367Wm-2. This value is accepted but the World Meteorological Organization (WMO 1981) and it has been estimated by the World Radiologic Center (WRC), from 25000 measurements done with several absolute cavity radiometers (ACR) (Fröhlich, C. & Brusa, R. W. 1981).

Due to the eccentricity which is described by the earth’s orbit in its translation movement, the distance Sun-Earth varies approximately 1.7% each year. This way, solar irradiance which is received in the upper limit of the earth’s atmosphere is not constant, and it is affected by the Law of the Square of the distance, obtaining a seasonal variation of ±3.3%. The eccentricity of the earth’s orbit () can be obtained using the following expression:

(8)

where Γ represents daily angle defined previously.

The energy which is received in a surface normal to the direction of the vector of the position of the Sun can be obtained in function of the eccentricity. This values is known as the

extraterrestrial solar irradiance ( ) and it represents the seasonal variation of the solar constant, due to the variation of the variation of the distance Sun-Earth with respect with the mean value (AU).

(9)

Using the last expression, we can calculate the irradiance received in a flat surface tangent to

the ground surface in the upper limit of the atmosphere ( ). The value can be obtained using the following expression:

(10)

The last relation establishes the upper limit of the irradiance, which can be received in a horizontal plane in the ground surface.

Figure 3 Variation of extraterrestrial solar irradiance along the whole year

Solar radiation in the ground surfaceOnce solar radiation has gone through the atmosphere, beam solar irradiance (B) can be defined as the incoming power on a surface by unit of area corresponding to the angle limited by the solar disk, with taking into account the atmospheric diffusion. In a similar way, diffuse solar irradiance (D) corresponding to the power per area unit received by a surface from the atmospheric diffusion of solar irradiance and circumsolar zone (bright zone around the solar disk). Global irradiance (G) corresponds to the total power per unit area received by a surface and as a source of beam, diffuse and outgoing irradiance reflected by the environment (R). We can relate these magnitudes using the following expressions:

(11)

Clearsky index (kt)The clear sky index (kt) is defined as the quotient between the values of solar irradiance registered in the surface and the corresponding values of extraterrestrial solar irradiance, both for the same temporal period. The values of kt are obtained from solar irradiance, applying the following expression:

(12)

where G is the global irradiance which reaches the earth’s surface in a horizontal plane and I0 is the extraterrestrial irradiance over a horizontal surface, both for the same temporal period.

3. Interaction of solar radiation with the atmosphereThe solar irradiance is composed of different wavelengths. Commonly it is considered that the Sun emits as a black body, which temperature is 5760 K. The spectrum of the solar radiation which reaches the upper limit of the atmosphere is composed by the wavelengths () from 0.28 to 5 mm and it is divided commonly in three regions, ultraviolet (< 0.33 mm), visible (0.33 << 0.76 mm) and infrared (> 0.76 mm).

In the outer space there is no loss of radiation due to interaction with any material, only attenuation due to the Law of the Square of the distance. Nevertheless, after going through the atmosphere, the solar radiation suffers different processes of reflection, attenuation and dispersion as a result of the interaction with the different atmospheric components: aerosols, clouds, ozone molecules, carbon dioxide, oxygen, water vapor, etc. The main atmospheric effects on solar irradiance are the following:

Diminution of the energy which is received on the ground level due to the interaction with the atmospheric components.

Modification of the spectral characteristics of the solar irradiance. Modification of the special distribution of the solar irradiance which is received in the

ground surface.

The reflection of the solar irradiance is due mainly to the interaction with cloud and floating particles. The absorption of solar irradiance, due to atmospheric components, is responsible of decrease of approximately 20% of the coming solar energy. The main components which produce the attenuation are the ozone, the water vapor and carbon dioxide.

Scattering produces the attenuation of solar irradiance which reaches the upper limit of the earth’s atmosphere, making it to be distributed in all directions. The atmospheric components which produce this effect are water vapor, aerosols and molecular components. The scattering effect is related directly with the size of the constituent and its concentration. The mediums size of the particle is defined using the non-dimensional coefficient Θ:

(13)

being q the size of the particle and λ the incoming wavelength. It is possible to distinguish three types of diffusion:

Rayleigh diffusion. It is produced when the wavelength of solar irradiance is higher

than the dimension of the responsible particles ( ). This process is produced by nitrogen and oxygen molecules. Rayleigh scattering is proportional to λ-4, this way, it affects to short-wavelengths and it is responsible of the color blue of the sky. This phenomenon is produced mainly the higher layers of the atmosphere.

Mie diffusion. It is produced when the wavelength of the solar irradiance has the same

order of magnitude as molecules which originate the effect ( ). The main cause is due water vapor, the dust and aerosols. It has effect on all wavelengths of the visible channel and it is produced in the lower layers of the atmosphere.

Non-selective diffusion. It is produced when the wavelength is lower than the

dimension of the particles ( ). This effect is caused mainly by the water drops which make up the clouds and fogs.

Integrating along all the radiative spectrum of the intensity or power of solar irradiance, solar energy which reaches the earth’s surface will depend on the thickness of earth’s layer which has to transpose the rays before reaching the earth’s surface, and on the concentration of the suspending particles and molecules which are on its way. The physical description of the interaction of solar energy with the atmosphere is not a trivial problem and it is broadly treated in current texts (Iqbal, M. 1983). An approximation, suitable for the resolution of the problem, is based on the parameterization of the main atmospheric characteristics depending on certain magnitudes which are described next.

Solar irradiance in its way through the atmospheric layer goes through a variable thickness. The relative optical mass of the air (m) quantifies the length of the optical way which solar radiation travels. This value can be estimated ignoring the earth’s curvature and supposing a uniform atmosphere with a refraction index equal to the unit, using the following expression (Kasten, F. & Young, A. T. 1989):

(A.14)

being the true solar altitude, that is, the solar altitude corrected by the atmospheric refraction effects, obtained using the following equation:

(A.15)

The non-dimensional coefficient (p/p0) is an atmospheric pressure correction due to the altitude above the level sea (z) of the site under study. The value of (p/p0) is calculated in a rough way using the following equation:

(A.16)

where z is the vertical coordinate referred to the sea level.

The influence of the different atmospheric components can be estimated using the comparison between the optical thickness, registered in a particular instant, and the theoretical thickness, for a totally cloudless and dry sky. This value is known as .From the relative optical air mass of the air (m), can be defined.

The influence of the different atmospheric constituents can be estimated using the following comparison between the optical thickness, registered in a certain instant, and the theoretical

depth, for a certain clear and dry sky. This value is known as the Rayleigh optical thickness (). Using the relative optical mass of the air, the Rayleigh optical thickness can be obtained (Kasten, F. 1996;Louche, A., Notton, G., Poggi, P., & Simonnot, G. 1991):

(A.17)

Bourguer-Lambert-Beer law

The equation which defines the attenuation of electromagnetic radiation when going through a certain medium is defined by the Bourguer-Lambert- Beer. This, applied to spectral solar irradiance going through the atmosphere can be expressed using the following equation:

(18)

Where In() : normal irradiance in the surface of the Earth. I0():extraterrestrial irradiance in the limit of the atmosphere. k(): total optical thickness in cenital direction. m: relative optical mass of the air. (): total espectral transmitance

Clear sky model European solar radiation atlas (ESRA)Clear sky models are of great usefulness in many solar energy applications. A clear sky model is basically a parameterization to estimate solar irradiance integrated in all spectrum for a cloudless sky day. For overcast or partly cloudy skies the estimation of solar radiation using physical models is very complex, because it is needed the knowledge of the morphology of the cloud cover.

ESRA model is a parameterization which only requires the Linke Turbidity to estimate beam radiation. There are Linke Turbidity tables for the whole World which allows the application of this clear sky model with certain precision.

Linke turbidity coefficient

The Linke turbidity coefficient (TL) is a simple parameter which expresses the attenuation of solar radiation due to the effect of aerosols and water vapor. It represents the level of transparency of the atmosphere and quantifies the effects of absorption and spreading produced by the atmosphere on solar radiation. It was created by Linke in 1922. It proposes to express optical thickness of the cloudless atmosphere, as the product of two terms, the optical thickness of an atmosphere free of aerosols and water vapor and Linke Turbidity. Linke defined the optical thickness integrated for an ideal atmosphere

The next table shows common values of the index for different atmospheric conditions.

Tabla 1. Frequent values of Linke turbidity (ESRA 2000)

Types of atmospheres TL

Very clear (Cloudless, low level of humidity) ~ 2Clear and dry ~ 3Wet and warm 4 ~ 6With pollution > 6

This value can be obtained using experimental measurements, although due to the lack of them, it can be obtained from empirical fittings. Although currently the definition of Linke turbidity has not been change, its values have been modified due to the improvement of the instrumentation and the accuracy of the measurements.

4. Solar radiation estimated from satellite

Among the possible different approaches to characterize the solar resource of a given specific site they can be pointed out the following:

Data from nearby stations. This option can be useful for relatively flat terrains and when distances are less than 10 km far from the site. In the case of complex terrain or longer distances the use of radiation data from other geographical points is absolutely inappropriate.

Interpolation of surrounding measurements. This approach can be only used for areas with a high density of stations and for average distances between stations of about 20-50 km.

Solar radiation estimation from satellite images is currently the most suitable approach. It supplies the best information on the spatial distribution of the solar radiation and it is a methodology clearly accepted by the scientific community and with a high degree of maturity. In this regard, it is worth to mention that BSRN (Baseline Surface Radiation Network) has among its objectives the improvement of methods for deriving solar radiation from satellite images, and also the Experts Working Group of Task 36 of the Solar Heating and Cooling Implement Agreement of IEA (International Energy Agency) focuses on solar radiation knowledge from satellite images.

Solar radiation derived from satellite images is based upon the establishment of a functional relationship between the solar irradiance at the Earth’s surface and the cloud index estimated from the satellite images. This relationship has been previously fitted by using high quality ground data, in such a manner that the solar irradiance-cloud index correlation can be extrapolated to any location of interest and solar radiation components can be calculated from the satellite observations for that point.

The method Heliosat-2

Various methods for deriving solar radiation from satellite images were developed during ’80. One of them was the method Heliosat-1 (Cano, D., Monget, J. M., Albussion, M., Guillard, H., Regas, N., & Wald, L. 1986) which could be one of the most accurate. The method Heliosat-2 (Rigollier, C., Lef+¿vre, M., & Wald, L. 2004) integrates the knowledge gained by these various exploitations of the original method and its varieties in a coherent and thorough way.

Both versions are based in the computation of a cloud index (n) from the comparison between the reflectance, or apparent albedo, observed by the spaceborne sensor (ρ), the apparent albedo of the brightest clouds (ρc) and the apparent albedo of the ground under clear skies (ρg):

For the estimation of radiation at ground level the method Heliosat-1 uses an empirical adjusted relation between the cloud index and the clearness index (KT). The new Heliosat-2 method uses a relation between the cloud index and the clear sky index (KC) defined as the ratio of the global irradiance (G) to the global irradiance under clear sky (Gclear).

The Heliosat-2 method deals with atmospheric and cloud extinction separately. As a first step the irradiance under clear skies is calculated by using the ESRA clear sky model (Rigollier, C., Bauer, O., & Wald, L. 2000), where the Linke turbidity factor is the only parameter required for the atmosphere composition. The following relationship between the cloud index and the clear sky index is then used for the global solar radiation determination (Rigollier, C. & Wald, L. 1998):

5. Measurement of solar radiation

Generally, meteorological instrumentation used to measure solar radiation are known as sola radiometers. All of them have a sensor which transforms the received radiant energy in a electrical signal easily recordable. As a function of the conversion process of the energy received it is possible to distinguish the following types of sensors:

Bimetallic. They are based on thermo mechanics properties of a bimetallic material which is modified depending on the incoming solar radiation.

Calorimeters. Solar energy is transformed in calorific energy and it induces a variation in the temperature of the sensor which allows the evaluation of the calorific flux and the quantity of incoming energy which produces it.

Thermoelectric. Based on the Seebeck effect, they respond to a high range of spectral radiation and its response is stable against variations of the temperature.

Photoelectric. They are based on the photovoltaic effect. They are cheap and have a high temporal response. Nevertheless, they are very sensible to variations of temperature and its spectral response is limited.

The World Meteorological Organization (WMO) propose a classification of the instrument, described in the next table, depending on the variable which they measure, it spectral response and field of vision, etc,…

6. Data quality assessment

The most reliable and comprehensive recommendations to make the measurement of solar radiation are established by the BSRN (Baseline surface Radiation Network) (McArthur, L. J. B. 1998). This institution recommends that the measurements of the three components have to be done with a configuration based on the use of a pyranometer to measure global horizontal solar irradiance, and one with a shading device for the diffuse irradiance. Finally, the direct normal irradiance must be measured with a pyrheliometer mounted on a solar tracker with two axes. Thus, by measuring the three components independently allows using procedures for quality assessment of the measurements based on the interrelationship between the three components. The main errors in the measurement of solar radiation can be grouped into the following categories: systematic errors of the measurement (such as a poor calibration of the equipment), errors by poorly maintenance (dirty sensor domes, or presence of obstacles), and or malfunctioning of the solar tracker. This report presents an analysis of the quality of the measurements of the three components of solar radiation based on the recommendations of the BSRN.

Tabla 2 Meteorological instruments to measure solar radiation

Name Variable measured Main use Angle of vision (sr)

Absolute pirheliometer

o Direct solar irradiance o Primary standard

5·10-3

Pirhelioemter o Direct solar irradiance o Secondary standard

o Measure

5·10-3 a 2.5·10-2

Spectral pirheliometer o Direct solar irradiance (high spectral wavelength)

o Measure 5·10-3 a 2.5·10-2

Solar fotometer o Radiación solar directa (banda espectral estrecha)

o Standardo Measure

1·10-3 a 1·10-2

Piranometer o Global radiationo Outgoing solar radiation

o Secondary standard

o Measure

2π

Espectral piranometer o Radiación global (banda espectral ancha)

o Measure 2π

Piranometer (RSR) o Global radiation o Secondary standard

o Measure

4π

Pirgeometer o Longwave radiation o Measure 2πPirradiometer o Total radiation o Scondary

Standardo Measure

2π

Pirradiometer (RSR) o Total radiation o Measure 4π

Before proceeding to the quality analysis of the measurements, we must change temporal reference of the data to true solar time. This change is performed by two corrections; the first one takes into account the difference in longitude between the meridian of the observer and the meridian of the temporal reference. The second includes various effects through the equation of time.

The verification of the temporal reference of the records is checked to have certain that solar irradiance is measured correctly between sunrise and sunset. This check is done visually and it uses a model of clear sky. Graphics are plotted each day for the following components: direct normal and global horizontal irradiance of clear sky, global horizontal and direct normal irradiance and diffuse measurements. To estimate the values of clear sky, the model used is the ESRA (European Solar Radiation Atlas) and the aerosol values used are the Linke Turbidity index provided by SODA (Beyer et al., 1996, Dumortier, 1999, ESRA 2000a, ESRA 2000b). The graphs of the solar irradiance components of ESRA clear sky model provide information of great interest. In addition, it allows the visualization of the moments of sunset and sunrise, besides we can compare the measurements with the values of the model in clear sky days. Accordingly, it is worth mentioning that the values of clear sky model have an uncertainty associated with the uncertainty of the Linke turbidity index fundamentally. However, the comparison is useful in terms of the profile shape of solar irradiance during the day as well as the relationship between direct and global irradiance for each day. Thus, both the shape and the relationship between the components are comparable in the days of clear sky conditions.

Once the temporal reference has been transformed to true solar time, measured data can be assessed using the following categories of filters levels:

1. Checking the time reference of the records;

2. Calculation of hourly values, daily and monthly averages;

3. Quality analysis with physical filters;

4. Quality analysis with cross component filters.

5. Quality analysis when the solar tracker is off under clear sky conditions.

The quality analysis with physical filters refers to the verification of the recorded values of the different components of the solar radiation, taking into account physical sense and not exceeding its value, therefore, limits physically possible. The next table presents the physical limits imposed on each component of solar radiation according to the recommendation of the BSRN.

Table 3: Physical limits of the solar radiation component

Parameter Minimum Flag for Minimum

Maximum

Global Irradiance (GHI) -42

Diffuse Irradiance (DIF) -- 700 W/m2

Diffuse Irradiance (DIF) -42

Direct Normal Irradiance (DNI)

-42

Direct Normal Irradiance (DNI)

-- DNI Clear Sky

ISC: Solar constant (1367 Wm-2), ɛ: eccentricity of the orbit, ϴz: zenith angle

The quality analysis of component cross filters is used to check that the measured data meets the interrelationship between the three components (GHI, DIF and DNI). Failure to pass these filters establishes a supposition that any of the components were poorly measured or that the solar tracker doesn’t points to the sun properly. The next table shows the conditions imposed on the cross components analysis.

Table 4: Conditions for the cross component

Parameter Conditions Limits

1 ± 8%

1 ± 15%

< 1.05

< 1.10

The next procedure relates the three components but using a more tight procedure. This test is based on the comparison of instruments which measure the same variables. The next table defines the limits for this procedure:

Table 5: Conditions for the second group of cross component filters

Parameter Lower Limit Upper Limit

B·cos z (G-D)-50 W/m-2 (G-D)+50 W/m-2

G-D B cos z - 50 W/m-2 B cos z + 50 W/m-2

The next procedure relates the diffuse component (DIF or D) and global extraterrestrial irradiance (Gext) using the diffuse index defined as:

Kd= DG ext

A higher limit of 0.6 is given to this filter and in case it is not fulfilled the filter is activated. The next procedure makes use of clearness index (Kt) which is defined as the quotient between grounds measured global solar irradiance (GHI or G) and extraterrestrial solar irradiance (Gext). In this procedure we establish the next condition for the activation of the filter:

If Kt is lower than 0.2 and D/G is lower than 0.9 then filter is activated

The next procedure uses the same variables as the last filter but with the following conditions:

If Kt is higher than 0.5 and D/G is higher than 0.8 then filter is activated

The last filter is named as the tracker off filter and it is used to detect when the solar tracker is not working correctly. First, the global solar irradiance (Sum SW) is estimated from measured diffuse solar irradiance and measured direct normal irradiance using the expression which relates the three components. Then the following condition is established using clear sky global irradiance (Gcclear) estimated with the model of ESRA and monthly climatological Linke Turbidity values from SODA:

For D > 50W/m2,

If (Sum SW)/Gcclear>0.85 and if D/(Sum SW) the tracker is not properly following the sun.

This last filter only works under clear sky conditions.

Besides this filters, we have estimated direct normal irradiance (Ibest) from measured GHI and DIF using the following expression:

Ibest=G(1−K d0)sin (γ )

Where Kd0 is defined as:

Kd0= DG

And γ is the angle of solar altitude.

7. Databases of solar radiation

The lack of measured radiometric data, the low spatial coverage and the temporal variability of the registered solar radiation data makes it difficult to characterize certain areas. This way, it is of great usefulness the availability of other radiometric data sources in different project phases like site selection in the prefeasibility phase or the beginning of a measurement campaign (installation of measurement instruments in certain locations). As a conclusion, the databases available on the internet (free or payment) are tool very useful in decision making. In the next paragraph we define the different radiometric data sources and present the worldwide databases available of sola irradiance.

SOURCES OF DATA

GROUND MEASURED DATA: There are several instruments to measure the components of solar radiation at different wavelengths. If instruments are correctly operated, calibrated and maintained this is the best source of information for site specific radiometric data. Due to uncertainties in the instruments, errors expected may be around 8% in terms of RMSE for instantaneous values.

SYNTETHIC GENERATED DATA: This data is generated to meet specific needs or certain conditions that may not be found in the original, real data. In the case that there is no measured data we can generate data artificially following general statistical properties of solar radiation, like monthly mean and auto-correlation function. There is no way to compare this data with real measured data because this data is artificially generated and doesn't take into account what happens in reality.

DATA ESTIMATED FROM SATELLITE: This is the best source of information to know accurately the value of long-term solar radiation in case there are no local measurements available. The errors for hourly, daily and monthly means are 12%, 10% and less than 5% respectively as stated before.

REANALYSIS: The reanalysis data set is a continually updating gridded data set representing the state of the Earth's atmosphere, incorporating observations and numerical weather prediction (NWP) model output. A meteorological reanalysis is a meteorological data

assimilation project which aims to assimilate historical observational data spanning an extended period, using a single consistent assimilation (or "analysis") scheme throughout implemented in the NWP model. The reanalysis data errors in terms of relative RMSE are higher than 30%.

WORLDWIDE DATABASES

1. Baseline Surface Radiation Network (BSRN)BSRN is a project of the Radiation Panel from the Global Energy and Water Cycle Experiment GEWEX under the umbrella of the World Climate Research Programme (WCRP) and as such is aimed at detecting important changes in the Earth's radiation field at the Earth's surface which may be related to climate changes.

The data are of primary importance in supporting the validation and confirmation of satellite and computer model estimates of these quantities. At a small number of stations (currently about 40) in contrasting climatic zones, covering a latitude range from 80°N to 90°S (see station maps ), solar and atmospheric radiation is measured with instruments of the highest available accuracy and with high time resolution (1 to 3 minutes).

The BSRN was recently (early 2004) designated as the global baseline network for surface radiation for the Global Climate Observing System (GCOS). The BSRN stations also contribute to the Global Atmospheric Watch (GAW).

Web address: http://www.bsrn.awi.de Source of the data: 63 stations with worldwide coverage. Comments: High quality data measured in single points. Access to data is free.

Figure 4 Running and planned BSRN stations up to September 2012

2. World radiation data centre (WRDC)The WRDC, located at the Main Geophysical Observatory in St. Petersburg, Russia, serves as a central depository for solar radiation data collected at over 1000 measurement sites throughout the world.

The WRDC was established in accordance with Resolution 31 of WMO Executive Committee XVIII in 1964. The WRDC centrally collects, archives and published radiometric data from the world to ensure the availability of these data for research by the international scientific community.

The WRDC archive contains the following measurements (not all observations are made at all sites):

Global solar radiation Diffuse solar radiation Downward atmospheric radiation Sunshine duration Direct solar radiation (hourly and instantaneous) Net total radiation Net terrestrial surface radiation (upward) Terrestrial surface radiation Reflected solar radiation Spectral radiation components (instantaneous fluxes)

At present, this online archive contains a subset of the data stored at the WRDC. As new measurements are received and processed, they are added to the archive. The archive currently contains all available data from 1964-1993.

Web address: http://wrdc-mgo.nrel.gov Source of the data: World radiometric data. Comments: provides data from 1964. Access to data is free.

3. MeteonormMeteonorm is a comprehensive meteorological reference. It gives access to meteorological data for solar applications, system design and a wide range of other applications for any location in the world. meteonorm addresses engineers, architects, teachers, planners and anyone interested in solar energy and climatology.

Meteonorm includes 8300 meteorological stations worldwide. Numerous global and regional databases have been examined for their reliability and combined in meteonorm. The most important data sources are the GEBA (Global Energy Balance Archive), the World Meteorological Organization (WMO/OMM) Climatological Normals 1961—1990 and the Swiss database compiled by MeteoSwiss.

In meteonorm, the climatological periods 1961—1990 and 2000—2009 are available for temperature, humidity, wind speed and precipitation. The climatological periods 1981—1990 and 1986—2005 are available for solar radiation.

Monthly climatological (long term) means are included for the following eight parameters:

global radiation ambient air temperature humidity precipitation, days with precipitation wind speed and direction sunshine duration

Web address: http://www.meteonorm.com Source of measured data: Data from 8300 climatological stations. The data belongs to

GEBA (Global Energy Balance Archive), WMO (World Meteorological Organization) and Swiss data base from MeteoSwiss.

Satellite data: Yes. Where ground measured data is unavailable data estimated from satellite with a resolution of 250 km is used.

Comments: Software of payment.

Figure 5 Ground radiometric stations used in Meteonorm in Europe and India

4. SSE-NASA (Surface Meteorology and Solar Energy)

NASA, through its' Science Mission Directorate, has long supported satellite systems and research providing data important to the study of climate and climate processes. These data include long-term estimates of meteorological quantities and surface solar energy fluxes.

These satellite and modeled based products have been shown to be accurate enough to provide reliable solar and meteorological resource data over regions where surface measurements are sparse or nonexistent, and offer two unique features - the data is global and, in general, contiguous in time. These two important characteristics, however, tend to generate very large data archives which can be intimidating for commercial users, particularly new users with little experience or resources to explore these large data sets. Moreover the data products contained in the various NASA archives are often in formats that present challenges to new users. To foster the commercial use of the global solar and meteorological data, NASA supported, and continues to support, the development of the Surface meteorology and Solar Energy (SSE) dataset that has been formulated specifically for photovoltaic and renewable energy system design needs. Of equal importance is the access to these data; to this end the SSE parameters are available via user-friendly web-based applications founded on user needs.

The original SSE data-delivery web site, intended to provide easy access to parameters needed in the renewable energy industry (e.g. solar and wind energy), was released to the public in 1997. The solar and meteorological data contained in this first release was based on the 1993 NASA/World Climate Research Program Version 1.1 Surface Radiation Budget (SRB) science data and TOVS data from the International Satellite Cloud Climatology Project (ISCCP). This initial design approach proved to be of limited value because of the use of "traditional" scientific terminology that was not compatible with terminology/parameters used in the energy industry to design renewable energy power systems. After consultation with industry, SSE Release 2 was made public in 1999 with parameters specifically tailored to the needs of the renewable energy community. Subsequent releases of SSE have continued to build upon an interactive dialog with potential customers resulting in updated parameters using revised NASA data as well as inclusion of new parameters as requested by the user community.

The Prediction of Worldwide Energy Resource (POWER) project was initiated in 2003 both to improve subsequent releases of SSE, and to create new datasets applicable to other industries from new satellite observations and the accompanying results from forecast modeling. POWER currently encompasses the SSE data set, tailored for the renewable energy industry, as well as parameters tailored for the sustainable buildings community, and the bio-energy/agricultural industries. In general, the underlying data behind the parameters used by each of these industries is the same - solar radiation and meteorology, including surface and air temperatures, moisture, and winds.

Web address: http://eosweb.larc.nasa.gov/sse Source of the data: Estimations from satellite with a resolution of 100km. Worldwide

coverage. Comments: Free access.

5. IrSOLaV (www.solarexplorer.info)The methodology of IrSOLaV uses two main inputs to compute hourly solar irradiance: the geostationary satellite images and the information about the attenuating properties of the atmosphere. The former consists of one image per hour offering information related with the cloud cover characteristics. The latter is basically information on the daily Linke turbidity which is a very representative parameter to model the attenuating processes which affects solar radiation on its path through the atmosphere, mainly daily values of aerosol optical depth and water vapor column from Moderate Resolution Imaging Spectroradiometer satellite (MODIS).

Solar radiation estimation from satellite images offered is made from a modified version of the renowned model Heliosat-3, developed and validated by CIEMAT with more than thirty radiometric stations in the Iberian Peninsula. Over this first development, IrSOLaV has generated a tool fully operational which is applied on a database of satellite images available with IrSOLaV (temporal and spatial resolution of the data depends on the satellite covering the region under study). It is worthwhile to point out that tuning-up and fitting of the original methodology in different locations of the World have been performed and validated with local data from radiometric stations installed in the region of interest. This way, it may be considered that the treatment of the information from satellite images offered by IrSOLaV is an exclusive service.

Even though the different research groups working in this field are making use of the same core methodologies, there are several characteristics that differ depending on the specific objectives pursued. Therefore, the main differences between the IrSOLaV/CIEMAT and others, like the ones applied by PVGis or Helioclim are:

Selection of the working window. The correlations developed by IrSOLaV/CIEMAT are focused on the Iberian Peninsula, and in particular in Spain, making use of 30 equidistant meteo-stations in this territory. However the other groups use stations distributed among all Europe and the resulting relations are applied to all the territory.

Filtering of images and terrestrial data. Images and data used for the fitting and relations are thoroughly filtered with procedures developed specifically for this purpose.

Selection of albedo for clear sky. The algorithm used for selection of clear sky albedos provides a daily sequence that is different for every year, however the other methodologies use a unique monthly value.

Introduction of characteristic variables. The relation developed by IrSOLaV/CIEMAT includes new variables characterizing the climatology of the site and the geographical location, with a significant improvement of the results obtained for global and direct solar radiation.

The uncertainty of the estimation comparing with hourly ground pyranometric measurements is expressed in terms of the relative root mean squared error (RMSE). Different assessments and benchmarking tests can been found at the available literature concerning the use of satellite images (Meteosat and GOES) on different geographic sites and using different models [Pinker y Ewing, 1985; Zelenka et al., 1999; Pereira et al., 2003; Rigollier et al., 2004; Lefevre et

al., 2007]. The uncertainty for hourly values is estimated around 20-25% RMSE and in a daily basis the uncertainty of the models used to be about 13-17%. It is important to mention here the contribution given by Zelenka in terms of distributing the origin of this error, concluding that 12-13% is produced by the methodology itself converting satellite information into radiation data and a relevant fraction of 7-10% because of the uncertainty of the ground measurements used for the comparison. In addition Zelenka estimates that the error of using nearby ground stations beyond 5 km reaches 15%. Because of that his conclusion is that the use of hourly data from satellite images is more accurate than using information from nearby stations located more than 5 km far from the site.

The IrSOLaV methodology is based on the work developed in CIEMAT by the group of Solar Radiation Studies. The model has been assessed for about 30 Spanish sites with the following uncertainty data for global horizontal irradiance:

About 12% RMSE for hourly values Less than 10% for daily values Less than 5% for annual and monthly means

The model has been modified for a better estimation of solar radiation with clear sky, leading to an important improvement in the accuracy of the model [Polo, 2009; Polo et al., 2009b].

Web address: http://www.irsolav.com and http://www.solarexplorer.info Source of the data: Satellite data. Comments: Payment data.

6. 3TIERSatellite-based time series of reflected sunlight are used to determine a cloud index time series for every land surface worldwide. A satellite based daily snow cover dataset is use to aid in distinguishing snow from clouds. In addition, the global horizontal clearsky radiation is modeled based on the surface elevation of each location, the local time, and the measure of turbidity in the atmosphere. 3Tier opted to use a satellite based, monthly time series of aersol optical depth and water vapor derived from the MODIS satellite. This dataset was combined with another turbidity dataset that includes both surface and satellite observations to provide turbidity measure that spans the period of our satellite dataset and is complete for all land surfaces. The cloud index n and the clear sky irradiance are then combined to model the global horizontal irradiance. This component of the process is calibrated for each satellite based on a set of high-quality surface observations. The global horizontal irradiance estimates are then combined with other inputs to evaluate the other irradiance components (diffuse and direct).

Web address: http://www.3tier.com Source of the data: Satellite data. Comments: Payment data.

7. SOLEMISolar Energy Mining (SOLEMI) is a service set up by DLR providing high-quality irradiance data for the solar energy community. The service is mainly based on METEOSAT-data with a nominal resolution of 2.5 km in the visible channel and 5 km in the infrared channel and half-hourly temporal resolution. Solar radiation maps and hourly time series will be available for almost half of the Earth's surface: the field of view of METEOSAT-7 placed at 0 longitude and additionally the field of view of METEOSAT-5 placed at 63E over the Indian Ocean will be provided. The METEOSAT-5 data cover such promising solar energy regions as India, Pakistan or China. Other very promising countries at the Saudi Arabian Peninsula may also be analyzed by METEOSAT-7 but METEOSAT-5 provides better viewing conditions. Fast access to the full METEOSAT-7 disc at full resolution is also a novelty. SOLEMI will provide fast access to quality-controlled homogenized long-term time series of large regions within the view of both satellites. The operational high performance computing environment DIMS (Data and Information Management System) at DLR-DFD (German Remote Sensing Data Center) allows for rapid processing and distribution of the products to the customers.

Web address: http://www.solemi.de Source of the data: Satellite data. Comments: Payment data.

8. GeomodelThe irradiance components are the results of a five steps process: a multi-spectral analysis classifies the pixels, the lower boundary (LB) evaluation is done for each time slot, a spatial variability is introduced for the upper boundary (UP) and the cloud index definition, the Solis clears sky model is used as normalization, and a terrain disaggregation is finally applied.

Four MSG spectral channels are used in a classification scheme to distinguish clouds from snow and no-snow cloud-free situations. Prior to the classification, calibrated pixel values were transformed to three indices: normalized difference snow index (Ruyter de Wildt M., G.Siez, & A.Gruen 2007), cloud index (Derrien M. & H.Gleau 2005), and temporal variability index. Exploiting the potential of MSG spectral data for snow classification removed the need of additional ancillary snow data and allowed using spectral cloud index information in cases of complex conditions such as clouds over high albedo snow areas.

In the original approach by Perez (Perez, R., Ineichen, P., Moore, K., Kmiecik, M., Chain, C., George, R. et al. 2002), the identification of surface pseudo-albedo is based on the use of a lower bound (LB), representing cloudless situations. This approach neglects diurnal variability of LB that is later corrected by a statistical approach. Instead of identifying one value per day, LB is represented by smooth 2-dimensional surface (in day and time slot dimensions) that reflects diurnal and seasonal changes in LB and reduces probability of in cloudless situation.

Overcast conditions represented in the original Perez model by a fixed Upper Bound (UB) value were updated to account for spatial variability which is important especially in the higher latitudes. Calculation of cloud index was extended by incorporation of snow classification results.

The broadband simplified version of Solis model (Ineichen 2008a) was implemented. As input of this model, the climatology values from the NAVAP water vapor database (Remund 2008) and Atmospheric Optical Depth data by (Remund 2008) assimilated with Aeronet and Aerocom datasets are used.

Simplified Solis model was also implemented into the global to beam Dirindex algorithms to calculate Direct Normal irradiance component (Perez 1992, Ineichen 2008c). Diffuse irradiance for inclined surfaces is calculated by updated Perez model (1987).

Processing chain of the model includes post-processing terrain disaggregation algorithm based on the approach by (Ruiz-Arias, J. A., T.Cebecauer, J.Tovar-Pescador, & M.Súri 2010). The disaggregation is limited to shadowing effect only, as it represents most significant local effect of terrain. The algorithm uses local terrain horizon information with spatial resolution of 100 m. Direct and circumsolar diffuse components of global irradiance were corrected for terrain shadowing.

Web address: http://www.geomodel.eu and http://www.solargis.info Source of the data: Satellite data. Comments: Payment data.

8. Using of solar radiation data for CSP technologies

The most important parameter that affects performance of CSP plants is DNI. We have to pay attention on the yearly value of DNI, the dynamic of the cloud transient and the DNI frequency distribution. CSP plants need 10-minute and hourly values to estimate their energy yield. Besides, these plants are designed to operate within a specific range of DNI values. If instantaneous DNI values are outside this range, the plant could not utilize such DNI values and hence energy is lost. The design range of DNI values for which a plant could operate are generally determined from long-term frequency distribution of DNI. Frequency distribution of DNI describes the number of occurrences of DNI values which are expected to be received for a specific location. Usually, DNI frequency distribution follows properties of normal distribution. It has been demonstrated that for years with the same DNI annual averages differences in DNI frequency distribution could make the annual energy yield to be different, with differences from -8% to +9%.

9. References

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Derrien M. & H.Gleau 2005. MSG/SEVIRI cloud mask and type from SAFNWEC. International Journal of Remote Sensing, 26: 4707-4732.

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Fröhlich, C. & Brusa, R. W. 1981. Solar radiation and its variation in time. Sol.Phys., 74: 209-215.

Iqbal, M. 1983. An introduction to solar radiation. Toronto (Canada): Academic Press Canada.

Kasten, F. 1996. The linke turbidity factor based on improved values of the integral Rayleigh optical thickness. Solar Energy, 56(3): 239-244.

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Louche, A., Notton, G., Poggi, P., & Simonnot, G. 1991. Correlations for direct normal and global horizontal irradiation on a French Mediterranean site. Solar Energy, 46(4): 261-266.

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Perez, R., Ineichen, P., Moore, K., Kmiecik, M., Chain, C., George, R., & Vignola, F. 2002. A new operational model for satellite-derived irradiances: description and validation. Solar Energy, 73: 307-317.

Rigollier, C., Bauer, O., & Wald, L. 2000. On the clear sky model of the ESRA -- European Solar Radiation Atlas -- with respect to the heliosat method. Solar Energy, 68(1): 33-48.

Rigollier, C., Lef+¿vre, M., & Wald, L. 2004. The method Heliosat-2 for deriving shortwave solar radiation from satellite images. Solar Energy, 77(2): 159-169.

Rigollier, C. & Wald, L. Using METEOSAT images to map the solar radiation: improvement of the Heliosat method. 432-433. 1998. Paris (France), 9th Conference on Satellite Meteorology and Oceanography. 25-5-1998. Ref Type: Conference Proceeding

Ruiz-Arias, J. A., T.Cebecauer, J.Tovar-Pescador, & M.Súri 2010. Spatial disaggregation of satellite-derived irradiance using a high resolution digital elevation model. Solar Energy.

Ruyter de Wildt M., G.Siez, & A.Gruen 2007. Operational snow mapping using multitemporal Meteosat SEVIRI imagery. Remote Sensing of Environment, 109: 29-41.

WMO 1981. Annex: World maps of relative global radiation. Technical note Nº 172. Meteorological aspects of the utilization of solar radiation as an energy source: 25-27. Geneva (Switzerland): Secretariat of the World Meteorological Organization.