Design, Modeling, and Optimization of Silicon Solar Cells and Modules. Victor Moroz

Transcription

1 Design, Modeling, and Optimization of Silicon Solar Cells and Modules Victor Moroz 1

2 Outlook 2

3 Outlook 3

4 PV System Challenges Improving PV efficiency Optimizing for design performance and target reliability Reducing the effects of variation on system performance Predicting manufacturing yields Lowering production costs 4

5 Addressing Issues at All Stages Cell Module System Synopsys TCAD tools Synopsys Saber tools Design criteria Cell Level Maximize efficiency Optimize cell: contact pitches, junctions, anti-reflective coatings, etc. Design criteria Module Level Minimize effect of interconnects on performance Minimize impact of cell variation or degradation on module performance Design Criteria System Level Maximize system performance accounting for diurnal solar inclination Maximize system level efficiency delivered to the grid, including inverter system 5

6 Why Simulate Solar Cells? Source: SERIS Early generation cell (Eff ~ 17%) New generation cell (Eff > 20%) 6

7 Solar Cell Simulation Flow Input Simulation Output Process Flow Recipe Process Simulation Texture Junctions Texture Optical Data: n & k Optical Simulation External reflection Optical generation Electrical Data: SRH, Auger, BGN, Mobility Device Geometry (lifetime, doping profiles) Electrical Simulation IQE, EQE Dark & Light I-V 7

8 Outlook 8

9 Solar PV Driving Force : $/W (about 1.2GW shipment) R&D cost ~ 1.5% (thousands) Net revenues $2,000,000 Cost of revenues $1,320, % Gross profit $680, % Operating expenses SG&A $160, % R&D $30, % Total operating expenses $190, % Operating income $490, % Cost Watt Production cost ($) = ~ Output power (W) Process Cost Conversion efficiency 9

10 Conversion Efficiency (E) Efficiency vs Profit 26% 24% p-type c-si Lab Impact of DE = 0.5% 22% E 0 =20% -> E=20.5% 20% DE/E 0 = 2.5% 18% 16% Pilot Production 2.5% more power output 2.4% less cost per Watt 2.4% more gross profit 14% % more gross profit = $1.32B * 2.4% = $32M 1 About the same as R&D budget ($30M ) 1 Assume the same cost per unit module and wattage sales 10

11 Outlook 11

12 Measured Texture 12 Source: AMAT

13 Simulated Surface Texture Zoom-in 20um * 20um surface 13

14 Behavior of UV light (0.3um Wavelength) Bounced out ray Incoming ray Absorbed ray 12um Absorption in Si happens within one micron from surface Typically one or two reflection events Only top surface matters 14

15 Behavior of Visible Light (l=0.6um) Bounced out ray (reflectance) Incoming ray 12um Bounced out rays (transmittance) Absorbed rays Absorption in Si happens within tens of microns Several reflection events 15

16 Behavior of Infrared Light (l=0.9um) Bounced out rays Incoming ray 12um Bounced out rays Absorbed rays Absorption in Si happens within hundreds of microns Dozens of reflection events Both the top and the rear surfaces matter 16

17 Reflectance, % Reflectance Curves: Texture is Good flat/flat textured/flat textured/textured bad good Wavelength, um 17

18 Reflectance, % Reflectance Curves: Nitride is Good textured/textured textured+nitride/textured Ideal! Wavelength, um 18

19 Reflectance, % Model Accuracy 60 Textured Si, measured data 50 Textured+SiN, measured data 40 Textured Si, model Textured+SiN, model Calibrated model captures Si texture and nitride ARC film Wavelength, um 19 Si data from AMAT

20 Outlook 20

21 c-si Solar Cell with Rear Point Contacts Rear point contacts (Al): Si-Al interface Front contact stripe (silver) Rear surface not covered by contact: Si-Nitride interface 21

22 Rear Point Contact Optimization Increasing Rear Point Contact Area is GOOD! Current Crowding Contact Resistance Bulk Recombination Doping Silicon quality Cell size Contact pitch Rear Point Contact Design Increasing Rear Point Contact Area is BAD! Optical Reflectivity Surface Recombination Rates 22

23 Junction Optimization Higher doping in n layer is GOOD! Higher doping increases conduction Junction depth Top Surface p-n Junction Design Higher doping in n layer is BAD! Higher doping increases recombination 23

24 Modeling Major Effects Optical Reflectivity Surface Recombination Contact Resistance Bulk Recombination Current Crowding Shaded area under top contact 24

25 Current Crowding Pattern Current crowding is observed in both lateral directions, which makes it a 3D effect 25

26 Rear Contact Optimization Best design with > 1% efficiency advantage solar cell design with full backside coverage 26

27 Cell Efficiency (%) Junction Optimization Resistance Recombination Xj=0.1um Xj=0.2um Xj=0.4um Xj=0.6um Xj=0.8um Xj=1.0um 1.E+18 1.E+19 1.E+20 1.E+21 Peak Doping Concentration (cm -3 ) Shallow junction Deep junction 27

28 Cell Efficiency (%) Junction Optimization 22.0 Improved junctions Xj=0.1um Xj=0.4um Xj=0.6um Xj=0.8um Industry standard POCl junctions E+18 1.E+19 1.E+20 1.E+21 Peak Doping Concentration (cm -3 ) 28

29 Outlook 29

30 System Integration & Optimization Simulation provides integrated test, validation and optimization environment for all aspects of the system: Environment Power Electronics Control System & Algorithms 30

31 Modules to Arrays and Systems Design problem: Thermal Effects on Module/Array performance and Maximum Power Point Analysis of faults on strings within the array Photovoltaic Module Performance Verification at Different Cell Temperatures Measurement of MPPT at Different Temperatures 31

32 Summary 32