2015 PV MARKET OUTLOOK
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1 15 June PV MARKET OUTLOOK ASEF, Manila Xiaoting Wang
2 PV NEW BUILD BY YEAR, HISTORICAL AND FORECAST TO 2017 (CONSERVATIVE) 55.5GW 61.0GW 61.3GW 40.0GW 45.0GW 28.5GW 30.7GW 18.2GW 6.6GW 7.7GW Western Europe Eastern Europe Japan USA China India Rest of World Note: A conservative and optimistic forecast has been developed for each country. It is unlikely that all countries will come in at the conservative or optimistic end, so for the global forecast, conservative is (sum of conservative country forecasts + 25%*(sum of optimistic conservative forecasts). Global optimistic forecast is sum of conservative country forecasts + 75%*(sum of optimistic conservative forecasts). 1
3 CHINA PV DEMAND (GW) CONSERVATIVE OPTIMISTIC 420% 38% 258% 1% 23% 9% 10% 420% 38% 258% 1% 46% 9% 15% e 2016e 2017e transmission-grid-connected distribution-grid-connected e 2016e 2017e transmission-grid-connected distribution-grid-connected 2
4 JAPAN PV DEMAND (GW) CONSERVATIVE OPTIMISTIC kW kW 1MW kW kW 1MW+ 3
5 US PV DEMAND (GW) CONSERVATIVE OPTIMISTIC Residential Commercial Utility Residential Commercial Utility 4
6 PV NEW BUILD BY YEAR, HISTORICAL AND FORECAST TO 2017 (OPTIMISTIC) 67.9GW 69.7GW 61.4GW 40.0GW 45.0GW 28.5GW 30.7GW 18.2GW 6.6GW 7.7GW Western Europe Eastern Europe Japan USA China India Rest of World Note: A conservative and optimistic forecast has been developed for each country. It is unlikely that all countries will come in at the conservative or optimistic end, so for the global forecast, conservative is (sum of conservative country forecasts + 25%*(sum of optimistic conservative forecasts). Global optimistic forecast is sum of conservative country forecasts + 75%*(sum of optimistic conservative forecasts). 5
7 SUPPLY CURVE FOR POLYSILICON, 2015 Estimated variable cost ($/kg) Tokuyama Malaysia II Hankook Silicon SunEdison FBR Renesola China Silicon 2015 demand 56-61GW Hanwha Chemical REC Siemens, Japanese 15 REC FBR GCL Siemens Wacker Nuchritz, Tennessee OCI Hemlock Michigan TBEA Wacker Burghausen Other Chinese DAQO 10 SMP FBR 5 GCL FBR , , , , , , , ,000 Potential production in 2015 (tonnes) Note: Variable cost includes processing cost and SG&A; depreciation is excluded demand estimate is GW. Assumes 6% of the demand will be supplied by thin-film modules; 24% by mono modules with polysilicon consumption of 4.52g/W; 70% by multi silicon modules with a polysilicon consumption of 5.0g/W; electronics market is estimated at 30,000 tonnes. 6
8 DEMAND AND SUPPLY FOR PV MODULES, E (MW/YEAR) 90 Historical Future Current effective cell manufacturing capacity - at least 66GW Supply - crystalline silicon Supply - thin-film silicon Supply - thin film non-silicon Demand - conservative Demand - optimistic 7
9 EBIT MARGINS OF QUOTED PV COMPANIES BY APPROXIMATE VALUE CHAIN POSITION, Q % 20% 10% 0% CSIQ Sungrow WCH Silicon Risen REC Solar FSLR Sunflower Daqo Tainergy SPWR Jinko Neo JA Trina ENPH OCI Eging Etrion -10% -20% -30% Renesola AEIS SUNE Silicon Gintech Motech Yingli SMA Solarworld REC Silicon HSOL Akcome Danen Develop, Inverters/ Silicon Wafers Cells Modules Develop/Own Own, BoP Operate $500 Q EMEA AMER APAC m 8
10 ALTMAN-Z SCORES OF QUOTED PUREPLAY PV MANUFACTURERS, AS OF Q OR Q FILING REC Solar, 4.34 First Solar, 3.60 S-Energy, 2.11 CSIQ, 1.99 SunPower, 1.93 Trina, SolarWorld, Hareon, 1.01 Jinko, 0.91 GCL-Poly, 0.84 Renesola, 0.41 SunEdison, Hanwha, Yingli, China US Europe South Korea REC Silicon,
11 PLANNED CAPACITIES OF LARGE MODULE COMPANIES BY END OF 2015 (MW) Trina Solar Yingli Jinko Solar JA Solar Canadian Solar Hanwha Talesun Suntech Kyocera SunPower Risen SolarWorld BYD Chint REC Solar Hareon Eging Renesola ZNShine CSUN HT-SAAE ET Solar 0 1,000 2,000 3,000 4,000 5,000 Module Cell Source: Company files, estimates, enquiries, Bloomberg New Energy Finance 10
12 GAP BETWEEN MODULE AND CELL CAPACITIES FOR LARGE COMPANIES BY END OF 2015 (MW) -1, ,000 1,500 2,000 Canadian Solar Jinko Solar Trina Solar Suntech ZNShine Kyocera Yingli Talesun Renesola Risen Chint CSUN ET Solar REC Solar HT-SAAE Eging SolarWorld BYD Hareon Hanwha SunPower JA Solar Gap Source: Company files, estimates, enquiries, Bloomberg New Energy Finance 11
13 PROPORTION OF TOTAL SHIPMENTS SENT TO INTERNAL PROJECTS BY CHINESE MODULE COMPANIES, 2014 AND 2015 ESTIMATE 17% 20% 18% 17% 13% 10% 9% 8% 9% 4% Jinko Canadian Solar Trina Yingli JA Solar E Source: Company files, estimates, Bloomberg New Energy Finance 12
14 ESTIMATED INTERNATIONAL CAPACITIES OWNED BY OR CHINESE COMPANIES AND HANWHA Q CELLS BY 2015 Canada: Canadian Solar M500 Germany: Hanwha Solar C230 M130 Chint M200 Turkey: CSUN C100 M300 South Africa: JA Solar M150 Znshine M150 Jinko M120 South Korea: CSUN C200 Hanwha Solar M230 Thailand: Trina C700 M500 Talesun C500 M500 Malaysia: Hanwha Solar C1300 M800 Jinko C500 M450 JA Solar C400 Singapore: Bluestar (REC Solar) C810 M1300 Note: C and M stand for cell and module capacities, respectively. Hanwha SolarOne is considered as a Chinese manufacturer since its headquarter is set in China although Korean Hanwha Chemical is the largest shareholder. Hanwha SolarOne was merged with Hanwha Q Cells in February
15 GLOBAL PV CAPEX BENCHMARK, UTILITY-SCALE, $/W (DC) Module Inverter Balance of plant EPC Other Note: Every PV project is different and has different costs; this is a typical buildup, from quotes from developers and EPCs, intended as a global benchmark. 14
16 LEARNING CURVES OF C-SI AND THIN FILM MODULES 100 Cost per W (2013 $) ,000 10, ,000 1,000,000 Experience curve Chinese c-si module prices (BNEF) Q Historical prices (Maycock) Thin-film experience curve Cumulative capacity (MW) 15
17 C-SI MODULE COST FORECAST FOR 2015 (US CENT/W) Module 2015 Polysilicon Polysilicon to wafer Wafer to cell Cell to module Module
18 DRIVERS OF COST REDUCTIONS ALONG THE C-SI VALUE CHAIN (US CENT/W) POLYSILICON POLYSILICON TO WAFER Cheaper poly-si Thinner cells Higher effciency Diamond saw Higher efficiency 2025 WAFER TO CELL CELL TO MODULE Materials saving Higher efficiency Cheaper materials Higher 2025 efficiency 17
19 PATHWAY TO HIGH EFFICIENCY MULTI C-SI SOLAR CELLS (%) P-type multi Al-BSF 4 or 5 BB Black silicon Rear passivation P-type multi PERC 18
20 C-SI MODULE PRODUCTION COSTS AND EFFICIENCIES, H (US /W, %) Multi Al-BSF Multi PERC Mono Al-BSF Mono PERC PERT Mono PERL % 0.0% 16.0% 16.5% 17.0% 17.5% 18.0% 18.5% 19.0% 19.5% 20.0% 20.5% 21.0% HIT IBC 19
21 C-SI MODULE COST FORECAST (US CENT/W) % gap 67% gap P-type Multi P-type Mono N-type PERT N-type HIT N-type IBC
22 MARKET SHARE FORECAST OF DIFFERENT C-SI SOLAR CELL TECHNOLOGIES P-type multi Al-BSF 74% 22% 0% P-type multi PERC 3% 41% 20% P-type mono Al-BSF 14% 7% 0% P-type mono PERC/L 3% 20% 40% N-type mono IBC 3% 4% 6% N-type mono HIT 2% 3% 9% N-type mono PERT 1% 2% 25% 21
23 COPYRIGHT AND DISCLAIMER This publication is the copyright of Bloomberg New Energy Finance. No portion of this document may be photocopied, reproduced, scanned into an electronic system or transmitted, forwarded or distributed in any way without prior consent of Bloomberg New Energy Finance. The information contained in this publication is derived from carefully selected sources we believe are reasonable. We do not guarantee its accuracy or completeness and nothing in this document shall be construed to be a representation of such a guarantee. Any opinions expressed reflect the current judgment of the author of the relevant article or features, and does not necessarily reflect the opinion of Bloomberg New Energy Finance, Bloomberg Finance L.P., Bloomberg L.P. or any of their affiliates ("Bloomberg"). The opinions presented are subject to change without notice. Bloomberg accepts no responsibility for any liability arising from use of this document or its contents. Nothing herein shall constitute or be construed as an offering of financial instruments, or as investment advice or recommendations by Bloomberg of an investment strategy or whether or not to "buy," "sell" or "hold" an investment. 22
24 MARKETS Renewable Energy Energy Smart Technologies Advanced Transport Gas Carbon and RECs SERVICES Americas Service Asia Pacific Service EMEA Service Applied Research Events and Workshops Unique analysis, tools and data for decision-makers driving change in the energy system Xiaoting Wang
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