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Solar resource measurements Presentation Transcript

  • 1. Solar Resource Measurementsand Satellite Data4th Sfera Summer School 2013Hornberg Castle, GermanyDr. Norbert GeuderCSP Services – Almería – Cologne
  • 2. 4th Sfera Summer School, Hornberg Castle, 2013 - 21) Introduction2) Fundamentals on Solar Irradiation3) Variability of Irradiation4) Irradiation Sensors5) Sensor calibration and measurement accuracy enhancement6) Satellite Based Assessment7) Outlook / SummaryOutline
  • 3. Selection of promising sitesLong-term time series(>10 years)Meteorological Station:Accurate irradiation data+Irradiation map: spatial distribution Geographical data: land use, etc.Plant design, inter-annual variability, uncertainty analysis, financing, …GIS analysisGeneral Procedure at Solar Resource Assessment4th Sfera Summer School, Hornberg Castle, 2013 - 3
  • 4. Solar Resource Assessment for CSP Plants• Direct Beam Irradiation data required for CSP Applications• Usually not available in suitable sunny regions in the world• Accessible via measurements or derived from satellite dataRestrictions:– Measurements: expensive, long duration, not for the past– Satellite data: high uncertainty (≈ 10 % or more)• High accuracy required for DNI with long-term performance4th Sfera Summer School, Hornberg Castle, 2013 - 4not global irradiation – this is quite a difference!
  • 5. Impact of Solar Resource Uncertaintyon CSP Plant rentabilityAnnual DNIAnnualexpenses(redemption,O&M, …)ElectricityproductionDNIuncertainty(e.g. ±10 %)Earningsexpected long-term value (100%)LossesIrradiation uncertainty decides over project realization !With thoroughly performed measurements an accuracy of approximately 2 % is achievable.4th Sfera Summer School, Hornberg Castle, 2013 - 5
  • 6. Fundamentals on Solar Irradiation4th Sfera Summer School, Hornberg Castle, 2013 - 6
  • 7. Solar ConstantMean solar irradiance (flux densityin W/m²) at normal incidenceoutside the atmosphereat the mean sun-earth distance r.1367 W/m²Calculation:Luminosity of the sun: L = 3.86 x 1026 WAstronomical unit: r = 149.60×109 m132013301340135013601370138013901400141014200 90 180 270 360IrradianceOutsideAtmosphere(W/m²)Day of YearAnnual Variation of Solar Constant2213674 mWrL4th Sfera Summer School, Hornberg Castle, 2013 - 7
  • 8. Source: DLRPath of Solar Radiation through the atmosphereRayleigh scattering and absorption (ca. 15%)Absorption (ca. 1%)Scatter and Absorption ( ca. 15%, max. 100%)Reflection, Scatter, Absorption (max. 100%)Absorption (ca. 15%)Ozone.……….…....Aerosol…….………..…...……Water Vapor…….……...………Clouds………….………..Air molecules..……Direct normal irradiance at groundRadiation at the top of atmosphere4th Sfera Summer School, Hornberg Castle, 2013 - 8
  • 9. Source: DLRRadiative Transfer in the Atmosphere020040060080010001200140000:0002:0004:0006:0008:0010:0012:0014:0016:0018:0020:0022:0000:00Hour of DayDirectNormalIrradiation(W/m²)ExtraterrestrialO2 and CO2OzoneRayleighWater VaporAerosolClouds4th Sfera Summer School, Hornberg Castle, 2013 - 9
  • 10. Source: DLRAir MassAM = 0 (outside of atmosphere)4th Sfera Summer School, Hornberg Castle, 2013 - 10
  • 11. Solar Spectrum and Atmospheric Influence1 Planck curve T=5780 K at mean sun-earth distance2 extraterrestrial solar spectrum3 absorption by 034 scattering by 02 und N25 scattering by aerosols6 absorption by H2O vapor7 absorption by aerosolsUV radiation: 0.01 - 0.39 µm, ~ 7 %Visible Spectrum: 0.39 – 0.75 µm, ~ 46 %Near infrared: 0.75 – 2.5 µm, ~ 47 %www.volker-quaschning.de/articles/fundamentals1/index.php4th Sfera Summer School, Hornberg Castle, 2013 - 11
  • 12. Characteristics of solar irradiation data• Component:– DNI (Direct-Normal Irradiation)– DHI (Diffus-Horizontal Irradiation)– GHI (Global-Horizontal Irradiation)• Source:– ground measurements:• precise thermal sensors (thermopiles)• Rotating Shadowband Irradiometers (RSI)– satellite data• Properties of irradiation:– spatial variability– inter-annual variability– long-term drifts4th Sfera Summer School, Hornberg Castle, 2013 - 12
  • 13. Direct, Diffuse and Global IrradianceWhen measuring solar irradiance, thefollowing components are of particularinterest: Direct normal irradiance (DNI)(also: beam irradiance) Diffuse horizontal irradiance (DHI)(also: diffuse sky radiation) Global horizontal irradiance (GHI)(also: total solar irradiance)GHI = DHI + DNI * sin ()Zenith angle θ,solar elevation 4th Sfera Summer School, Hornberg Castle, 2013 - 13
  • 14. DNI = BHI / sin Example: = 50°BHI = 600W/m² DNI = 848W/m²DNI > BHIDirect-Normal- Irradiation (DNI)directDirect Normal Irradiation (DNI)with: BHI = Beam Horizontal Irradiation4th Sfera Summer School, Hornberg Castle, 2013 - 14
  • 15. GHI = BHI + DIFExample:DIF = 150W/m²BHI = 600W/m² GHI = 750W/m²Global-Horizontal-Irradiation (GHI)diffusedirectdiffuseGlobal Horizontal Irradiation (GHI)4th Sfera Summer School, Hornberg Castle, 2013 - 15
  • 16. Variability of irradiation
  • 17. Long-term variability of solar irradianceGHI from Potsdam, Germany4th Sfera Summer School, Hornberg Castle, 2013 - 17
  • 18. Source: DLRLong-term variability of solar irradiance7 to 10 years of measurement to get long-term mean within 5%4th Sfera Summer School, Hornberg Castle, 2013 - 18
  • 19. Source: DLRInter-annual variabilityStrong inter-annual andregional variations19992001200020022003deviationto meankWh/m²aAverage of the direct normalirradiance from 1999 to 20034th Sfera Summer School, Hornberg Castle, 2013 - 19
  • 20. Irradiation sensors4th Sfera Summer School, Hornberg Castle, 2013 - 20
  • 21. Absolute Cavity RadiometerPrinciple of Measurements:- Possibility to measure absolute irradiancevalues. All other irradiance measurementdevices need to be calibrated using an absolutecavity radiometer- Its principle of operation is based on thesubstitution of radiative power by electrical(heating) power- Measurement in intervals with minimal lengthof 45 s. Constant irradiation required formeasurement campain- Tracking device required- No continuous measurement (!)ftp.pmodwrc.ch/pub/pmo6-cc/user_guide_11.pdfValid for calibration purposes4th Sfera Summer School, Hornberg Castle, 2013 - 21
  • 22. Thermal sensors Semiconductor sensorRotating Shadowband Irradiometer,RSI(photodiode)Suitable equipment for irradiance measurements forConcentrating Solar Power (CSP)Pyranometer,pyrheliometer(thermopiles)4th Sfera Summer School, Hornberg Castle, 2013 - 22
  • 23. Thermopile SensorsCMP21 Pyranometer (GHI, DHI shaded)with ventilation unit CVF3CHP1 Pyrheliometer (DNI)Shading assembly with shading ballSolys 2 sun trackerSun sensor4th Sfera Summer School, Hornberg Castle, 2013 - 23
  • 24. Thermopile Sensors – PyrheliometerPrinciple of Measurement:- Pyrheliometer = radiometer suitable tomeasure direct normal irradiance- Highly transparent window 97 – 98 %transmission of solar radiation- Housing geomerty with 200 mm absorber tuberestricting acceptance angle to 5°- Sensing element with black coating andbuilt-in termopile device- Pt-100 temperature sensor for temperaturecorrectionswww.kippzonen.com/?product/18172/CHP+1.aspx4th Sfera Summer School, Hornberg Castle, 2013 - 24
  • 25. Pyrheliometer SpecificationsKipp&Zonen CHP 1 Specifications:Spectral range: 200 to 4000 nmSensitivity: 7 to 14 µV/W/m² (mV/kW/m²)Response time: < 5 sExpected daily uncertainty: ± 1 %Full opening view angle: 5° ± 0.2°Required tracking accuracy: ± 0.5° fromidealwww.kippzonen.com/?product/18172/CHP+1.aspx4th Sfera Summer School, Hornberg Castle, 2013 - 25
  • 26. Thermopile Sensors – PyranometerPrinciple of Measurements:- Pyrheliometer = radiometer suitable tomeasure short-wave (0.2 - 4 µm)global or diffuse radiation- Highly transparent glass dome 97 – 98 %transmission of solar radiation- Full view on 2π hemisphere(horizontal levelling required)- Sensing element with black coating andbuilt-in termopile- Pt-100 temperature sensor for temperaturecorrectionswww.kippzonen.com/?product/18172/CHP+1.aspx4th Sfera Summer School, Hornberg Castle, 2013 - 26
  • 27. Thermopile Sensors – PyranometerKipp&Zonen CMP21 Specifications:Spectral range: 285 to 2800 nmSensitivity: 7 to 14 µV/W/m² (mV/kW/m²)Response time: 5 s www.kippzonen.com/?product/1491/CMP+21.aspx4th Sfera Summer School, Hornberg Castle, 2013 - 27
  • 28. Rotating Shadowband Pyranometer (RSP)Rotating shadowbandLicor silicon photodiodeHousing of mechanics4th Sfera Summer School, Hornberg Castle, 2013 - 28
  • 29. RSI – Principle of MeasurementSource: Solar Millennium AGSimplified sensor signal during shadow band rotation:once per minute, rotation lasts about 1.5 seconds4th Sfera Summer School, Hornberg Castle, 2013 - 29
  • 30. Licor Li-200 Pyranometer SensorSpecifications:Sensitivity:Typically 90 µA per 1000 W/m²Response time: 10 µs.Spectral range: 0.4 – 1.1 µmCalibration:Calibrated against an Eppley PrecisionSpectral Pyranometer under naturaldaylight conditions.Typical error under these conditions is±3% up to ±5%.www.licor.com/env/Products/Sensors/200/li200_description.jsp4th Sfera Summer School, Hornberg Castle, 2013 - 30
  • 31. Precise thermal sensors:Pyrheliometer and Pyranometer on sun trackerAdvantages:+ high accuracy (1 to 2%)+ separate sensors forGHI, DNI and DHI(cross-check through redundancy)Disadvantages:- high acquisition costs- high maintenance costs- high susceptibility for soiling- high power demand(grid connection required)-GHI -DNI-DHI4th Sfera Summer School, Hornberg Castle, 2013 - 31
  • 32. Sensor with photo diode:Rotating Shadowband Irradiometer, RSIAdvantages:+ fair acquisition costs+ low maintenance+ low susceptibility for soiling+ low power demand (PV-Panel)Disadvantage:- reduced accuracy due to systematicdeviations of the photodiode sensorresponse:primordial DNI: ≈ 6 to 10 %(or even higher)4th Sfera Summer School, Hornberg Castle, 2013 - 32
  • 33. Measurement uncertaintyPrecise instruments (HP) versus RSIError source: Pyrheliometer: RSI: Calibration < ±1.1% ±3% (... ±5%) Temperature < ±0.5% 0% ... ±5% Linearity < ±0.2% ±1% Stability < ±0.5%/a < ±2%/a Spectral dependence <±0.1% 0% ... ±8% Sensor soiling -0.7% per day -0.07% per daysystematic errorscan be corrected!!4th Sfera Summer School, Hornberg Castle, 2013 - 33
  • 34. Choice of Measurement EquipmentHigh Precision sensors (thermopiles) Rotating Shadowband Irradiometer:RSI?Which equipment is suitable for measurements in Solar Resource Assessment?4th Sfera Summer School, Hornberg Castle, 2013 - 34
  • 35. Objectives for Irradiance MeasurementsSolar Resource Assessment• at remote site• no qualified staff• no electric grid• often dusty and arid areasPower Plant Monitoring• always qualified staff on site• electric power available4th Sfera Summer School, Hornberg Castle, 2013 - 35
  • 36. Pyrheliometer soiling in southern Spain4th Sfera Summer School, Hornberg Castle, 2013 - 36Plataforma Solar de Almería
  • 37. Comparison of sensor soiling4th Sfera Summer School, Hornberg Castle, 2013 - 37University of Almería
  • 38. Soiling characteristics of pyrheliometers and RSI‘sRSI sensor headPyrheliometerSolarIrradiation4th Sfera Summer School, Hornberg Castle, 2013 - 38direct sunlightglass platetube with 200 mm lengthabsorberdiffusor disk over photodiode
  • 39. Choice of the adequate equipmentFor Solar Resource Assessment• at remote sites and• daily maintenance not feasiblean RSI is the premium choice for DNI measurements.However:• Proper calibration• Corrections of systematic signal response• regular maintenance inspections (2 to 4 weeks)are indispensable for reliable measurements.4th Sfera Summer School, Hornberg Castle, 2013 - 39
  • 40. Sensor calibrationand measurement accuracy enhancement4th Sfera Summer School, Hornberg Castle, 2013 - 40
  • 41. Sensor Calibration – Fundamentals I- The World Standard Group(WSG) is an assembly of highlyprecise absolute cavityradiometers.- The measured mean value(World Radiometric Reference)is the measurement standardrepresenting the SI unit ofirradiance with an estimatedaccuracy of 0.3 %.- All other short wave irradiationmeasurement systems arecalibrated against this singlevalue.www.pmodwrc.ch/pmod.php?topic=wrcPrecision measurement at theWorldRadiation Center (WRC)4th Sfera Summer School, Hornberg Castle, 2013 - 41
  • 42. RSI sensor calibration by DLR on PSA2-monthly calibration of each RSI againsthigh-precision instrumentsat Plataforma Solar de Almería (PSA)(recommended every 2 years)4th Sfera Summer School, Hornberg Castle, 2013 - 42
  • 43. RSI sensor calibration durationVariations of the Calibration Constant with calibration duration4th Sfera Summer School, Hornberg Castle, 2013 - 43DNI
  • 44. Variability of the Correction Factors (CF)Variability ofcorrection factors(CF):radiation componentsneed to be correctedwith separate CFs.4th Sfera Summer School, Hornberg Castle, 2013 - 44
  • 45. Recalibration of RSIsDrift of Calibration Factor within 2 to 4 years4th Sfera Summer School, Hornberg Castle, 2013 - 45
  • 46. Correction of raw RSI measurement valuesOrigin of systematic errors of RSI response• Temperature dependence of semiconductor sensor• Spectrally varying irradiation– different for irradiation components (direct beam / diffuse)– depending on Air Mass• Angle of incidence• Pre-calibration of the sensor head (from the manufacturer)4th Sfera Summer School, Hornberg Castle, 2013 - 46
  • 47. Spectral correction of diffuse irradiation2DHIGHIDNIΠspeccorrectedraw valuesvariation withair mass + altitude4th Sfera Summer School, Hornberg Castle, 2013 - 47
  • 48. Dependence of response on solar elevationBHIref/ BHIRSIsolar elevation angle in degreeso called „cat-ear effect“Correction applied only on direct beam portion of the global response4th Sfera Summer School, Hornberg Castle, 2013 - 48
  • 49. Dependence of response on solar elevationBHIref/ BHIRSIsolar elevation angle in degreecorrected4th Sfera Summer School, Hornberg Castle, 2013 - 49
  • 50. Reachable accuracy for DNI with RSIsRMSD = 13 W/m²Accuracy of RSImeasurementsas derived from a comparisonof the data from 23 RSIswith precise thermopilemeasurementswithin the courseof a whole yearRSPGHI DHI DNI reference(CHP 1)unitraw cor raw cor raw coraverage MB -10.3 ± 4.0 0.3 ± 1.3 -17.3 ± 1.6 -0.4 ± 0.7 24.6 ± 10.5 1.0 ± 0.5 1.0 ± 3.9 W/m²RMSD 14.2 7.6 18.9 4.5 33.3 13.0 5.3 W/m²Annual sum up to -2.5 < ±1 up to -15 < ±3.5 up to +7 < ±1 up to 1.3 %4th Sfera Summer School, Hornberg Castle, 2013 - 5010 min time resolution
  • 51. Transferability of the results?The reachable accuracy of the measured beam irradiance datafor the client at his prospected sites depends on 2 crucial points:• Stability of the sensor sensitivity• Transferability of the results to other sites• Regular inspections and data controlling4th Sfera Summer School, Hornberg Castle, 2013 - 51
  • 52. Transferability to other sites and climatesParallel measurement campaignsin UAE:• Comparision of 6 RSIs to high-precisionthermal sensors• Measurement periods >3 weeks• in summer and winter4th Sfera Summer School, Hornberg Castle, 2013 - 52
  • 53. Relative deviation of DNI sum within measurementcampaign4th Sfera Summer School, Hornberg Castle, 2013 - 53only summer:DNI < 730 W/m²summer + winter:DNI until 1000 W/m²
  • 54. Satellite Based Assessment4th Sfera Summer School, Hornberg Castle, 2013 - 54
  • 55. Satellite Derived DataPrinciple of Measurements:Analyze satellite data in two steps:1. Atmosphere: Gather satellite information ofatmospheric composition (ozone, water vaporand aerosols) and apply the ‘clear sky model’ tocalculate the fractions of direct and diffuseirradiance2. Clouds: Calculate the cloud index as thedifference between actual reflectivity of theearth as it is seen by the satellite and areference image which only includesreflectance of the groundwww.solemi.de/method.html020040060080010001200140000:0002:0004:0006:0008:0010:0012:0014:0016:0018:0020:0022:0000:00Hour of DayDirectNormalIrradiation(W/m²)ExtraterrestrialO2 and CO2OzoneRayleighWater VaporAerosolClouds4th Sfera Summer School, Hornberg Castle, 2013 - 55
  • 56. Scan The Meteosat satellite islocated in ageostationary orbit The satellite scans theearth line by line everyhalf hourHow to derive irradiance data from satellitesSource: DLR4th Sfera Summer School, Hornberg Castle, 2013 - 56
  • 57. How to derive irradiance data from satellitesDerivation of acloud indexfrom the twochannels Scan in infra-red spectrumScan in visible spectrumSource: DLR4th Sfera Summer School, Hornberg Castle, 2013 - 57
  • 58. Different Cloud Transmission for GHI and DNI-0.200.20.40.60.811.2-0.2 0 0.2 0.4 0.6 0.8 1 1.2cloudtransmissioncloud index-0.200.20.40.60.811.2-0.2 0 0.2 0.4 0.6 0.8 1 1.2Sun-satellite angle 60-80-26 °C-16 °C-6 °C4 °C14 °C-30°C - -20°C-20°C - -10°C-10 °C - 0°C0°C - 10 °C>10°CDifferent exponentialfunctions for varyingviewing angles andbrightnesstemperatures Global Irradiation Direct IrradiationSource: DLR4th Sfera Summer School, Hornberg Castle, 2013 - 58
  • 59. Clear sky Model input data Aerosol optical thickness GACP Resolution 4°x5°, monthly data MATCH Resolution 1.9°x1.9°, daily data Water Vapor:NCAR/NCEP ReanalysisResolution 1.125°x1.125°, daily values Ozone:TOMS sensorResolution 1.25°x1.25°, monthly valuesSource: DLR4th Sfera Summer School, Hornberg Castle, 2013 - 59
  • 60. Uncertainty in AerosolsAll graphs are forJulyScales are the same!(0 – 1.5)Large differences inAerosol values anddistributionGADSTomsGOCARTNASA GISS v1 / GACPNASA GISS v2 1990AeroCom Linke TurbiditySource: DLR4th Sfera Summer School, Hornberg Castle, 2013 - 60
  • 61. satellite pixel( 3x4 km²)groundmeasurementinstrument(2x2 cm²)solar thermalpower plant(200MW  2x2km²Comparing ground and satellite data:“sensor size”Source: DLR4th Sfera Summer School, Hornberg Castle, 2013 - 61
  • 62. 0200400600800100012000 6 12 18 24hour of dayW/m²groundsatellitegeneral difficulties:• point versus area• time integrated versusarea integratedSource: DLRComparing ground and satellite data:accuracy4th Sfera Summer School, Hornberg Castle, 2013 - 62
  • 63. 12:45 13:00 13:15 13:30 13:45 14:00 14:15Hi-res satellite pixel in EuropeComparing ground and satellite data:time scales Ground measurements are typicallypin point measurements which aretemporally integrated Satellite measurements areinstantaneous spatial averages Hourly values are calculated fromtemporal and spatial averaging(cloud movement)Hourly average Meteosat image MeasurementSource: DLR4th Sfera Summer School, Hornberg Castle, 2013 - 63
  • 64. Source: DLRTemporal resolution of input data: 1 hourSpatial resolution of digital map: 1 km x 1 km per PixelLong term analysis: up to 20 years of datadata produced by (DLR, 2004) for MED-CSPThe original digital maps canbe navigated and zoomed withGeographical InformationsSystems like ArcView or Idrisi.Results of the satellite-based solar assessmentDigital maps: e.g. annual sum of direct normal irradiationin 2002 in the Mediterranean Region4th Sfera Summer School, Hornberg Castle, 2013 - 64
  • 65. Source: DLRHourly monthly mean of DNI in Wh/m², Solar Village 2000hourAnnual sums of DNI [kWh/m²] for one site in SpainMonthly sums of DNI [kWh/m²] for one site in SpainHourly DNI [Wh/m²] for one site in SpainResults of the satellite-based solar assessmentTime series: for single sites, e.g. hourly, monthly or annual4th Sfera Summer School, Hornberg Castle, 2013 - 65
  • 66. Satellite data and nearest neighbourstationsSatellite deriveddata fit betterto a selectedsite thangroundmeasurementsfrom a sitefarther than25 km away.Source: DLR4th Sfera Summer School, Hornberg Castle, 2013 - 66
  • 67. Ground measurements vs. satellite derived dataGround measurementsAdvantages+ high accuracy (depending on sensors)+ high time resolutionDisadvantages- high costs for installation and O&M- soiling of the sensors- possible sensor failures- no possibility to gain data of the pastSatellite dataAdvantages+ spatial resolution+ long-term data (more than 20 years)+ effectively no failures+ no soiling+ no ground site necessary+ low costsDisadvantages- lower time resolution- low accuracy at high time resolution4th Sfera Summer School, Hornberg Castle, 2013 - 67
  • 68. Combining Ground and Satellite Assessments• Satellite data– Long-term average– Year to year variability– Regional assessment• Ground data– High Precision (if measurements taken thoroughly)– High temporal resolution possible(up to 1 min to model transient effects)– Good distribution function– Site specific4th Sfera Summer School, Hornberg Castle, 2013 - 68
  • 69. Procedure for Matching Ground and Satellite DataSatelliteassessmentGroundmeasurementsComparisonSeparation of clear skyand cloud conditionsRecalculationwith alternativeatmospheric inputSelectionof best atmospheric inputRecalculationwith alternative cloudtransmission tablesSelectionof best cloudtransmission tableTransfer MSG to MFGRecalculation oflong term time seriesBest fitsatellite dataclearskycorrectioncloudcorrection4th Sfera Summer School, Hornberg Castle, 2013 - 69
  • 70. What you should care for in goodSolar Resource Assessment4th Sfera Summer School, Hornberg Castle, 2013 - 70
  • 71. Procedure to Follow for Proper Solar ResourceAssessment• Find a good location: close to site, safe, suitable for collocation of WeatherStation• Clarify the ground property conditions• Check/define the budget for:instrumentation, maintenance and measurement related services• Select the appropriate measurement equipment and provider(based on budget considerations, local conditions on site and maintenancepossibilities)• Find local maintenance personnel• Prepare the measurement site according to the supplier’s specifications(foundations, fencing, etc.)• Installation and commissioning of the measurement equipment• Steady monitoring of the measurement data,duration minimum 1 year4th Sfera Summer School, Hornberg Castle, 2013 - 71
  • 72. Procedure to Follow for Proper Solar ResourceAssessment• Documenting the selection of instruments• Choosing a renowned company or institution to conduct or assist themeasurement campaign• Documenting sensor calibration with proper calibration certificates• Meticolously documenting the instrument installation and alignment• Performing and documenting regular sensor cleaning, maintenance andverification of alignment• Cautiously and continuously checking data for errors and outliers• Flagging suspect data, and applying corrections if possible, during and afterthe measurement campaign• Stating and justifying the uncertainty estimate in a detailed report after themeasurement campaign.4th Sfera Summer School, Hornberg Castle, 2013 - 72
  • 73.  Delivery of hardware Installation & commissioning Operational supervision andcontrol Equipment monitoringwith inspection visits on siteDaily data retrieval viamodem (GSM/GPRS)Data collection and processing:• accuracy enhancement(correction)• quality and functionality check• graphical visualizationExpert officeDaily, monthly,annual report withgood quality datato client (via e-mail)On siteClientUsual Expert Service for Solar Resource Assessment4th Sfera Summer School, Hornberg Castle, 2013 - 73
  • 74. Quality Control of Measurement Data Are values physically possible ?Measurement values must metphysical limits Are they reasonable?e.g. comparison to a clear skymodel (Bird) or in kd-kt-space Are they consistent?Comparison of redundantinformation Visual inspection by an expert4th Sfera Summer School, Hornberg Castle, 2013 - 74
  • 75. Summary• Knowledge of accurate irradiation data is indispensable for CSPprojects(→ proper plant design, financial calculation, efficient plant operation)• site selection, pre‐feasibility with satellite data• colocation of a measurement station, taking care on thorough operation• match long‐term satellite data with good quality measurement data from ground• monitor the operating plant efficiency thoroughly with high‐precision data4th Sfera Summer School, Hornberg Castle, 2013 - 75
  • 76. Thank youvery muchfor yourattention!4th Sfera Summer School, Hornberg Castle, 2013 - 76
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