Outdoor PV Module Data with Focus on Spectral Irradiance in Different Climates
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1 Outdoor PV Module Data with Focus on Spectral Irradiance in Different Climates M. Schweiger 2, G. Friesen 1, U. Jahn 2 1 SUPSI, Switzerland, 2 TÜV Rheinland, Germany
2 Contents Introduction xperimental approach Spectral influence on performance Spectral irradiance in different climates Correction methods for spectral shifts Conclusion
3 Why Analysing the Spectral Irradiance? Commercial available PV modules have different spectral response (SR). Real outdoor spectrum for PV module characterization differs from AM1.5 spectrum used in the lab (IC ). Reliable spectral data for different locations is rare. Impact of spectrum on energy yield prediction is an uncertainty factor. I Photo I SC = b A i ( λ ) ( λ) a
4 SR Data versus Spectral Data AM1.5 reference spectrum defined in IC AM1.5 1 Intensity Wavelength [nm]
5 SR Data versus Spectral Data AM1.5 reference spectrum defined in IC Area normalised spectra show relative change Cologne AM1.5 Summer ( _14:00) Winter ( _12:30) 1 Intensity Wavelength [nm]
6 SR Data versus Spectral Data Low wavelength region defined by encapsulation Near band gap region specified by charge carrier lifetime AM1.5 poly c-si BC mono c-si HIT Rel. Spectral Response Wavelength [nm]
7 SR Data versus Spectral Data Low wavelength region defined by encapsulation Near band gap region specified by charge carrier lifetime AM1.5 a-si CIS CdTe CIGS poly c-si BC mono c-si HIT CIGS Rel. Spectral Response Wavelength [nm]
8 Approach Measurements in array plane, nm, every minute Identical setup in 5 different locations world-wide Calibration by TÜV Rheinland every year Factors influencing the spectrum: Clouds, AM, mounting direction, location, aerosols
9 Influence of Spectrum on Photo Current Analysis with average photon energy factor (AP) AP a = b q 1.65eV = AM1.5 e b ' Low dependency of I SC on spectrum for c-si a i Φ i I SC,Relative 1,53 1,56 1,59 1,62 1,65 1,68 1,71 1,74 a-si a-si/µc-si CIGS & c-si 1,53 1,56 1,59 1,62 1,65 1,68 1,71 1,74 Average photon energy [ev] CdTe [1] T. Betts: Investigation of Photovoltaic Device Operation under Varying Spectral Conditions, Loughborough University, 2004
10 Influence of Spectrum on Photo Current Analysis with average photon energy factor (AP) AP a = b q 1.65eV = AM1.5 e b ' Low dependency of I SC on spectrum for c-si a i Φ i I SC,Relative 1,53 1,56 1,59 1,62 1,65 1,68 1,71 1,74 Loss Top limited STC a-si a-si/µc-si CIGS & c-si 1,53 1,56 1,59 1,62 1,65 1,68 1,71 1,74 Average photon energy [ev] Gain Bottom limited CdTe [1] T. Betts: Investigation of Photovoltaic Device Operation under Varying Spectral Conditions, Loughborough University, 2004
11 Average Annual Spectrum in Cologne Annual average spectrum for Cologne almost identical to AM1.5 Long term average values not available IC _d.2, 921 W/m², 1.65 ev AVG_ , 355 W/m², 1.68 ev IC - AVG Intensity Wavelength [nm]
12 Measurements in Different Climates Data from 5 test sites since 2014: Cologne (Germany): 50 N Ancona (Italy): 43 N Tempe (Arizona): 33 N Thuwal (Saudi Arabia): 22 N Chennai (India): 13 N northern tropic 23 26'
13 Measurements in Different Climates spectral measurements Great spectral shifts within a day, maximum blue shift in summer AM1.5
14 Cloudless Days in Summer / Winter Daily spectral shifts: Pan shaped curves in summer Lid shaped curves in winter Blue shift in summer Red shift in winter Tempe more blue than Ancona AM1.5 AM1.5
15 sonnenverlauf.de India USA Italy Germany Increase of AirMass leads to red shift of spectrum (Rayleigh scattering) Lowest mean AirMass near equator Northern hemisphere: Maximum blue shift for solstice in summer (21 June) Maximum red shift for solstice in winter (21 December) Between equator and tropic: Sun is at zenith twice a year. Solar Noon Chennai: 24/25.4. & 18./19.08.
16 Correction of Spectral Influence Sophisticated monitoring of PV module performance using spectral irradiance data MM = Mess Mess Spec Spec Convert data to STC conditions Irradiance and temperature correction via IC proc. 2 a-si Spectral Mismatch (MM) correction according to IC Spectral response of irradiance sensor (Ref) and module (Spec) needed
17 Correction of Spectral Influence Sophisticated monitoring of PV module performance using spectral irradiance data MM = Mess Mess Spec Spec Convert data to STC conditions Irradiance and temperature correction via IC proc. 2 a-si Spectral Mismatch (MM) correction according to IC Spectral response of irradiance sensor (Ref) and module (Spec) needed
18 Correction of Spectral Influence Sophisticated monitoring of PV module performance using spectral irradiance data MM = Mess Mess Spec Spec Convert data to STC conditions Irradiance and temperature correction via IC proc. 2 a-si Spectral Mismatch (MM) correction according to IC Spectral response of irradiance sensor (Ref) and module (Spec) needed
19 Correction of Spectral Influence Sophisticated monitoring of PV module performance using spectral irradiance data MM = Mess Mess Spec Spec Convert data to STC conditions Irradiance and temperature correction via IC proc. 2 a-si Spectral Mismatch (MM) correction according to IC Spectral response of irradiance sensor (Ref) and module (Spec) needed
20 Correction of Spectral Influence (ΣPm/Pm,stc)/(ΣG/1000) Norway UK 0.4 Germany USA Switzerland c-si France 0.2 Jan Feb Apr May Jul Sep Oct Dec Daily Performance Ratio PR (P M ) are influenced by spectral effects PR( P m ) / P m STC = 2 GPyr /1000Wm c-si: mainly affected by thermal effects Maximum PR in winter P (ΣPmax/Pmax,stc)/(ΣG/1000) Norway UK Germany USA 0.4 Switzerland France a-si Cyprus 0.2 Jan Feb Apr May Jul Sep Oct Dec a-si: thermal effects are hided by spectral and Staebler-Wronski effect Maximum PR in summer liminate spectral effects by self-reference approach via PR (I SC )
21 Correction of Spectral Influence 1.2 a-si 1.2 a-si (ΣIsc/Isc,stc)/(ΣG/1000) Norway UK Germany USA PR(Isc)=1 0.4 Switzerland France Cyprus 0.2 Jan Feb Apr May Jul Sep Oct Dec (ΣPmax/Pmax,stc)/(ΣG/1000) Norway UK Germany USA PR(Pm) 0.4 Switzerland France Cyprus 0.2 Jan Feb Apr May Jul Sep Oct Dec Normalization of PR(P m ) with PR(I SC ): 1.2 a-si PR( I SC ) G / I SC SC, STC = 2 Pyr /1000Wm No spectral response data or spectral irradiance data needed I Norm. ΣPmax/Pmax,stc)/(ΣG/1000) norm. PR(Pm) 0.6 Norway UK Germany USA 0.4 Switzerland France Cyprus 0.2 Jan Feb Apr May Jul Sep Oct Dec
22 Conclusions No database for long term spectral irradiance measurements worldwide Measurements are cost intensive and complex Lowest mean AirMass for latitude closest to equator Blue shift of spectrum Harmonized measurement procedures for technological dependent behavior in different climates new contributions welcome
23 Thank You for Your Attention! TÜV Rheinland Test Site: Ancona
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