Assessment and evaluation of solar resources adb course
Assessment and Evaluation of Solar Resources Luis Martín Pomares IrSOLaV
ContentsAssessment and Evaluation of Solar Resources ............................................................................ 11. Introduction .......................................................................................................................... 32. Solar Geometry ..................................................................................................................... 33. Interaction of solar radiation with the atmosphere ............................................................. 94. Solar radiation estimated from satellite ............................................................................. 125. Measurement of solar radiation ......................................................................................... 146. Data quality assessment...................................................................................................... 147. Databases of solar radiation ............................................................................................... 188. Using of solar radiation data for CSP technologies ............................................................. 279. References ........................................................................................................................... 27
1. IntroductionThe solar radiation is a meteorological variable measured only in few measurement stationsand during short and, on most occasions, discontinuous periods of times. The lack of reliableinformation on solar radiation, together with the spatial variability that it presents, leads to thefact that developers do not find appropriate historical databases with information available onsolar resource for concrete sites. This lack provokes in turn serious difficulties at the momentof projecting or evaluating solar power systems. The next paragraphs are a summary ofconcepts and tools which can help to the solar community to evaluate their projects. 2. Solar GeometryThe trajectory which describes the sun in the vault of heavenvaries for each day of the year.This way, the modeling and the solar irradiance measurements need to know with precisionthe 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 masswhere thermonuclear reactions are produced which transform the hydrogen nucleus in heliumnucleus. Due to these nuclear reactions, the temperature in the surface varies between 4700and 7500 K, and its emissions belong to the spectrum of a black body.Supposing that thetemperature and the Sun’s radiation spectrum are constant, the quantity of the energy whichreaches the surface of the earth atmosphere can be established analytically from the relativepositions of the Sun and the Earth. Due to the fact that the Earth has also a movement ofrotation in its own axis and another of translation around the Sun, it is necessary to definepreviously a spatial and temporal reference system which places the Sun and the Earth, due tothe 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 thesame local meridian. The longitude of the solar day is not constant, due to the fact that itchanges along the year because the following reasons: ThedistanceSun-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 solartime 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:ET 229.18 0.000075 0.001868cos 0.032077sin 0.014615cos2 0.040849sin 2 (1)whereΓrepresents the daily angle; it is depenant of the Julian day ( J d ) and can be calcualted,in radians, as: 2 J d 1 / 365.24 (2)In certain occasions, it can be necessary a third temporal correction ( C h ) due to the hourlychanges to save energyas a policy of the country (in Spain C h =1 in winter and in summer C h=2). Thisway, para transformar el tiempo solar verdadero en hora decimal, se puede utilizar lasiguiente expresión (ESRA 2000) : TSV TLM of loc /15 ET / 60 Ch (3)being of = The meridian longitude of the official hourly reference. loc = Local meridianlongitude.Spatial reference system.Solar geometry.The dynamic of the Earth around the Sun needs the evaluation of certain geometricparameters which describes the position of the Sun respect to a certain location of the Earth tobeen able to do any calculation for that location.
Figure 1 Equation of time in minutesThe main parameters to determine the geometric relations of the Sun respect to an observerover 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; 90 0 90 0 . Julian Day (Jd). It is defined as the day of the year (Jd=1~366). Being Jd=1 forthefirst of January. Declination ( ). It is defined as the angle between the equatorial plane and the translation plane of the Earth, positive in the North; 23.450 23.450 . The declination ( ) can be obtained using the following approximation (in radians): 23.45sin 360 284 J d / 365 180 (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 ( z ). 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: cos z sin sin cos cos cos sin (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 anglesThe cenital and azimutal angles can be calculated using the following equation: 1 cos sin sin cos cos cos /2 z (6) 1 1 cos cos z sin sin / sin z cos sin cos sin / sin z (7)
Variation of extraterrestrial irradianceThe outgoing solar radiation and its spatial relation show and intensity approximately fixed outof the earth’s atmosphere. The value of the solar irradiance on a flat surface normal to thevector of the position of the Sun, is located in the upper limit of the earth’s atmosphere and itis known as the solar constant (ISC). The value accepted for this constant has changed onseveral measurements done during the last years. However, the value currently more acceptedis 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 measurementsdone 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, thedistance Sun-Earth varies approximately 1.7% each year. This way, solar irradiance which isreceived in the upper limit of the earth’s atmosphere is not constant, and it is affected by theLaw of the Square of the distance, obtaining a seasonal variation of ±3.3%.The eccentricity ofthe earth’s orbit ( ) can be obtained using the following expression: 1.000110 0.034221 cos 0.001280 sin 0.000719 cos 2 0.000077 sin 2 (8)whereΓ represents daily angle defined previously.The energy which is received in a surface normal to the direction of the vector of the positionof the Sun can be obtained in function of the eccentricity. This values is known as theextraterrestrial solar irradiance( I 0n ) and it represents the seasonal variation of the solarconstant, due to the variation of the variation of the distance Sun-Earth with respect with themean value (AU). I 0n I CS (9)Using the last expression, we can calculate the irradiance received in a flat surface tangent tothe ground surface in the upper limit of the atmosphere ( I 0 ). The value I 0 can be obtainedusing the following expression: I0 I CS cos z (10)
The last relation establishes the upper limit of the irradiance, which can be received in ahorizontal plane in the ground surface. Figure 3 Variation of extraterrestrial solar irradiance along the whole yearSolar radiation in the ground surfaceOnce solar radiation has gone through the atmosphere, beam solar irradiance (B) can bedefined as the incoming power on a surface by unit of area corresponding to the angle limitedby the solar disk, with taking into account the atmospheric diffusion. In a similar way, diffusesolar irradiance (D) corresponding to the power per area unit received by a surface from theatmospheric diffusion of solar irradiance and circumsolar zone (bright zone around the solardisk). Global irradiance (G) corresponds to the total power per unit area received by a surfaceand as a source of beam, diffuse and outgoing irradiance reflected by the environment (R). Wecan relate these magnitudes using the following expressions: G B D R (11)Clearsky index (kt)The clear sky index (kt) is defined as the quotient between the values of solar irradianceregistered in the surface and the corresponding values of extraterrestrial solar irradiance, bothfor the same temporal period. The values of kt are obtained from solar irradiance, applying thefollowing expression: G kt (12) I0
whereG is the global irradiance which reaches the earth’s surface in a horizontal plane and I0 isthe 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 theSun emits as a black body, which temperature is 5760 K. The spectrum of the solar radiationwhich reaches the upper limit of the atmosphere is composed by the wavelengths ( ) from0.28 to 5 m and it is divided commonly in three regions, ultraviolet ( < 0.33 m), visible (0.33< < 0.76 m) and infrared ( > 0.76 m).In the outer space there is no loss of radiation due to interaction with any material, onlyattenuation due to the Law of the Square of the distance. Nevertheless, after going throughthe atmosphere, the solar radiation suffers different processes of reflection, attenuation anddispersion as a result of the interaction with the different atmospheric components: aerosols,clouds, ozone molecules, carbon dioxide, oxygen, water vapor, etc. The main atmosphericeffects 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 floatingparticles. The absorption of solar irradiance, due to atmospheric components, is responsible ofdecrease of approximately 20% of the coming solar energy. The main components whichproduce the attenuation are the ozone, the water vapor and carbon dioxide.Scattering produces the attenuation of solar irradiance which reaches the upper limit of theearth’s atmosphere, making it to be distributed in all directions. The atmospheric componentswhich produce this effect are water vapor, aerosols and molecular components. The scatteringeffect is related directly with the size of the constituent and its concentration. The mediumssize of the particle is defined using the non-dimensional coefficient Θ: 1 2 q (13)beingq the size of the particle and λthe incoming wavelength. It is possible to distinguish threetypes of diffusion: Rayleigh diffusion. It is produced when the wavelength of solar irradiance is higher than the dimension of theresponsible 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 ( 50 ). 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, solarenergy which reaches the earth’s surface will depend on the thickness of earth’s layer whichhas to transpose the rays before reaching the earth’s surface, and on the concentration of thesuspending particles and molecules which are on its way. The physical description of theinteraction of solar energy with the atmosphere is not a trivial problem and it is broadlytreated in current texts(Iqbal, M. 1983). An approximation, suitable for the resolution of theproblem, is based on the parameterization of the main atmospheric characteristics dependingon 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 solarradiation travels. This value can be estimated ignoring the earth’s curvature and supposing auniform atmosphere with a refraction index equal to the unit, using the following expression(Kasten, F. & Young, A. T. 1989): 1.6364 1 * * m p / p0 sin 0.50572 57.29578 6.07995 (A.14) *being the true solar altitude, that is, the solar altitude corrected by the atmosphericrefraction effects, obtained using the following equation: 2 * 0.1594 1.1230 0.065656 0.061359 1 28.9344 277.3971 2 (A.15)The non-dimensional coefficient (p/p0) is an atmospheric pressure correction due to thealtitude above the level sea (z) of the site under study. The value of (p/p0) is calculated in arough way using the following equation: p / p0 exp z / 8400 (A.16)
wherezis the vertical coordinatereferred to the sea level.The influence of the different atmospheric components can be estimated using thecomparison between the optical thickness, registered in a particular instant, and thetheoretical thickness, for a totally cloudless and dry sky. This value is known as .From therelative optical air mass of the air (m), can be defined.The influence of the different atmospheric constituents can be estimated using the followingcomparison between the optical thickness, registered in a certain instant, and the theoreticaldepth, for a certain clear and dry sky. This value is known as the Rayleigh optical thickness ( r). 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): 1 6.6296 1.7513m 0.1202m2 0.0065m3 0.00013m4 para m 20 r (m) = 1 (A.17) 10.4 0.718 m para m 20Bourguer-Lambert-Beer lawThe equation which defines the attenuation of electromagnetic radiation when going througha certain medium is defined by the Bourguer-Lambert- Beer. This, applied to spectral solarirradiance going through the atmosphere can be expressed using the following equation: In I0 exp k m I0 (18)WhereIn( ) : normal irradiance in the surface of the Earth. I0( ):extraterrestrial irradiance inthe limit of the atmosphere. k( ): total optical thickness in cenital direction. m: relative opticalmass of the air. ( ): total espectraltransmitanceClear sky model European solar radiation atlas (ESRA)Clear sky models are of great usefulness in many solar energy applications. A clear sky model isbasically a parameterization to estimate solar irradiance integrated in all spectrum for acloudless sky day. For overcast or partly cloudy skies the estimation of solar radiation usingphysical models is very complex, because it is needed the knowledge of the morphology of thecloud cover.ESRA model is a parameterization which only requires the Linke Turbidity to estimate beamradiation. There are Linke Turbidity tables for the whole World which allows the application ofthis clear sky model with certain precision.
Linke turbidity coefficientThe Linke turbidity coefficient (TL) is a simple parameter which expresses the attenuation ofsolar radiation due to the effect of aerosols and water vapor. It represents the level oftransparency of the atmosphere and quantifies the effects of absorption and spreadingproduced by the atmosphere on solar radiation. It was created by Linke in 1922. It proposes toexpress optical thickness of the cloudless atmosphere, as the product of two terms, the opticalthickness of an atmosphere free of aerosols and water vapor and Linke Turbidity. Linke definedthe optical thickness integrated for an ideal atmosphereThe next table shows common values of the index for different atmospheric conditions. Tabla1.Frequent values of Linke turbidity(ESRA 2000) Types of atmospheres TL Very clear (Cloudless, low level of humidity) ~2 Clear and dry ~3 Wet and warm 4~6 Withpollution >6This value can be obtained using experimental measurements, although due to the lack ofthem, it can be obtained from empirical fittings. Although currently the definition of Linketurbidity has not been change, its values have been modified due to the improvement of theinstrumentation and the accuracy of the measurements. 4. Solar radiation estimated from satelliteAmong the possible different approaches to characterize the solar resource of a given specificsite 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. Itsupplies the best information on the spatial distribution of the solar radiation and it is amethodology 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) hasamong its objectives the improvement of methods for deriving solar radiation from satelliteimages, and also the Experts Working Group of Task 36 of the Solar Heating and CoolingImplement Agreement of IEA (International Energy Agency) focuses on solar radiationknowledge from satellite images.Solar radiation derived from satellite images is based upon the establishment of a functionalrelationship between the solar irradiance at the Earth’s surface and the cloud index estimatedfrom the satellite images. This relationship has been previously fitted by using high qualityground data, in such a manner that the solar irradiance-cloud index correlation can beextrapolated to any location of interest and solar radiation components can be calculated fromthe satellite observations for that point.The method Heliosat-2Various 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 variousexploitations 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 betweenthe reflectance, or apparent albedo, observed by the spaceborne sensor (ρ), the apparentalbedo of the brightest clouds (ρc) and the apparent albedo of the ground under clear skies(ρg): 1 n g c gFor the estimation of radiation at ground level the method Heliosat-1 uses an empiricaladjusted relation between the cloud index and the clearness index (KT). The new Heliosat-2method uses a relation between the cloud index and the clear sky index (KC) defined as theratio of the global irradiance (G) to the global irradiance under clear sky (Gclear). G KC GclearThe Heliosat-2 method deals with atmospheric and cloud extinction separately. As a first stepthe 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 theclear sky index is then used for the global solar radiation determination(Rigollier, C. & Wald, L.1998): n 0.2 , KC 1.2 0.2 n 0.8 , KC 1 n 0.8 n 1.1 , KC 2.0667 3.6667 n 1.6667 n 2 1.1 n , KC 0.05 5. Measurement of solar radiationGenerally, meteorological instrumentation used to measure solar radiation are known as solaradiometers. All of them have a sensor which transforms the received radiant energy in aelectrical signal easily recordable. As a function of the conversion process of the energyreceived 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 spectralresponse and field of vision, etc,… 6. Data quality assessmentThe most reliable and comprehensive recommendations to make the measurement of solarradiation 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 tobe 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 directnormal irradiance must be measured with a pyrheliometer mounted on a solar tracker withtwo axes. Thus, by measuring the three components independently allows using proceduresfor quality assessment of the measurements based on the interrelationship between the threecomponents.The main errors in the measurement of solar radiation can be grouped into thefollowing categories: systematic errors of the measurement (such as a poor calibration of theequipment), errors by poorly maintenance (dirty sensor domes, or presence of obstacles), andor malfunctioning of the solar tracker.This report presents an analysis of the quality of themeasurements of the three components of solar radiation based on the recommendations ofthe BSRN. Tabla2 Meteorological instruments to measure solar radiation Name Variable measured Main use Angle of vision (sr) -3Absolutepirheliometer o Direct solar irradiance o Primarystandard 5·10 -3 -2Pirhelioemter o Direct solar irradiance o Secondarystandard 5·10 a 2.5·10 o Measure -3 -2Spectralpirheliometer o Direct solar irradiance (high o Measure 5·10 a 2.5·10 spectral wavelength) -3 -2Solar fotometer o Radiación solar directa o Standard 1·10 a 1·10 (banda espectral estrecha) o MeasurePiranometer o Global radiation o Secondarystandard 2π o Outgoing solar radiation o MeasureEspectral piranometer o Radiación global o Measure 2π (banda espectral ancha)Piranometer (RSR) o Global radiation o Secondarystandard 4π o MeasurePirgeometer o Longwaveradiation o Measure 2πPirradiometer o Total radiation o Scondary Standard 2π o MeasurePirradiometer (RSR) o Total radiation o Measure 4πBefore proceeding to the quality analysis of the measurements, we must change temporalreference of the data to true solar time. This change is performed by two corrections; the firstone takes into account the difference in longitude between the meridian of the observer andthe meridian of the temporal reference. The second includes various effects through theequation of time.The verification of the temporal reference of the records is checked to have certain that solarirradiance is measured correctly between sunrise and sunset. This check is done visually and ituses a model of clear sky. Graphics are plotted each day for the following components: directnormal and global horizontal irradiance of clear sky, global horizontal and direct normalirradiance and diffuse measurements. To estimate the values of clear sky, the model used isthe ESRA (European Solar Radiation Atlas) and the aerosol values used are the Linke Turbidityindex provided by SODA (Beyer et al., 1996, Dumortier, 1999, ESRA 2000a, ESRA 2000b). Thegraphs 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 uncertaintyassociated with the uncertainty of the Linke turbidity index fundamentally. However, thecomparison is useful in terms of the profile shape of solar irradiance during the day as well asthe relationship between direct and global irradiance for each day. Thus, both the shape andthe 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 beassessed 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 thedifferent components of the solar radiation, taking into account physical sense and notexceeding its value, therefore, limits physically possible. The next table presents the physicallimits imposed on each component of solar radiation according to the recommendation of theBSRN. Table 3: Physical limits of the solar radiation component Parameter Minimum Flag for Maximum Minimum Global Irradiance (GHI) -4 2 I SC 1.5(cos z) 1.2 100 W / m2 2 Diffuse Irradiance (DIF) - - 700 W/m Diffuse Irradiance (DIF) -4 2 I SC 0.95(cos z) 1.2 50 W / m2 Direct Normal Irradiance -4 2 I SC (DNI) Direct Normal Irradiance - - DNI Clear Sky (DNI)ISC: Solar constant (1367 Wm ), ɛ : eccentricity of the orbit, ϴ z: zenith angle -2The quality analysis of component cross filters is used to check that the measured data meetsthe interrelationship between the three components (GHI, DIF and DNI). Failure to pass thesefilters 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 imposedon the cross components analysis. Table 4: Conditions for the cross component Parameter Conditions Limits G z 75º , D B cos z 50 W / m2 1 ± 8% D B cos z G 75º z 93º , D B cos z 50 W / m2 1 ± 15% D B cos z D z 75º , G 50 W / m2 < 1.05 G D 75º z 93º , G 50 W / m2 < 1.10 GThe next procedure relates the three components but using a more tight procedure. This testis based on the comparison of instruments which measure the same variables. The next tabledefines the limits for this procedure: Table 5: Conditions for the second group of cross component filters Parameter Lower Limit Upper Limit -2 -2 B·cos z (G-D)-50 W/m (G-D)+50 W/m -2 -2 G-D B cos z- 50 W/m B cos z + 50 W/mThe next procedure relates the diffuse component (DIF or D) and global extraterrestrialirradiance (Gext) using the diffuse index defined as: Kd=A higher limit of 0.6 is given to this filter and in case it is not fulfilled the filter is activated. Thenext procedure makes use of clearness index (Kt) which is defined as the quotient betweengrounds 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 activatedThe 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 activatedThe last filter is named as the tracker off filter and it is used to detect when the solar tracker isnot working correctly. First, the global solar irradiance (Sum SW) is estimated from measureddiffuse solar irradiance and measured direct normal irradiance using the expression whichrelates the three components. Then the following condition is established using clear skyglobal irradiance (Gcclear) estimated with the model of ESRA and monthly climatological LinkeTurbidity 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 andDIF using the following expression:Where Kd0 is defined as: Kd0=And is the angle of solar altitude. 7. Databases of solar radiationThe lack of measured radiometric data, the low spatial coverage and the temporal variability ofthe registered solar radiation data makes it difficult to characterize certain areas. This way, it isof great usefulness the availability of other radiometric data sources in different project phaseslike site selection in the prefeasibility phase or the beginning of a measurement campaign(installation of measurement instruments in certain locations). As a conclusion, the databasesavailable 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 worldwidedatabases available of sola irradiance.SOURCES OF DATAGROUND MEASURED DATA: There are several instruments to measure the components ofsolar radiation at different wavelengths. If instruments are correctly operated, calibrated andmaintained this is the best source of information for site specific radiometric data. Due touncertainties in the instruments, errors expected may be around 8% in terms of RMSE forinstantaneous values.SYNTETHIC GENERATED DATA: This data is generated to meet specific needs or certainconditions that may not be found in the original, real data. In the case that there is nomeasured data we can generate data artificially following general statistical properties of solarradiation, like monthly mean and auto-correlation function. There is no way to compare thisdata with real measured data because this data is artificially generated and doesnt take intoaccount what happens in reality.DATA ESTIMATED FROM SATELLITE: This is the best source of information to know accuratelythe value of long-term solar radiation in case there are no local measurements available. Theerrors for hourly, daily and monthly means are 12%, 10% and less than 5% respectively asstated before.REANALYSIS: The reanalysisdata set is a continually updating gridded data set representing thestate of the Earths atmosphere, incorporating observations and numerical weather prediction(NWP) model output. A meteorological reanalysis is a meteorological data assimilation projectwhich aims to assimilate historical observational data spanning an extended period, using asingle consistent assimilation (or "analysis") scheme throughout implemented in the NWPmodel. 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 ExperimentGEWEX under the umbrella of the World Climate Research Programme (WCRP) and as such isaimed at detecting important changes in the Earths radiation field at the Earths surface whichmay be related to climate changes.The data are of primary importance in supporting the validation and confirmation of satelliteand computer model estimates of these quantities. At a small number of stations (currentlyabout 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 highestavailable accuracy and with high time resolution (1 to 3 minutes).The BSRN was recently (early 2004) designated as the global baseline network for surfaceradiation for the Global Climate Observing System (GCOS). The BSRN stations also contributeto 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 4Running 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 acentral depository for solar radiation data collected at over 1000 measurement sitesthroughout the world.The WRDC was established in accordance with Resolution 31 of WMO Executive CommitteeXVIII in 1964. The WRDC centrally collects, archives and published radiometric data from theworld to ensure the availability of these data for research by the international scientificcommunity.The WRDC archive contains the following measurements (not all observations are made at allsites): 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 newmeasurements are received and processed, they are added to the archive. The archivecurrently 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 meteorologicaldata for solar applications, system design and a wide range of other applications for anylocation in the world. meteonorm addresses engineers, architects, teachers, planners andanyone interested in solar energy and climatology.Meteonorm includes 8300 meteorological stations worldwide. Numerous global and regionaldatabases have been examined for their reliability and combined in meteonorm. The mostimportant data sources are the GEBA (Global Ener-gy Balance Archive), the WorldMeteorological Organization (WMO/OMM) Cli-mato-logical Normals 1961—1990 and theSwiss database compiled by MeteoSwiss.In meteonorm, the climatological periods 1961—1990 and 2000—2009 are available fortemperature, humidity, wind speed and precipitation. The climatological periods 1981—1990and 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 5Ground 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 andresearch providing data important to the study of climate and climate processes. These datainclude long-term estimates of meteorological quantities and surface solar energy fluxes.These satellite and modeled based products have been shown to be accurate enough toprovide reliable solar and meteorological resource data over regions where surfacemeasurements are sparse or nonexistent, and offer two unique features - the data is globaland, in general, contiguous in time. These two important characteristics, however, tend togenerate very large data archives which can be intimidating for commercial users, particularlynew users with little experience or resources to explore these large data sets. Moreover thedata products contained in the various NASA archives are often in formats that presentchallenges to new users. To foster the commercial use of the global solar and meteorologicaldata, NASA supported, and continues to support, the development of the Surface meteorologyand Solar Energy (SSE) dataset that has been formulated specifically for photovoltaic andrenewable energy system design needs. Of equal importance is the access to these data; tothis end the SSE parameters are available via user-friendly web-based applications founded onuser needs.
The original SSE data-delivery web site, intended to provide easy access to parameters neededin the renewable energy industry (e.g. solar and wind energy), was released to the public in1997. The solar and meteorological data contained in this first release was based on the 1993NASA/World Climate Research Program Version 1.1 Surface Radiation Budget (SRB) sciencedata and TOVS data from the International Satellite Cloud Climatology Project (ISCCP). Thisinitial 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 theenergy 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 ofthe renewable energy community. Subsequent releases of SSE have continued to build uponan interactive dialog with potential customers resulting in updated parameters using revisedNASA 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 toimprove subsequent releases of SSE, and to create new datasets applicable to other industriesfrom new satellite observations and the accompanying results from forecast modeling. POWERcurrently encompasses the SSE data set, tailored for the renewable energy industry, as well asparameters tailored for the sustainable buildings community, and the bio-energy/agriculturalindustries. In general, the underlying data behind the parameters used by each of theseindustries is the same - solar radiation and meteorology, including surface and airtemperatures, 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: thegeostationary satellite images and the information about the attenuating properties of theatmosphere. The former consists of one image per hour offering information related with thecloud cover characteristics. The latter is basically information on the daily Linke turbidity whichis a very representative parameter to model the attenuating processes which affects solarradiation on its path through the atmosphere, mainly daily values of aerosol optical depth andwater vapor column from Moderate Resolution Imaging Spectroradiometer satellite (MODIS).Solar radiation estimation from satellite images offered is made from a modified version of therenowned model Heliosat-3, developed and validated by CIEMAT with more than thirtyradiometric stations in the Iberian Peninsula. Over this first development, IrSOLaV hasgenerated a tool fully operational which is applied on a database of satellite images availablewith IrSOLaV (temporal and spatial resolution of the data depends on the satellite covering theregion 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 localdata from radiometric stations installed in the region of interest. This way, it may beconsidered that the treatment of the information from satellite images offered by IrSOLaV isan exclusive service.Even though the different research groups working in this field are making use of the samecore methodologies, there are several characteristics that differ depending on the specificobjectives 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 measurementsis expressed in terms of the relative root mean squared error (RMSE). Different assessmentsand benchmarking tests can been found at the available literature concerning the use ofsatellite 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 etal., 2007]. The uncertainty for hourly values is estimated around 20-25% RMSE and in a dailybasis the uncertainty of the models used to be about 13-17%. It is important to mention herethe contribution given by Zelenka in terms of distributing the origin of this error, concludingthat 12-13% is produced by the methodology itself converting satellite information intoradiation data and a relevant fraction of 7-10% because of the uncertainty of the groundmeasurements used for the comparison. In addition Zelenka estimates that the error of usingnearby ground stations beyond 5 km reaches 15%. Because of that his conclusion is that theuse of hourly data from satellite images is more accurate than using information from nearbystations located more than 5 km far from the site.The IrSOLaV methodology is based on the work developed in CIEMAT by the group of SolarRadiation Studies. The model has been assessed for about 30 Spanish sites with the followinguncertainty data for global horizontal irradiance: About 12% RMSE for hourly values Less than 10% for daily values
Less than 5% for annual and monthly meansThe model has been modified for a better estimation of solar radiation with clear sky, leadingto 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 seriesfor every land surface worldwide. A satellite based daily snow cover dataset is use to aid indistinguishing snow from clouds. In addition, the global horizontal clearsky radiation ismodeled based on the surface elevation of each location, the local time, and the measure ofturbidity in the atmosphere. 3Tier opted to use a satellite based, monthly time series of aersoloptical depth and water vapor derived from the MODIS satellite. This dataset was combinedwith another turbidity dataset that includes both surface and satellite observations to provideturbidity measure that spans the period of our satellite dataset and is complete for all landsurfaces. The cloud index n and the clear sky irradiance are then combined to model the globalhorizontal irradiance. This component of the process is calibrated for each satellite based on aset of high-quality surface observations. The global horizontal irradiance estimates are thencombined 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 datafor the solar energy community. The service is mainly based on METEOSAT-data with anominal 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 foralmost half of the Earths surface: the field of view of METEOSAT-7 placed at 0 longitude andadditionally the field of view of METEOSAT-5 placed at 63E over the Indian Ocean will beprovided. The METEOSAT-5 data cover such promising solar energy regions as India, Pakistanor China. Other very promising countries at the Saudi Arabian Peninsula may also be analyzedby METEOSAT-7 but METEOSAT-5 provides better viewing conditions. Fast access to the fullMETEOSAT-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 bothsatellites. The operational high performance computing environment DIMS (Data andInformation Management System) at DLR-DFD (German Remote Sensing Data Center) allowsfor 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 analysisclassifies the pixels, the lower boundary (LB) evaluation is done for each time slot, a spatialvariability is introduced for the upper boundary (UP) and the cloud index definition, the Solisclears 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 snowand no-snow cloud-free situations. Prior to the classification, calibrated pixel values weretransformed 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 ofadditional ancillary snow data and allowed using spectral cloud index information in cases ofcomplex 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 alower bound (LB), representing cloudless situations. This approach neglects diurnal variabilityof 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) thatreflects 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) valuewere updated to account for spatial variability which is important especially in the higherlatitudes. Calculation of cloud index was extended by incorporation of snow classificationresults.The broadband simplified version of Solis model (Ineichen 2008a) was implemented. As inputof 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 Aerocomdatasets are used.Simplified Solis model was also implemented into the global to beam Dirindex algorithms tocalculate Direct Normal irradiance component (Perez 1992, Ineichen 2008c). Diffuse irradiancefor inclined surfaces is calculated by updated Perez model (1987).Processing chain of the model includes post-processing terrain disaggregation algorithm basedon the approach by (Ruiz-Arias, J. A., T.Cebecauer, J.Tovar-Pescador, & M.Súri 2010). Thedisaggregation is limited to shadowing effect only, as it represents most significant local effectof terrain. The algorithm uses local terrain horizon information with spatial resolution of 100m. Direct and circumsolar diffuse components of global irradiance were corrected for terrainshadowing.
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 technologiesThe most important parameter that affects performance of CSP plants is DNI. We have to payattention on the yearly value of DNI, the dynamic of the cloud transient and the DNI frequencydistribution. 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. Ifinstantaneous DNI values are outside this range, the plant could not utilize such DNI values andhence energy is lost. The design range of DNI values for which a plant could operate aregenerally determined from long-term frequency distribution of DNI. Frequency distribution ofDNI describes the number of occurrences of DNI values which are expected to be received fora specific location. Usually, DNI frequency distribution follows properties of normaldistribution. It has been demonstrated that for years with the same DNI annual averagesdifferences in DNI frequency distribution could make the annual energy yield to be different,with differences from -8% to +9%. 9. ReferencesCano, D., Monget, J. M., Albussion, M., Guillard, H., Regas, N., & Wald, L. 1986. A method forthe determination of global solar radiation from meteorological satellite data. Solar Energy,37: 31-39.Derrien M. & H.Gleau 2005. MSG/SEVIRI cloud mask and type from SAFNWEC. InternationalJournal of Remote Sensing, 26: 4707-4732.ESRA 2000. The European solar radiation atlas. Paris (France): Les Presses de lEcole des Mines.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 Rayleighoptical thickness. Solar Energy, 56(3): 239-244.Kasten, F. & Young, A. T. 1989. Revised optical air mass tables and approximation formula.Applied Optics, 28(22): 4735-4738.Louche, A., Notton, G., Poggi, P., & Simonnot, G. 1991. Correlations for direct normal andglobal horizontal irradiation on a French Mediterranean site. Solar Energy, 46(4): 261-266.
McArthur, L. J. B. Baseline Surface Radiation Network. Operations Manual. WMO/TD-No.879.1998.Ref Type: ReportPerez, R., Ineichen, P., Moore, K., Kmiecik, M., Chain, C., George, R., & Vignola, F. 2002. A newoperational 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 SolarRadiation 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 solarradiation from satellite images. Solar Energy, 77(2): 159-169.Rigollier, C. & Wald, L. Using METEOSAT images to map the solar radiation: improvement ofthe Heliosat method. 432-433. 1998. Paris (France), 9th Conference on Satellite Meteorologyand Oceanography. 25-5-1998.Ref Type: Conference ProceedingRuiz-Arias, J. A., T.Cebecauer, J.Tovar-Pescador, & M.Súri 2010. Spatial disaggregation ofsatellite-derived irradiance using a high resolution digital elevation model. Solar Energy.Ruyter de Wildt M., G.Siez, & A.Gruen 2007. Operational snow mapping using multitemporalMeteosat 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.