Characterization and Analysis of Photovoltaic Modules and the Solar Resource Based on In-Situ Measurements in Southern Norway Georgi Hristov Yordanov Supervisor: Prof. Ole-Morten Midtgård (NTNU) Co-supervisor: Prof. Lars Einar Norum (NTNU)
OUTLINE • Aims and objectives • Context and background • Research questions • Experimental setups • Solar resource in Grimstad • PV performance analysis and modeling • Contributions to PV industry • Scientific contributions 2
AIMS AND OBJECTIVES • Investigate the PV potential in S. Norway • Explain with device physics the observed performance differences among c-Si PV • To achieve this, one needs to: 1. Study the local solar resource 2. Measure, analyze and model PV performance 3. Measure, analyze and model I-V curves 4. Identify quantitative links between performance and I-V curve parameters 3
HIGH LATITUDE: 58° 20’N 4
COASTAL CONTEXT 5
SEA TO THE SOUTH-EAST 6
PRIOR STUDY 1 Olseth and Skartveit , “The solar radiation climate of Norway”, Solar Energy 37 (1986) 423; GHI ≈ 1050 kWh/m 2 /yr 7
PRIOR STUDY 2 Midtgård et al., “A qualitative examination of performance and energy yield of photovoltaic modules in Southern Norway ”, Renewable Energy 35 (2010) 1266. 8
SOLAR RESOURCE IN 2005 Ibid. 10 % more than predicted by the EU PVGIS 9
η VS. IRRADIANCE Ibid. The effects from G and T not separated. 10
I-V CURVE RESOLUTION Ibid. Poor-resolution I-V; Every 20 min; 73 % up 11
PRIOR STUDY 3 Huld et al., “A power -rating model for crystalline silicon PV modules”, Solar Energy Mat. and Solar Cells 95 (2011) 3359. T MOD = 40°C 12
PV PERFORMANCE MODEL η REL = η ( G′ , T′ )/ η STC Relative efficiency: G ′ = G / G 0 , G 0 = 1000 W/m 2 ; T′ = T – 25 ° C • An empirical performance model was proposed in Huld et al., “Mapping the performance of PV modules, effects of module type and data averaging”, Solar Energy 84 (2010) 324: 2 2 2 k G k G T k k G k G k T 1 ln ' ln ' ' ln ' ln ' ' REL 1 2 3 4 5 6 • k 3 – the rel. temp. coeff. of P MAX at G = G 0 13
RESEARCH QUESTIONS • Seasonal distribution of solar resource in 2011 vs. 2005 and PVGIS? Maximal year-to-year variability? Maximal overirradiances? Burst durations? Physical cause? Effects of discrete sampling? Optimal azimuthal orientation of PV? Energy lost due to clouds? Accuracy « 3 % by using I SC of many PV modules? • How individual I-V curve parameters such as R S and n affect η REL at different G ? • How can a PV system builder recognize the best- performing modules on the market? • How can a PV manufacturer design cells which make best-performing modules? 14
THE NEW TEST SETUP Altitude ≈ 60 m a.s.l. Tilt angle = 39° ± 1° 15
THE NEW TEST SETUP 2 16
THE NEW SOFTWARE 17
THE NEW I-V CURVES 18
MPP TRACKING 19
2 nd SETUP IN S. NORWAY Tilt angle = 60°; Mutual shadowing 20
IRRADIANCE SENSORS SOLDATA 80SPC KIPP & ZONEN CMP 3 21
IRRADIATION IN 2011 • 1200 kWh/m 2 – 15 % more than in PVGIS (long-term!) • As in 2005, very sunny April, March and January 22
STATISTICS 2011 23
YEAR-TO-YEAR VARIABILITY GHI data from nearby Landvik; 20.5 % Max. (y2y); σ = 5.5 % 24
EFFECTS OF DISCRETE SAMPLING 1.6 % extra uncertainty (annual) if sampling every 20 min 0.33 % for 1-min sampling (with a slow sensor) 25
CLOUD ENHANCEMENT 26
FORWARD SCATTERING 27
FORWARD SCATTERING 2 28
MIE PHASE FUNCTION Strongly anisotropic • Depends on droplet size, wavelength, etc. • Important to e.g. 3D gaming graphics programmers • LOG SCALE! 49% 49% 1% 29
SENSOR RANGE MATTERS! 30
TYPICAL DURATIONS 31
LONGEST DURATIONS Total no. of events: ≈ 13,000 32
RESULTS FROM 2012 11 May: 1521 W/m 2 ; 10 June: 1528 W/m 2 33
PRIOR STUDIES Emck & Richter (2008): 1832 W/m 2 (equatorial Andes) • T. Buseth (Elkem Solar AS, 2011): >1800 W/m 2 (Kenya) • Hansen et al. (2010): GHI, >1500 W/m 2 (New Mexico) • Luoma et al. (2012): Tilted, >1500 W/m 2 (California) • Zehner et al. (2010, 2011): Attributed to reflection • Parisi et al. (2004): Cloud-enhanced UV skin cancer ?!! • Overirradiances impose range requirements on sensors • Calculation of UV doses and UV index should account for • cloud enhancement!!! 34
13,000 BEWARE Danes OF develop UV skin !!!!!!! cancer each year 35
CLOUD ‘RESOURCE’ A hypothetical cloud-free year: 2130 kWh/m 2 ; 44 % lost due to clouds in the year 2011 36
OPTIMAL PV AZIMUTH Averaged all daily irradiance profiles from 2011; ‘Center of mass’: 13:05 p.m. 10-15 ° W from S 37
PV PERFORMANCE: ANALYSIS AND MODELING Relative efficiencies at 25°C of 10 c-Si modules; Fitted performance model coefficients k 1 through k 6 38
LINKING PERFORMANCE TO DEVICE PHYSICS I nN v R I M STC , S 0 S M STC k R , k 2 S 1 V 2 V M STC , M STC , • Assuming 1-exponential I-V curve model, no shunts • n – ideality factor; N S – no. of cells in series; v 0 =k B T 0 /q (thermal voltage at 25°C); R S – series resistance; (V M,STC ,I M,STC ) – MPP at STC • k 1 determines the slope of η REL (G,25°C) at G=G 0 and thus the behavior at intermediate irradiances • k 2 determines the low-light performance; always < 0 • Very good agreement between fitted and theoretical k 1 39
CONTRIBUTIONS TO PV INDUSTRY • Quantitative and qualitative guidelines for design and selection of PV devices with better performance • If modules with screen-printed c-Si cells are chosen, PV system builders should generally go for 2 busbars, not 3 • PV module makers have 2 new methods to monitor R S 40
A RECENT RECOGNITION • By: Bosch Solar Energy AG, Germany • Referred to: Yordanov et al. (2010), 25 th EUPVSEC 41
THE RESULT (AS OF 5 DEC) 42
SCIENTIFIC CONTRIBUTIONS • A methodology for in-situ testing of PV modules • A very detailed analysis of the local solar resource • Identification of peaks > 1500 W/m 2 in S. Norway • Two new methods for evaluation of I-V parameters • 1 improved and 1 novel differential technique • An equation for Equivalent Cell Temperature (ECT) calculation from V OC for PV devices with variable ideality factors which are not covered in IEC 60904-5 • Showed limits of applicability of classic I-V curve models • k 1 ..k 6 for 8 c-Si and 1 CIGS modules; equations for k 1 , k 2 43
2 NEW METHODS TO EVALUATE R S , n AND I 0 44
IMPROVED AND NOVEL DIFFERENTIAL TECHNIQUES 45
MUCH BETTER IRRADIANCE ACCURACY Self-referenced irradiance from I SC of many new PV modules uncertainty ≤ 1 % ! Corrections! 46
SOME CITATIONS OF MY PAPERS Verma et al., 38 th IEEE PVSC (2012) p. 002372 C.W. Hansen, Sandia Report SAND2012-8417 Attivissimo et al., IEEE Trans. Instrum. Meas. (2012) p. 1334 Stošović et al., Proc. Small Syst. Simul. Symp. (2012) p. 28 Nuotio and Kernahan, US Patent 8,239,149, 2012 Kernahan - US Patent 8,093,754, 2012 Polverini et al., Prog. Photovolt: Res. & Appl. 20 (2012) p. 650 A.K. Das, Solar Energy 86 (2011) p. 26 Lee et al., Int. J. Photoenergy 2012 , 11 pp. Lamont and El Chaar, Renewable Energy 36 (2011) p. 1306 Zimmermann and Edoff, IEEE J. Photovolt. 2 (2012) p. 47 47
THANK YOU! 48
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