THE SOLAR RESOURCE: PART II MINES ParisTech Center Observation, Impacts, Energy (Tel.: +33 (0) )

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1 MASTER REST Solar Resource Part II THE SOLAR RESOURCE: PART II MINES ParisTech Center Observation, Impacts, Energy (Tel.: +33 (0) ) MASTER REST Solar Resource Ambiguity on the definition of the direct irradiance SO definition ISO9488 (1999): direct irradiance is the quotient of the radiant flux on a given plane receiver surface received from a small solid angle centered on the sun s disk to the area of that surface. If the plane is perpendicular to the axis of the solid angle, direct normal solar irradiance is received. MINES ParisTech 1

2 MASTER REST Solar Resource Part II 3 Ambiguity on the definition of the direct irradiance 4 Ambiguity on the definition of the direct irradiance MINES ParisTech 2

3 MASTER REST Solar Resource Part II 5 Ambiguity on the definition of the direct irradiance Different implicit interpretations for the term small solid angle For concentrating solar systems: large range of acceptance half-angles CSP: typically from 0.7 to 2.3 CPV: typically from 0.5 to 5 For standard radiative transfer model: no angular extension (// Dirac function) or corresponding to the solar angular radius For solar radiation measurement: Recommendations from WMO CIMO Guide Primary standard: 2.5 (6 msr) Secondary standard: from 2.5 to 5 (6 24 msr) 6 - SOLAR RADIATION - GROUND MEASUREMENTS SATELLITE-BASED ESTIMATION MINES ParisTech 3

4 MASTER REST Solar Resource Part II Ground pyranometric stations 7 Pyranometer: thermopile meant to measure the broadband global ground solar irradiation on a horizontal surface (300 nm à 2500 nm, typically) Measurement of Global Horizontal Irradiation (GHI) 8 Ground pyranometric station Pyrheliometer: thermopile on a collimation tube (angle of view < 1 5 ) on an automatic 2-axis sun trackers Measurement of the direct (or beam) normal irradiation (DNI) MINES ParisTech 4

5 MASTER REST Solar Resource Part II Ground pyranometric station 9 Pyranometer with a shadow band (manual, automatic, rotating, ) Measurement of the diffuse horizontal irradiation (DHI) Shadow-band pyranometer Synthesis 10 MINES ParisTech 5

6 MASTER REST Solar Resource Part II 11 Example: Complete ground pyranometric stations 12 High quality solar radiation systems for irradiance measurement Pyranometer, shaded pyranometer, pyrheliometer on a high precision sun tracking system Model of the pyranometric system used for the Baseline Surface Radiation Network (BSRN) Redundancy between the three measurements Three component based quality test Data gap filling possibilities Ground pyranometric station G = Gd + Gb, n cosθs Very sensitive to angular misalignment and soiling & humidity effects need high quality and frequent on-site complex maintenance MINES ParisTech 6

7 MASTER REST Solar Resource Part II Alternative ground pyranometric station 13 Alternative Solar radiation system for DNI measurement More robust (and less maintenance) Delta-T SPN1 sensors Less expensive (investment and O&M cost) Rotating Shadowband Irradiometer (RSI) Courtesy of EDF R&D - CEREA Ground pyranometric station 14 With no moving parts MINES ParisTech 7

8 MASTER REST Solar Resource Part II Alternative ground pyranometric station 15 RSI Simple and low-consumption mechanism of rotating shadowband No complex and fragile angular alignment (no Sun tracking system) Robustness w.r.t. soiling by dust & humidity Root Mean Square Error (RMSE) (10-min average irradiance): < 2 % - 3 % for DNI > 200 W/m2 Opening half-angle: ~ 2.9 Silicon photodiode LI-COR (0.4 µm 1.2 µm): need calibration modeling to be coherent with a thermopile sensor. No redundant measurement SPN1 No moving parts (robustness, very low electric consumption) Same maintenance as a standard pyranometer Thermopiles based sensor (~ full solar spectrum: 0.25 µm 2.5 µm) Root Mean Square Error (RMSE) (10-min average irradiance): ~ > 7 % (Bias > 5 %) for DNI > 200 W/m 2 Opening half-angle >> 2.5 (to be assessed) "Signal processing" of the seven thermopiles to be improved: Sky radiance is non isotropic Damp the discontinuities during transitions between thermopiles Correction of the opening half-angle larger than Sunshine Recorder: measurement of the sunshine duration (Beam Horizontal Irradiation > 120 W/m 2 ) Angstrøm relation H/Ho = a + b S/So with : Ground pyranometric station H = Daily Global Horizontal Irradiation (GHI) Ho= TOA Daily Global Horizontal Irradiation S = Sunshine duration S 0 = Astronomical Day length And coefficients a and b locally and empirically estimated MINES ParisTech 8

9 MASTER REST Solar Resource Part II 17 International networks of meteorological ground stations Baseline Surface Radiation Network (BSRN) 18 International networks of meteorological ground stations WMO (Nations Unies) : ~ stations MINES ParisTech 9

10 MASTER REST Solar Resource Part II 19 International networks of meteorological ground stations Meteo France Meteorological Ground Stations (~ 490 stations that measures at least daily global irradiation) Source : International networks of meteorological ground stations 20 Some difficulties to deal with those ground stations Different types of access (phone, (e)mail, automatic , CD, web-services, ) Different levels of maintenance No data gaps and complex temporal coverage Problem with metadata (existence, reliability) Unit problem: W/m 2, J/cm 2, J/m 2, Wh/m 2, etc Time reference (UT, LAT, TST, MST, etc.) Temporal integration (left, centre, or right) 1h 2h 3h 4h 5h m 1 m 2 m 3 m 4 m 1 m 2 m 3 m 4 time time m 1 m 2 m 3 m 4 time MINES ParisTech 10

11 MASTER REST Solar Resource Part II 21 International networks of meteorological ground stations How to get a time series of irradiation at a given location? Spatial (and temporal) complex interpolation based on an irregular set of ground stations. Underlying issue : what is the spatial variability of the irradiation field? Daily irradiation data in the South of France RMSE (%) Distance géodésique (km) Satellite-based estimation of solar irradiation The HELIOSAT method 22 Geostationary satellites METEOSAT (9) METEOSAT 1 (1977) METEOSAT Second Generation MSG-1 en 2002 MSG-2 en 2005 MINES ParisTech 11

12 MASTER REST Solar Resource Part II 23 Satellite-based estimation of solar irradiation The HELIOSAT method The principle Luminance measured by MSG Irradiation 24 Satellite-based estimation of solar irradiation The HELIOSAT method SPACE satellite ATMOSPHERE cloud target 1 target 2 OCEAN, GROUND MINES ParisTech 12

13 MASTER REST Solar Resource Part II 25 Satellite-based estimation of solar irradiation The HELIOSAT method HELIOSAT HelioClim Solar Databases HelioClim-1 (HC-1) Spatial resolution: km Temporal resolution: daily values Temporal coverage: HelioClim-3 (HC-3) Spatial resolution: 4 km Temporal resolution: ¼ horaire Temporal coverage: since 2004 Spatial coverage and resolution of HelioClim-3 Satellite-based estimation of solar irradiation The HELIOSAT method 26 Hourly sums of GHI Daily sums of GHI Monthly sums of GHI MINES ParisTech 13

14 MASTER REST Solar Resource Part II 27 Satellite-based estimation of solar irradiation The HELIOSAT method Rough order of differences between ground stations and HelioSat estimation of GHI: Hourly sums: % Daily sums: 10 Monthly sums: 5 % Yearly sums: 2 % Differences: Comparison between of precise location vs. spatially integrated estimation on the MSG pixel (underlying spatial variability effects) At ¼ hours resolution: Instantaneous estimation with MSG Integrated value during the previous 15 minutes Measurement errors due to the ground station (~3 5 %) Heliosat estimation errors (albedo, parallax effects, etc.) (12 15 %) 28 Satellite-based estimation of solar irradiation The HELIOSAT method Irradiation on a tilted plan from the GHI estimation (static or with a 2D/1D sun-tracker) Need a decomposition of GHI: Beam Horizontal Irradiation B h Diffuse Horizontal Irradiation D h Diffuse Circumsolar Diffuse Isotropic (Diffuse from the horizon) MINES ParisTech 14

15 MASTER REST Solar Resource Part II 29 Satellite-based estimation of solar irradiation The HELIOSAT method Actual HELIOSAT method: estimation of the broadband GHI Direct and Diffuse components estimated from empirical transposition models Different stages : K t : ratio GHI / TOA K d : ratio DHI / GHI Abacus of K d from K t and other possible parameters (solar elevation, temporal variability, etc.) G t D t = f(kt, p 1,, p n )G t B t = G t D t DNI t =B t /sin(γ t ) D h /G h G h /H 0 Satellite-based estimation of solar irradiation Empirical transposition models 30 Limits of the empirical transposition models High variability of the residual with respects the model (high Root Mean Square Error) Problem of extrapolation of these models in space (and in time) : high RMSE and possible high MBE (Mean Bias Error) J. A Ruiz-Arias et al. 2010, Proposal of a regressive model for the hourly diffuse solar radiation under all sky conditions, Energy Conversion and Management, vol. 51, no. 5, pp , May MINES ParisTech 15

16 MASTER REST Solar Resource Part II 31 Satellite-based estimation of solar irradiation The new HELIOSAT-4 method Direct approach based on radiative transfer code Inputs parameters Site location (lat,lon,h) Atmospheric constituents Spectral aerosol optical depth Water vapor contents Ozone content Atmospheric profiles Cloud cover SPACE I 0 absorption Atmospheric parameters derived from satellite Sun position (SZA) ATMOSPHERE scattering Modeling propagation Direct / Diffuse estimation (no empirical transposition models) Spectral resolution B reflection Angular resolution OCEAN, GROUND target 32 Fast Clear-sky irradiation models McClear - Map results McClear: fast implementation of libradtran Abacci + specific interpolation functions Example of Clear-sky daily GHI (MACC data) May 2008 MINES ParisTech 16

17 MASTER REST Solar Resource Part II 33 - SOLAR RADIATION - SOLAR CARTOGRAPHY FROM THE WORLD SCALE TO THE REGIONAL SCALE Solar cartography from the World scale to the regional scale 34 Worldwide scale solar radiation maps: Numerical Weather Model (reanalysis products) Yearly sum of irradiation map (kwh/m 2 ) 3500 kwh/m² 3000 kwh/m² 2500 kwh/m² 2000 kwh/m² 1500 kwh/m² 1000 kwh/m² 500 kwh/m² Daily UV map for the World Cancer Report (WHO) MINES ParisTech 17

18 MASTER REST Solar Resource Part II 35 Solar cartography from the World scale to the regional scale HelioClim-based cartography (country, continent scales) Yearly sum of irradiation European map (kwh/m 2 ) 36 Solar cartography from the World scale to the regional scale Example of solar cartography at the regional scale Solar Atlas at 250 m resolution for PACA MINES ParisTech 18

19 MASTER REST Solar Resource Part II 37 Solar Atlas for PACA region Introduction Main characteristics: 200 m resolution solar resource maps Monthly and annually sum of Direct and Global Irradiations Typical Mean Years from 20 years of daily solar resource analysis (HelioClim) PV and Solar Thermodynamic Applications Global irradiations on typical tilted plans (PV) Direct Irradiation on typical tilted plans and in normal incidence (for Concentrated Solar Technologies) 38 Solar Atlas for PACA region The Project Intra-pixel (HC-3) effects of the relief Effect of the optical depth variations of the atmosphere Shadow effects respectively for the diffuse and direct components of the global irradiation Use of the relief database SRTM (Shuttle Radar Topography Mission) Spatial resolution of 100 m Localization Accuracy better than 10 m Local calibration of irradiation estimation with on-ground measurements Calibration of the global horizontal irradiation Calibration of the parametric experimental model of global/diffuse decomposition Modeling of uncertainty from the calibration residue analysis MINES ParisTech 19

20 MASTER REST Solar Resource Part II 39 Example : Annot Solar Atlas for PACA region Horizon database (shadows effects) 40 Solar Atlas for PACA region Shadows effects on solar irradiations Example: Annot MINES ParisTech 20

21 MASTER REST Solar Resource Part II 41 Solar Atlas for PACA region Shadows effects on solar irradiations GHI varibility inside a HC3 pixel (annual and monthly sums) 42 Monthly sums of GHI (Ref: 20 MF stations) Monthly sums of GHI LOOCV (Ref: 20 MF stations) Monthly sums of GHI (3 RSP stations) Solar Atlas for PACA region Corrected * HelioClim-3: monthly GHI estimation errors NDATA MREF MBE MAE RMSE CC 1269 months 132 kwh/m % 3.1 % 4.3 % months 132 kwh/m % 4.4 % 6.2 % months 126 kwh/m % 2.5 % 3.1 % * Corrected HC3: Orography effects Local calibration RMSE dependency with orography Mountainous area: 5.8 % => 7.4 kwh/m 2 (et MBE = -0.6%) Non-mountainous area: 3.2 % => 4.3 kwh/m 2 (et MBE < -0.1%) RMSE MBE <0 MBE >0 MINES ParisTech 21

22 MASTER REST Solar Resource Part II 43 Solar Atlas for PACA region Example of high resolution irradiation map Map of yearly sums of GHI (mean between ) 44 Solar Atlas for PACA region Example of high resolution irradiation map Map of yearly sums of DNI (mean between ) MINES ParisTech 22

23 MASTER REST Solar Resource Part II 45 Solar Atlas for PACA region Conclusion High resolution Solar Atlas Resolution: 200 m HelioClim-3 database (res. 4 km, period: ) Shadow effects estimated from the DEM SRTM Local calibration with ground pyranometric stations Monthly sum of global and direct irradiation on different tilted plan Uncertainties estimated from statistical analysis of the calibration residue w.r.t. pyranometric ground stations Monthly sum of global irradiation: bias < 1 %, RMSE ~ 5 % (~7 kwh/m2) Monthly sum of direct normal irradiation: bias < 1 %, RMSE ~8 % (~12.5 kwh/m2) Web-client to view the solar atlas : 46 Some available Solar Databases Solar Maps and Time series of Solar radiation NASA SSE : PVGIS : SATEL-LIGHT : SOLEMI : 3tier : Geomodel : SoDa : Bases de la future version de SoDa : Standard and interoperable Web Services W3C : WSDL OGC : WMS, WPS, etc. MINES ParisTech 23

24 MASTER REST Solar Resource Part II Other high resolution solar atlas 47 Projet Solar Med Atlas (BMU: German department of Environment) 48 Solar Databases Different time frames Long-term analysis Monitoring Forecasting Long term Season Term Short term Very Short Term T0+20 years T0+3 months T0+2 h T0 T0-15 min T0-1 day MINES ParisTech 24

25 MASTER REST Solar Resource Part II 49 Solar Databases Maps of solar resource + other GIS information potential sites / Solar potential of a region Slope from Digital Elevation Model Distances from the roads, from electricity grids, from hydrological Land uses (restricted areas, risk areas, etc.) Long term intraday time series of irradiation Power plant sizing and simulation Yield (or bankable reports) Real time local solar irradiation Production monitoring Production forecasting Typical Meteorological year 50 What is a Typical Meteorological year (TMY)? Why the TMY are used? How the TMY is generated? Other possibilities? MINES ParisTech 25

26 MASTER REST Solar Resource Part II 51 What is a Typical Meteorological Year (TMY)? Is a set of one-year time series of meteorological data: For solar conversion systems: surface solar irradiance (GHI, DHI, BHI, BNI) air temperature (T2), wind speed (WS), air relative humidity (DWT), Pressure (P) representing the typical situations encountered in a longtime (LT) period for a given location No missing data in a TMY: gap-filling method is required 52 What is a Typical Meteorological Year (TMY)? JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC MINES ParisTech 26

27 MASTER REST Solar Resource Part II 53 What is a Typical Meteorological Year (TMY)? 54 What is a Typical Meteorological Year (TMY)? Year Time (TU) Time (TU) MINES ParisTech 27

28 % % MASTER REST Solar Resource Part II Why TMY is used? 55 To convert it into production data Used in simulation software in solar energy (PVSYST, System Advisor Model SAM...) which require one year of meteorological data. Used in pre-feasibility studies of solar energy projects It can be useful for comparing two different locations even when temporal coverage of data is different How TMY is generated? 56 The cumulative distribution function (CDF) Histogram W/m Cumulative Distribution Function W/m 2 MINES ParisTech 28

29 MASTER REST Solar Resource Part II How TMY is generated? UT Day % Filkenstein-Schafer (FS) distance between CDFs δ( ) W/m 2 How TMY is generated? 58 LT of hourly time series Data-blocks of monthly meteorological datasets TMY based on the linear weighted combination of Filkenstein-Schafer distance between cumulative distribution functions Published by Hall et al. (1978) and Kalogirou (2003) Difference between CDF of LT and a particular month (for example, January) for: δ(ghi) δ (BNI) δ (T2) δ (WS) δ (DWT) Variable weight GHI 5 BNI 5 T2 4 WS 1 DWT 4 Weights are chosen depending on the application The month selected is the one which minimize the quantity: 5 δ(ghi) + 5 δ(bni) + 4 δ(t2) + 1 δ(ws) + 4 δ(dwt) MINES ParisTech 29

30 MASTER REST Solar Resource Part II 59 Other subjects related to solar resource Bankable dataset Long term satelite-based datasets of Surface Solar Irradiation (SSI) Short term on-site ground measurement Merging to long-term low uncertainty dataset of SSI Vernay et al. (2013) Beyer et al. (2012) Solar resource variability Perez et Hoff (2010) 60 Others subjects related to solar resource Solar Forecasting Inman, Pedro, Coimbra (2013) Voyant et al. (2012) MINES ParisTech 30