Preliminary results on modelling the monochromatic beam and circumsolar radiation under cloud-free conditions in desert environment

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Preliminary results on modelling the monochromatic beam and circumsolar radiation under cloud-free conditions in desert environment Yehia EISSA a,b, Philippe BLANC a, Lucien WALD a, Hosni GHEDIRA b a MINES ParisTech, PSL Research University, O.I.E. Centre Observation, Impacts, Energy, Sophia Antipolis, France b Masdar Institute, Research Center for Renewable Energy Mapping and Assessment, Abu Dhabi, UAE 1

Introduction Introduction Data sets and methods Results and discussion Conclusions The direct normal irradiance (DNI) Youva Aoun, 2014. Circumsolar normal irradiance: CSNI Direct normal irradiance from solar disc only: DNI S 2

Introduction The direct normal irradiance (DNI) The direct normal irradiance, abbreviated in DNI, is the radiant flux per unit area normal to the Sun rays received from a small solid angle centered to the solar disc (ISO-9488, 1999; WMO, 2010). The SI unit of irradiance is W m 2. Angular radius of solar disc: δ S = 0.266 ± 1.7% (Ω s = 67.7 μsr). What is the value of this small solid angle? No value in the ISO definition of the DNI The WMO recommends a value between Ω = 6 msr (α = 2.5, for higher quality pyrheliometers) and Ω = 24 msr (α = 5 ) Sun Circumsolar region Ω S = 67.7 μsr; δ S = 0.266 Ω = 6 msr; α = 2.5 Ω = 24 msr; α = 5 Pyrheliometer thermopile 3

Introduction Concentrated solar technologies Concentrated solar technologies (CST) Concentrated solar thermal electric (CSTE): sensitive to broadband DNI Concentrated photovoltaics (CPV): sensitive to a specific interval of the spectrum System α ( ) Parabolic trough CSTE ~ 0.7 to 0.8 Solar tower CSTE < 1.8 Linear Fresnel CSTE ~ 1 Parabolic dish CSTE < 1.6 Different CPV systems ~ 0.5 to 5 More common pyrheliometers 2.5 Picture of the parabolic troughs of Shams 1, a CSTE power plant located in the UAE. Yehia Eissa, 2012. Parallel beams reflected onto the receiver (Richter et al., 2009). 4

Introduction Reporting DNI measurements In the framework of the Task 46 Solar Resource Assessment and Forecasting of the Solar Heating and Cooling (SHC) program of the International Energy Agency (IEA) an article was very recently published particularly on the definition of the DNI. They recommend to report: The measured DNI Viewing angles of the measuring instrument The sunshape and circumsolar contribution Blanc, P., Espinar, B., Geuder, N., Gueymard, C., Meyer, R., Pitz-Paal, R., Reinhardt, B., Renne, D., Sengupta, M., Wald, L., Wilbert, S., 2014. Direct normal irradiance related definitions and applications: the circumsolar issue. Solar Energy 110, 561 577. doi: http://dx.doi.org/10.1016/j.solener.2014.10.001. 5

Introduction Reporting DNI measurements DNI S DNI(α) CSNI DNI S : DNI from the extent of the solar disc only, noted B n Sun CSNI: circumsolar normal irradiance, noted CS n (δ, α) DNI(α): DNI up to α, noted B n (α) CSR: circumsolar ratio, noted CSR(α) Examples of the sunshape plotted in the log-log scale for: clear conditions, intermediate conditions and turbid conditions. Measurement campaigns of the profile of solar radiance are limited in time and space. 6

Introduction Objective To investigate if the spectral aerosol optical properties of AERONET are sufficient for an accurate modelling of the monochromatic DNI S and CSNI under cloud-free conditions in a desert environment. Why monochromatic? Why a desert environment? Why cloud-free conditions? 7

Data sets and methods Introduction Data sets and methods Results and discussion Conclusions Study area and measuring instruments A picture of the SAM instrument in Abu Dhabi (image from: http://www.visidyne.com/sam/sam_data_mas_files/ima ge002.jpg). The Cimel 318 Sun photometer used in the AERONET stations (image from: http://www.cimel.fr/?instrument=photometre-multi-bandes-soleilciel). 8

Data sets and methods Data sets B n,λ Sun = f(τ a,λ ) L λ (ξ) = f(τ a,λ, P a,λ (ξ), ω a,λ ), CS n, (, ) 2 L ( )sin( ) d Quality control procedures have been defined and applied on the SAM radiance measurements Not available Available Mean value Data set # of samples AERONET (Level 2.0) SAM DS1 10285 DS2 3723 DS3 1066 DS4 491 DS5 425 DS6 138 τ a,λ tcwv P a,λ (ξ) g λ ω a,λ τ a,λ L λ (ξ) AERONET Direct Sun Algorithm AERONET Inversion the AERONET τ a,λ is available at: 340 nm, 380 nm, 440 nm, 500 nm, 675 nm, 870 nm, 1020 nm, 1640 nm the AERONET ω a,λ and P a,λ (ξ) are available at: 440 nm, 675 nm, 870 nm, 1020 nm the SAM τ a,λ is available at: 670 nm the SAM L λ (ξ) is available at: 670 nm 9

Data sets and methods Aerosol optical depth SAM a, 0.8 0.6 0.4 0.2 2978 samples mean = 0.278 bias = 0.013 (5%) RMSE = 0.016 (6%) CC = 0.999 y = x LS: y = 0.991x + 0.016 PCA: y = 0.992x + 0.016 Robust: y = 0.992x + 0.016 0 0 0.2 0.4 0.6 0.8 AERONET a, Fitting subset: 80% of samples of DS2. SAM τ a,λ : retrieved within the extent of the solar disc AERONET τ a,λ : Sun photometer: α 0.6 (CSNI is intercepted within the aperture) Corrected AERONET a, 0.8 0.6 0.4 0.2 745 samples mean = 0.278 bias = 0.000 (0%) RMSE = 0.009 (3%) CC = 0.999 y = x LS: y = 1.002x - 0.000 PCA: y = 1.003x - 0.001 Robust: y = 1.001x - 0.001 0 0 0.2 0.4 0.6 0.8 SAM a, Testing subset: remaining 20% of samples of DS2. Data set # of samples AERONET (Level 2.0) SAM DS2 3723 τ a,λ tcwv P a,λ (ξ) g λ ω a,λ τ a,λ L λ (ξ) 10

Data sets and methods Aerosol single scattering albedo 70 60 mean mean +/- 1 mean +/- 2 Number of observations 50 40 30 20 10 0 0.88 0.9 0.92 0.94 0.96 0.98 1 a, Histogram of ω a,λ of DS4. L λ (ξ) ω λ : mean value of ω a,λ = 0.954 used Data set # of samples AERONET (Level 2.0) SAM τ a,λ tcwv P a,λ (ξ) g λ ω a,λ τ a,λ L λ (ξ) DS4 491 11

Data sets and methods Aerosol phase function P a, ( ) (log-scale) 10 2 10 1 10 0 10-1 10-2 0 6 20 40 60 80 100 120 140 160 180 L λ (ξ) P λ (ξ) AERONET Two Term Henyey-Greenstein Henyey-Greenstein ( o ) P TTHG P TTHG 2 2 P HG (, g) (1 g ) /(1 g 2g cos( P HG (, g) (, c1, c2, c3) c1phg (, c2) (1 c1 ) PHG (, c3) l 0 l 0 (2l 1) g (, c1, c2, c3) (2l 1)( c1c2 (1 c1) c3 ) pl (cos( )) l l p (cos( )) l 1 d p l ( x) ( x 2 1) l l (2 l!) dx c 1, c 2 and c 3 fitted using the nonlinear leastsquares Levenberg-Marquardt method l l l )) 1.5 12

Data sets and methods Parameterizations of the radiative transfer codes τ a,λ at 670 nm tcwv libradtran ω a,λ aerosol phase function: desert type aerosol from the OPAC library HG phase function moments of the TTHG phase function τ a,λ at 550 nm tcwv aerosol model: DESERT_MAX SMARTS ALPHA1 (Ångström wavelength exponent for wavelength less than 500 nm), ALPHA2 (Ångström wavelength exponent for wavelength greater than 500 nm), OMEGAL (the aerosol single scattering albedo), and GG (the asymmetry parameter) 13

Results and discussion Introduction Data sets and methods Results and discussion Conclusions DNI S,λ SMARTS B Sun n, (W m-2 m -1 ) 1600 1400 1200 1000 800 600 400 200 3723 samples mean = 863.9 W m -2 m -1 bias = 8.5 W m -2 m -1 (1%) RMSE = 46.7 W m -2 m -1 (5%) CC = 0.987 y = x LS: y = 0.98x + 28.0 PCA: y = 0.99x + 16.6 Robust: y = 0.99x + 12.2 0 0 200 400 600 800 1000 1200 1400 1600 SAM B Sun n, (W m-2 m -1 ) libradtran B Sun n, (W m-2 m -1 ) 1600 1400 1200 1000 800 600 400 200 3723 samples mean = 863.9 W m -2 m -1 bias = 4.6 W m -2 m -1 (1%) RMSE = 46.9 W m -2 m -1 (5%) CC = 0.986 y = x LS: y = 0.97x + 27.9 PCA: y = 0.99x + 16.2 Robust: y = 0.98x + 12.3 0 0 200 400 600 800 1000 1200 1400 1600 SAM B Sun n, (W m-2 m -1 ) Data set # of samples AERONET (Level 2.0) SAM DS2 3723 τ a,λ tcwv P a,λ (ξ) g λ ω a,λ τ a,λ L λ (ξ) 14

Results and discussion CSNI λ RTM Aerosol optical properties Mean Bias RMSE CC W m 2 μm 1 W m 2 μm 1 % W m 2 μm 1 % libradtran τ a,670 nm ; OPAC desert type aerosol 84.3 28.3 34 33.9 40 0.848 SMARTS libradtran τ a,550 nm ; DESERT_MAX aerosol model 84.3 39.0 46 45.5 54 0.755 τ a,670 nm ; mean ω a,675 nm ; HG phase 84.3 63.8 76 68.2 81 0.849 function: g 675 nm SMARTS τ a,550 nm ; mean ω a,675 nm ; g 675 nm 84.3 61.6 73 66.6 79 0.833 libradtran τ a,670 nm ; mean ω a,675 nm ; TTHG phase function 84.3 15.7 19 18.8 22 0.944 Data set # of samples AERONET (Level 2.0) SAM DS5 425 τ a,λ tcwv P a,λ (ξ) g λ ω a,λ τ a,λ L λ (ξ) 15

Results and discussion CSNI λ : libradtran TTHG phase function libradtran CS n, ( = 0.64 o, = 6 o ) (W m -2 m -1 ) 200 160 120 80 40 425 samples mean = 84.3 W m -2 m -1 bias = -15.7 W m -2 m -1 (-19%) RMSE = 18.8 W m -2 m -1 (22%) CC = 0.944 y = x LS: y = 0.80x + 1.4 PCA: y = 0.84x - 1.9 Robust: y = 0.82x + 0.9 0 0 40 80 120 160 200 SAM CS n, ( = 0.64 o, = 6 o ) (W m -2 m -1 ) Data set # of samples AERONET (Level 2.0) SAM DS5 425 τ a,λ tcwv P a,λ (ξ) g λ ω a,λ τ a,λ L λ (ξ) 16

Conclusions Introduction Data sets and methods Results and discussion Conclusions Up to now the work has been presented only in terms of monochromatic irradiance values, the purpose was to: check if AERONET data could be used to accurately model the monochromatic DNI S and CSNI to compare the libradtran and SMARTS modelled values with reference measurements from SAM The best configuration tested for modelling the DNI S and CSNI: the AERONET τ a,670 nm is corrected with respect to the SAM τ a,670 nm the AERONET P a,λ (ξ) is expressed as a TTHG phase function and is decomposed as a series of Legendre polynomials The assessment of the DNI resource, in particular for CSTE systems, requires broadband irradiance values in the interval [0.3 μm, 4 μm]: the follow-up is to devise a model based on these findings to estimate the broadband DNI S and CSNI complying with the recommendations of the Task 46 of the SHC program of the IEA when reporting DNI measurements 17