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India Wind Outlook Towards 2022 Looking beyond headwinds Disclaimer Copyright May 2020 This document.

2020-09-18 38页 5星级

2020年风电技术市场报告 - Berkeley Lab（英文版）（87页）.pdf

ELECTRICITYMARKETS ERCOT: 19.9%; MISO: 8.5%; CAISO: 6.9%; PJM: 3.0%; ISO-NE: 2.9%; NYISO: 2.8% Texas3,938Texas28,871Iowa41.9%Kansas53.5% Iowa1,739Iowa10,201Kansas41.4%Iowa53.1% Illinois541Oklahoma8,173Oklahoma34.6%North Dakota51.1% South Dakota506Kansas6,128North Dakota26.8%Oklahoma45.3% Kansas475California5,942South Dakota23.9%New Mexico27.4% North Dakota473Illinois5,350Maine23.6%Nebraska24.7% Michigan286Minnesota3,843Nebraska19.9%Wyoming24.1% New Mexico221Colorado3,762New Mexico19.4%South Dakota23.8% Oregon201North Dakota3,628Colorado19.2%Texas20.6% Minnesota167Oregon3,423Minnesota19.0%Maine20.4% Nebraska160Washington3,085Texas17.5%Colorado19.4% California133Indiana2,317Vermont16.4%Minnesota17.0% Oklahoma100Michigan2,188Idaho16.1%Montana15.4% Pennsylvania90Nebraska2,132Oregon11.5%Oregon15.0% Colorado59New York1,987Wyoming9.8%Idaho11.2% New Hampshire29New Mexico1,953Montana8.5%Illinois10.1% Massachusetts10Wyoming1,589Illinois7.6%Washington8.6% Ohio9South Dakota1,525Washington7.3%Vermont7.1% Alaska1Pennsylvania1,459California6.8%Indiana6.4% Idaho973Indiana6.0%Hawaii6.3% Rest of U.S.0Rest of U.S.7,062Rest of U.S.1.1%Rest of U.S.1.6% Total9,137Total105,591Total7.2%Total8.0% Installed Capacity (MW)2019 Wind Generation as a Percentage of: Annual (2019)Cumulative (end of 2019)In-State GenerationIn-State Sales Source: AWEA WindIQ, EIA 13Interactive data visualization: https:/emp.lbl.gov/wind-energy-growthInteractive data visualization: https:/emp.lbl.gov/wind-energy-growth Online wind hybrid / co-located projects of various configurations 14 Sources: EIA 860 2019 Early Release, Berkeley Lab Online Wind Hybrid / Co-located Projects Data on subset of the hybrid / co-located project configurations: end of 2019 Sources: EIA 860 2019 Early Release, Berkeley Lab Note: Not included in figure are 54 other hybrid / co-located projects with other configurations; details on those projects are provided in the underlying data file. Storage ratio defined as total storage capacity divided by total generation capacity within a type. Duration defined as total MWh of storage divided by total MW of storage within a type. 15 Most wind hybrid / co-located projects are Wind Storage (located in PJM and ERCOT), with storage having limited duration to serve ancillary services markets There are far fewer other wind hybrid / co-located configurations of significant size # projectsTotal capacity (MW)Storage ratioDuration (hrs) WindPVFossilStorage PV Storage40881.6169.119%2.6 Wind Storage131,289.9183.614%0.6 Wind PV Storage2215.820.734.315%0.4 Fossil Storage102,413.691.04%0.9 Wind PV6535.3211.50.0n/an/a 05001000150020002500 Wind PV Fossil Storage Interactive data visualization: https:/emp.lbl.gov/online-hybrid-and-energy-storage-projectsInteractive data visualization: https:/emp.lbl.gov/online-hybrid-and-energy-storage-projects Generator storage hybrid / co-located projects at end of 2019: wind storage, PV storage, fossil storage Wind storage plants located primarily in ERCOT and PJM PV storage plants located primarily in non-ISO West, ERCOT, and Southeast Fossil storage plants located primarily in MISO and ISO-NE 16 Sources: EIA 860 2019 Early Release, Berkeley Lab Interactive data visualization: https:/emp.lbl.gov/online-hybrid-and-energy-storage-projectsInteractive data visualization: https:/emp.lbl.gov/online-hybrid-and-energy-storage-projects Scope of transmission interconnection queue data Data compiled from interconnection queues for 7 ISOs and 30 utilities, representing 80% of all U.S. electricity load Projects that connect to the bulk power system Includes all projects in queues through the end of 2019 Filtered to include only “active” projects: removed those listed as “online,” “withdrawn,” or “suspended” Hybrid / co-located projects identified via either of these two methods: “Generator Type” field includes multiple types for a single queue entry (row) Two or more queue entries (of different gen. types) that share the same point of interconnection and sponsor, queue date, ID number, and/or COD Emphasis was placed on identification of wind storage and solar storage Other hybrid configurations are likely undercounted Note that being in an interconnection queue does not guarantee ultimate construction: majority of plants are not subsequently built 17 Generation capacity in 37 selected interconnection queues from 2014 to 2019, by resource type Note: Not all of this capacity will be built Source: Berkeley Lab review of interconnection queues 18Interactive data visualization: https:/emp.lbl.gov/generation-storage-and-hybrid-capacityInteractive data visualization: https:/emp.lbl.gov/generation-storage-and-hybrid-capacity Wind power capacity within selected interconnection queues by region: cumulative total and 2019 additions Note: Not all of this capacity will be built Source: Berkeley Lab review of interconnection queues 19Interactive data visualization: https:/emp.lbl.gov/generation-storage-and-hybrid-capacityInteractive data visualization: https:/emp.lbl.gov/generation-storage-and-hybrid-capacity Hybrid / co-located capacity within interconnection queues at end of 2019: 11 GW of wind proposed as hybrids, 102 GW of solar Notes: (1) Not all of this capacity will be built; (2) Hybrid plants involving multiple generator types (e.g., wind PV storage, wind PV) show up in all generator categories, presuming the capacity is known for each type. Source: Berkeley Lab review of interconnection queues 20 Wind Storage and Solar Storage configurations are more common than other hybrid types1 1 Emphasis was placed on identification of wind storage and solar storage: other hybrid configurations are likely undercounted. Interactive data visualization: https:/emp.lbl.gov/generation-storage-and-hybrid-capacityInteractive data visualization: https:/emp.lbl.gov/generation-storage-and-hybrid-capacity Location of hybrid / co-located capacity within interconnection queues at end of 2019 Notes: (1) Not all of this capacity will be built; (2) Hybrid plants involving multiple generator types (e.g., wind PV storage, wind PV) show up in all generator categories, presuming the capacity is known for each type; (3) Emphasis was placed on identification of wind storage and solar storage in queues: other hybrid / co-located projects are likely undercounted. Source: Berkeley Lab review of interconnection queues 21 As a proportion of proposed wind, solar, and natural gas in regional queues, proposed wind hybrids are more prevalent in CAISO; solar somewhat more evenly distributed WindSolarNat. Gas CAISO50g%0% ERCOT3%0% SPP1%0% MISO2%0% PJM0%1% NYISO1%5%4% ISO-NE6%0%0% West (non-ISO)6P%0% Southeast (non-ISO)0%6%0% TOTAL4.8.7%0.6% Percentage of Proposed Generators Hybridizing in Each RegionRegion Interactive data visualization: https:/emp.lbl.gov/generation-storage-and-hybrid-capacityInteractive data visualization: https:/emp.lbl.gov/generation-storage-and-hybrid-capacity Generator storage hybrid / co-located projects and standalone storage in interconnection queues Source: Berkeley Lab review of interconnection queues 22 Note: Not all of this capacity will be built Average storage:generation capacity ratio for solar storage (66%) is higher than for wind storage (27%), in subset of ISO queues shown here: solar hybrids likely to install more storage capacity relative to generation capacity than wind hybrids Wind StorageSolar Storage CAISO25x% ERCOT548% SPP238% NYISO7I% Combined27f% Storage:Generation Capacity Ratio Region ELECTRICITYMARKETS see full report for the assumptions used to generate the figure. Source: Berkeley Lab analysis of data from USITC DataWeb: http:/dataweb.usitc.gov 28 Tracked wind equipment imports into the United States in 2019, by region Note: Tracked wind-specific equipment includes: wind-powered generating sets, towers, hubs and blades, wind generators and parts Source: Berkeley Lab analysis of data from USITC DataWeb: http:/dataweb.usitc.gov 29 Origins of U.S. imports of selected wind turbine equipment in 2019 Majority of imports of wind-powered generating sets come from Spain Generators and parts come from Europe and Asia Towers largely come from Asia, but also Canada Blades and hubs come from all four world regions Source: Berkeley Lab analysis of data from USITC DataWeb: http:/dataweb.usitc.gov 30 Approximate domestic content of major components in 2019 Figure reflects percentage of blades, towers, and nacelles that were installed in the U.S. in 2019 that were also manufactured / assembled domestically Imports occur in untracked trade categories not included below, including many nacelle internals; nacelle internals generally have lower domestic content of 5 MW are included. ELECTRICITYMARKETS as a result, prices do not reflect wind generation costs Also presented are Level10 Energy data on PPA offers; these are often for shorter contract durations, and levelization details are unclear Levelized cost of energy is calculated based on following assumptions Project-level CapEx and capacity factor data presented elsewhere in this deck Levelized OpEx declines from $83/kW-yr in 1998 to $43/kW-yr in 2019 (2019$); project life increases from 20 years in 1998 to 29.6 years in 2019 (from previous LBNL research) Weighted average cost of capital (WACC) based on 10% equity return over time; debt interest rate varies over time as shown earlier in deck; constant 65%/35% debt/equity ratio Combined income tax of 40% pre-2018 and 27% post-2017; 5-yr MACRS; no PTC; 2% inflation 61 Levelized wind PPA prices by PPA execution date and region (full sample) 62 Source: Berkeley Lab, FERC Interactive data visualization: https:/emp.lbl.gov/wind-power-purchase-agreement-ppa-pricesInteractive data visualization: https:/emp.lbl.gov/wind-power-purchase-agreement-ppa-prices Generation-weighted average levelized wind PPA prices by PPA execution date: national and region averages 63 Source: Berkeley Lab, FERC Interactive data visualization: https:/emp.lbl.gov/wind-power-purchase-agreement-ppa-pricesInteractive data visualization: https:/emp.lbl.gov/wind-power-purchase-agreement-ppa-prices Note: West = CAISO, West (non-ISO); Central = MISO, SPP, ERCOT; East = PJM, NYISO, ISO-NE, Southeast (non-ISO) Levelized wind PPA prices by PPA execution date and region (recent sample) 64 Source: Berkeley Lab, FERC Interactive data visualization: https:/emp.lbl.gov/wind-power-purchase-agreement-ppa-pricesInteractive data visualization: https:/emp.lbl.gov/wind-power-purchase-agreement-ppa-prices Level10 Energy wind PPA price indices Source: Level10 Energy 65 Levelized cost of wind energy by commercial operation date Note: Yearly estimates reflect variations in installed cost, capacity factors, operational costs, cost of financing, and project life; includes accelerated depreciation but exclude PTC. See full report for details. 66 Source: Berkeley Lab Interactive data visualization: https:/emp.lbl.gov/levelized-cost-wind-energyInteractive data visualization: https:/emp.lbl.gov/levelized-cost-wind-energy 947771617473859085857259484441393535 0 20 40 60 80 100 120 140 160 1998-99 2000-01 2002-03 2004-05 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Commercial Operation Year Average and Project-level LCOE (2019 $/MWh) 100 MW Levelized cost of wind energy by region, over last five years 67 Source: Berkeley Lab Interactive data visualization: https:/emp.lbl.gov/levelized-cost-wind-energyInteractive data visualization: https:/emp.lbl.gov/levelized-cost-wind-energy Note: Total sample presented here includes 34 GW of installed wind capacity, but regional sample is especially small in ISO-NE (569 MW), CAISO (319 MW, no data in 2019), and NYISO (156 MW, no data in 2019) 0 30 60 90 2015 2017 2019 National $35/MWh 2019 Avg = 2015 2017 2019 ERCOT $32/MWh 2015 2017 2019 SPP $33/MWh 2015 2017 2019 MISO $36/MWh 2015 2017 2019 West $37/MWh 2015 2017 2019 PJM $44/MWh 2015 2017 2019 ISO-NE $76/MWh 2015 2017 2019 CAISO no data 2015 2017 2019 NYISO no data Average LCOE (2019 $/MWh) Historical renewable energy certificate (REC) prices REC prices vary by: market type (compliance vs. voluntary); geographic region; specific design of state RPS policies. Source: Marex Spectron 68 ELECTRICITYMARKETS generalized flat block is 24x7 average price across all pricing nodes in region Estimates of wind power integration costs, by region and wind penetration level Note: Because methods vary and a consistent set of operational impacts has not been included in each study, results from the different analyses presented here are not fully comparable. Nonetheless, in general, the balancing costs included in the above graphic are often additional to the market value and value factor results presented in previous slides. 78 Sources: see data file for details Integrating wind energy into power systems is manageable, but not free of additional costs Miles of transmission projects completed, by year and voltage Source: FERC 79 New transmission build has been relatively modest in recent years ELECTRICITYMARKETS for projects installed from 2013 through 2017, confidential EIA Form 860 data were used extensively. Wind project O&M costs come primarily from two sources: EIA Form 412 data from 2001 to 2003 for private power projects and projects owned by publicly-owned utilities, and FERC Form 1 data for investor-owned utility projects. Power Sales Price and Levelized Cost Trends Wind power purchase agreement (PPA) price data come from multiple sources, including prices reported in FERCs Electronic Quarterly Reports, FERC Form 1, avoided-cost data filed by utilities, pre-offering research conducted by bond rating agencies, and a Berkeley Lab collection of PPAs. Additional data come from Level10 Energy ( The levelized cost of wind energy estimated based on assumptions described on a later slide. REC prices come from Marex Spectron ( Price and Value Comparisons Data on solar PPA prices are based on the same sources as wind prices. Gas price projections come from EIAs Annual Energy Outlook (https:/www.eia.gov/outlooks/aeo/). Details on the calculation of energy and capacity value are available in Wiser and Bolinger (2019): https:/emp.lbl.gov/sites/default/files/wtmr_final_for_posting_8-9-19.pdf. In brief, estimated hourly wind generation profiles are matched to hourly nodal real-time wholesale prices from ABBs Velocity database. The capacity value of each plant is estimated based on the modeled wind profiles and ISO-specific rules for winds capacity credit and ISO-zone-specific capacity prices. Integration cost estimates derive from a Berkeley Lab review of the available published literature: see data-file for the full list of citations. Data on completed transmission lines come from FERC Infrastructure reports (https:/www.ferc.gov/industries-data/resources/staff-reports-and-papers). Conclusions Independent analys

2020-09-18 87页 5星级

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2020-09-09 34页 5星级

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2020-09-07 23页 5星级

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2020-08-01 25页 5星级

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2020-08-01 19页 5星级

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2020-07-02 42页 5星级

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2020-07-02 72页 5星级

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2020-07-02 26页 5星级

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2019-12-02 25页 5星级

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BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Utility-Scale Solar Empirical Trends in Project Technology, Cost, Performance, and PPA Pricing in the United States 2019 Edition Mark Bolinger, Joachim Seel, Dana Robson Lawrence Berkeley National Laboratory December 2019 This material is based upon work supported by the U.S. Department of Energys Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy Technologies Office (SETO) Agreement Number 34158 and Contract No. DE-AC02-05CH11231. BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Presentation Outline 1. Solar deployment trends (and utility-scales relative contribution) 8. Future outlook 2 Key findings from analysis of the data samples (first for PV, then for CSP): 2.Project design, technology, and location 3.Installed project prices 4.Operation and maintenance (O c-Si modules led thin-film 7 PV project population: 690 projects totaling 24,586 MWACContinued dominance of tracking projects (69% of newly installed capacity) relative to fixed-tilt projects (31%). Thin-film projects are nearly exclusively using tracking now. c-Si modules continue their clear lead (72% of newly installed capacity) relative to thin-film modules (28%). Hanwha had the highest market share among c-Si modules in our sample, followed by Jinko, and Canadian Solar. First Solar provided 85% of all thin-film modules in 2018, the remainder supplied by Solar Frontier. BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Florida is the new national leader in utility-scale solar growth 8 PV project population: 690 projects totaling 24,586 MWAC The Southeast is the new growth engine of the US utility-scale solar market. It is led by Florida, now the largest annual market at 1010 MWACor 25% of national additions. Established player North Carolina added 472 MWAC. For the first time since 2011, California is not the state with the most capacity growth (981 MWAC). But it still accounts for 40% of the cumulative installed capacity of the country. Texas continues its solar growth with another year of 650 MWACand is the state with the third-most additions in 2018. The Southwest only added 160 MWACin 2018, and was surpassed by new installations in the Northwest (181 MWAC). BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Floridas growth was driven by the regulated utilities FPL and TECO, which added many fixed-tilt projects ( ). California only completed 10 projects, but these were large (up to 252 MWAC) and added a respectable 981 MW. Northwestern additions in 2018 were predominantly tracking projects ( ). In 2018, storage ( ) was added to already existing (3) and new (4) PV projects. 6 of these were built in high penetration/transmission-constrained regions in HI, CA, AZ and TX, while the 7this in relative newcomer state MN. 4 new states added their first utility-scale PV projects: Connecticut, Vermont, Washington and Wyoming. 9 Florida is the new national leader in utility-scale solar growth BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Utility-Scale Solar has become a growing source of electricity in all regions of the United States 10 Utility-Scale PV is now well-represented throughout the nation with the exception of Midwestern states in the “wind belt.” Fixed-tilt projects (in particular c-Si ) have been built in lower-insolation regions, primarily along the east coast. Tracking projects ( ) started out in the Southwest but have increasingly spread throughout the country, north to Washington, Idaho, and Minnesota, and northeast to Virginia. BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Utility-Scale Solar is increasingly built at lower-insolation sites 11 The median solar resource (measured in long-term global horizontal irradiance GHI) at new project sites has decreased since 2013 as the market expands to less- sunny states but stabilized in 2018. Fixed-tilt PV is increasingly relegated to lower-insolation sites (note the decline in its 80th percentile), while tracking PV is pushing into those same areas (note the decline in its 20th percentile). Exceptions are fixed-tilt installations in either windy regions (Florida) or on brown- fields / landfill sites. All else equal, the buildout of lower-GHI sites will dampen sample-wide capacity factors (reported later). BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov The median inverter loading ratio (ILR) continued to climb, especially for fixed-tilt projects 12 As module prices have fallen (faster than inverter prices), developers have oversized the DC array capacity relative to the AC inverter capacity to enhance revenue and reduce output variability. The median inverter loading ratio (ILR or DC:AC ratio) increased to 1.33 in 2018, though considerable variation remains (ranging from 1.14 to 1.59). Fixed-tilt PV has more to gain from a higher ILR than does tracking PV, and 2018 showed a new record lead for fixed-tilt installations (1.41 vs. 1.31 - driven by high ILR projects in Florida, CT, and MD). All else equal, a higher ILR should boost capacity factors (reported later). BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Median installed price of PV has fallen by nearly 70% since 2010, to $1.6/WAC($1.2/WDC) in 2018 13 PV price sample: 641 projects totaling 22,886 MWAC The lowest 20th percentile of project prices fell from $1.7/WAC($1.3/WDC) in 2017 to $1.3/WAC($0.9/WDC) in 2018. The lowest projects among the 60 data points in 2018 was $1.0/WAC ($0.7/WDC). Historical pricing sample is robust (99% of installed capacity through 2017). 2018 data covers 64% of new projects or 62% of new capacity. This sample is backward-looking and does not reflect the price of projects built in 2019/2020. BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Pricing distributions have narrowed and continuously moved towards lower prices over the last 7 years 14 Both medians and modes have continued to fall (i.e., shift towards the left) each year. Share of relatively high-cost systems decreases steadily each year while share of low-cost systems increases. Price spread is the smallest in 2018, pointing to a reduction in underlying heterogeneity of prices across all installed projects. PV price sample: 641 projects totaling 22,886 MWAC BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Within our sample, projects with trackers now have lower average upfront costs than fixed-tilt projects 15 PV price sample: 640 projects totaling 22,880 MWAC Through 2016, projects with tracking were regularly more expensive (though by varying amounts) than fixed-tilt projects in our sample on average. But in both 2017 and 2018, this historical relationship seemingly reversed, with average pricing in 2018 at $1.7/WAC ($1.3/WDC) for fixed-tilt projects vs. $1.6/WAC($1.2/WDC) for tracking projects. This apparent reversal may be driven by challenging construction environments for fixed-tilt projects (e.g., high wind loads, sensitive brown-field sites) as well as sampling issues. However, for any individual project, using trackers still likely has a higher CapEx than mounting at a fixed-tilt. Trackers can sustain some amount of higher upfront costs because they deliver more generation. BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Within our 2018 sample, large projects enjoy a 30% cost advantage over smaller projects 16 PV price sample for 2018: 60 projects totaling 2,499 MWAC Differences in project size could potentially explain pricing variation we focus only on 2018 for this analysis. Median price for the first and second size bin (5-50MWAC) is larger than for third and fourth size bin (50-200MWAC) - $1.74/WACvs. $1.32/WAC. In $/WDCterms cost decline is even more obvious over first three bins: $1.42/WDCfor 5-20MW $1.21/WDCfor 20-50MW $1.04/WDCfor 50-100MW BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Project prices vary by region, newcomers have lower prices 17 Price differences could be driven in part by technology ubiquity; other factors may include labor costs and share of union labor, land costs, terrain, soil conditions, snow and wind loads, and balance of supply and demand. The Northeast, Northwest and Southwest seem to be priced above the national median, while the Midwest, Southeast and Texas appear to be lower priced. Sample size outside of Southeast is very limited (Hawaii and California are excluded due to few observations), so these rankings should be viewed with some caution. Note: The regions are defined in the earlier slides with a map of the United States PV price sample for 2018: 60 projects totaling 2,499 MWAC BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Bottom-up models estimate lower prices than all-in cost reports 18 LBNLs top-down estimates reflect a mix of union and non-union labor and span a wide range of project sizes and prices ($0.7-$2.3/WDC). The median of our fixed-tilt price sample is higher than other price estimates, whereas the median of our tracking price sample falls within the range of other estimates. Some of the price delta may be due to differences in the defined system boundaries and time horizon (e.g. under construction vs. operation date). For example, GTM (Wood Mackenzie) represents only turnkey EPC costs and excludes interconnection, and transmission costs, as well as developer overhead, fees, and profit margins. Note: Prices are presented in $/WDCto enable comparison with estimates by NREL, BNEF, and GTM PV price sample for 2018: 60 projects totaling 2,499 MWAC BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Operation and Maintenance (O&M) costs broaden in range 19 11 utilities report solar O&M costs for projects with 1 full operational year by 2018 and a mix of technologies (tracking vs. fixed tilt, module type). Average O&M costs for the cumulative set of PV plants have declined from about $32/kWAC-year (or $20/MWh) in 2011 to about $18/kWAC-year ($10.6/MWh) in 2018. Overall cost range among utilities has spread relative to earlier years as our sample has grown in 2018, perhaps reflecting different reporting practices by utilities. O&M Cost sample: 48 projects totaling 919 MWAC Cost Scope (per guidelines for FERC Form 1): Includes supervision and engineering, maintenance, rents, and training Excludes payments for property taxes, insurance, land royalties, performance bonds, various administrative and other fees, and overhead BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov 25.0% average sample-wide PV net capacity factor (cumulative), but with large project-level range from 12.1%-34.8% 20 Project-level variation in PV capacity factor driven by: Solar Resource (GHI): Strongest solar resource quartile has a 9 percentage point higher capacity factor than lowest resource quartile Tracking: Adds 2-5 percentage points to capacity factor on average, depending on solar resource quartile Inverter Loading Ratio (ILR): Highest ILR quartiles have on average 3 percentage point higher capacity factors than lowest ILR quartiles 0% 5% 10% 15% 20% 25% 30% 35% 40% 1 ILR 2 ILR 3 ILR 4 ILR 1234123412341234123412341234 Fixed-TiltTrackingFixed-TiltTrackingFixed-TiltTrackingFixed-TiltTracking 1st Quartile Solar Resource2nd Quartile Solar Resource3rd Quartile Solar Resource4th Quartile Solar Resource Cumulative Net AC Capacity Factor Median Individual Project 32 projects, 369 MW 12 projects, 139 MW 19 projects, 326 MW 8 projects, 122 MW 9 projects, 124 MW 7 projects, 151 MW 11 projects, 367 MW 22 projects, 858 MW 20 projects, 478 MW 14 projects, 622 MW 31 projects, 808 MW 4 projects, 96 MW 5 projects, 855 MW 26 projects, 903 MW 43 projects, 2,336 MW 13 projects, 634 MW 12 projects, 684 MW 24 projects, 242 MW 6 projects, 152 MW 26 projects, 732 MW 6 projects, 153 MW 41 projects, 1,843 MW 28 projects, 1,514 MW 24 projects, 523 MW 3 projects, 336 MW 3 projects, 626 MW 12 projects, 160 MW 29 projects, 1,374 MW 6 projects, 973 MW 20 projects, 601 MW Sample includes 550 projects totaling 20.0GWACthatcame online from 2007-2017 ILR QuartileILR QuartileILR QuartileILR QuartileILR QuartileILR QuartileILR QuartileILR Quartile 25 projects, 649 MW 9 projects, 275 MW BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Tracking boosts net-capacity factors by up to 5% in high-insolation regions 21 PV Performance sample: 550 projects totaling 20,024 MWAC Not surprisingly, capacity factors are highest in California and the Southwest, and lowest in the Northeast and Midwest. Although sample size is small in some regions, the greater benefit of tracking in the high-insolation regions is evident, as are the greater number of tracking projects in those regions. Note: The regions are defined in the earlier slides with a map of the United States 0% 5% 10% 15% 20% 25% 30% NortheastMidwestSoutheastTexasNorthwestHawaiiSouthwestCalifornia Average Cumulative Net AC Capacity Factor Fixed-Tilt Tracking 37 projects, 351 MW 1 project, 6 MW 17 projects, 242 MW 17 projects, 243 MW 2 projects, 44 MW 24 projects, 1,166 MW 72 projects, 1,912 MW 16 projects, 1,319 MW 4 projects, 43 MW 1 project, 28 MW 35 projects, 2,566 MW 140 projects, 6,041 MW 92 projects, 3,479 MW 21 projects, 407 MW 70 projects, 2,169 MW 1 project, 10 MW BerkeleyLabEMP Utility-Scale Solar 2019 Edition http:/utilityscalesolar.lbl.gov Since 2013, competing drivers have gradually reduced average capacity factors by project vintage 22 Recent flat-to-declining trend is not necessarily negative, but rather a sign of a market that is expanding geographically into less-sunny regions (as indicated by changes to GHI, portrayed both numerically and via shading intensity) Average capacity factors increased from 2010- to 2013-vintage projects due to an increase in: ILR (from 1.17 to 1.28) tracking (from 14% to 55%) average site-level GHI (from 4.97 to 5.32 kWh/m2/day) But trends in tracking and GHI were at odds from 2013- to 2016-vintage projects, resulting in capacity factor stagnation (on average) 2017-vintage projects match 2016- vintage on both ILR and tracking, but GHI has declined further, resulting in a 2 percentage point drop in average capacity factor (from 25.6% down to 23.6%) 0% 5% 10% 15% 20% 25% 30% 2010 7 0.14 2011 31 0.45 2012 37 0.89 2013 47 1.71 2014 52 2.78 2015 83 2.76 2016 155 7.56 2017 126 3.57 2018 Cumulative Mean Net AC Capacity Factor ILR: 1.17 Tracking: 14% GHI: 4.97 ILR: 1.23 Tracking: 49% GHI: 5.13 ILR: 1.18 Tracking: 52% GHI: 5.13 ILR: 1.28 Tracking: 55% GHI: 5.32 ILR: 1.29 Tracking: 63% GHI: 5.21 ILR: 1.32 Tracking: 75% GHI: 4.96 ILR: 1.30 Tr

2019-12-01 41页 5星级

2019年太阳能可利用等级报告 -Berkeley Lab（英文版）（75页）.pdf

Empirical Trends in Project Technology, Cost, Performance, and PPA Pricing in the United States 2019 Edition Authors: Mark Bolinger, Joachim Seel, Dana Robson Lawrence Berkeley National Laboratory December 2019 Table of ContentsTable of Contents List of AcronymsList of Acronyms . i i Executive SummaryExecutive Summary . ii ii 1. Introduction1. Introduction .5 5 2. Utility2. Utility- -Scale Photovoltaics (PV)Scale Photovoltaics (PV) . 1010 2.1 Installation and Technology Trends (690 projects, 24.6 GWAC) 11 Florida was the new national leader in utility-scale solar growth 11 Tracking c-Si projects continued to dominate 2018 additions 13 More projects at lower-insolation sites, fixed-tilt mounts crowded out of sunny areas 14 Developers continued to favor larger array capacity relative to inverter capacity 16 Utility-scale PV battery projects are becoming more common 17 2.2 Installed Project Prices (641 projects, 22.9 GWAC) 18 Median prices fell to $1.6/WAC ($1.2/WDC) in 2018 18 The price premium for tracking over fixed-tilt installations seemingly disappeared 20 Evidence of economies of scale among our 2018 sample 21 System prices vary by region 22 2.3 Operation and Maintenance Costs (48 projects, 0.9 GWAC) 25 2.4 Capacity Factors (550 projects, 20.0 GWAC) 27 Wide range in capacity factors reflects differences in insolation, tracking, and ILR 27 Since 2013, competing drivers have reduced average capacity factors by project vintage 30 Performance degradation is evident, but is difficult to assess and attribute at the project level 31 2.5 Power Purchase Agreement Prices (290 contracts, 18.6 GWAC) and LCOE (640 projects, 22.9 GWAC) 34 PPA prices have fallen dramatically, in all regions of the country 36 An increasing number of PPAs (and projects in general) are including battery storage 39 The incremental PPA price adder for storage depends on the size of the battery 42 Despite record-low PPA prices, solar faces stiff competition from both wind and natural gas 44 Levelized PPA prices track the LCOE of utility-scale PV reasonably well 46 2.6 Wholesale Market Value 49 Solar curtailment is a function of market penetration and transmission constraints 49 In most regions of the United States, solar provides above-average market value 51 Reduced by the ITC, solar PPA prices are generally comparable to solars market value 54 3. Utility3. Utility- -Scale Concentrating SolarScale Concentrating Solar- -Thermal Power (CSP)Thermal Power (CSP) . 5757 3.1 Technology and Installation Trends Among the CSP Project Population (16 projects, 1.8 GWAC) 57 3.2 Installed Project Prices (7 projects, 1.4 GWAC) 58 3.3 Capacity Factors (13 projects, 1.7 GWAC) 60 3.4 Power Purchase Agreement (PPA) Prices (6 projects, 1.3 GWAC) 61 4. Conclusions and Future Outlook4. Conclusions and Future Outlook . 6363 ReferencesReferences . 6666 Data Sources 66 Literature Sources 67 AppendixAppendix . . 7070 Total Operational PV Population 70 Total Operational CSP Population 71 O with some limited exceptions (including Figure 1 and Chapter 4), the report does not discuss forecasts or seek to project future trends. The home page for this reportutilityscalesolar.lbl.gov houses an Excel workbook that provides all of the publicly available data for each of the reports figures, as well as a number of interactive data visualizations that enable one to explore the data in different ways. The Federal Investment Tax Credit (“ITC”) The business energy investment tax credit, or ITC, in Section 48 of the U.S. tax code has been available to commercial solar projects for many years. Though originally a 10% credit, the Energy Policy Act of 2005 temporarily increased the size of the credit to 30% starting in 2006. In October 2008, the Emergency Economic Stabilization Act of 2008 extended the 30% credit through the end of 2016, and in December 2015, the Consolidated Appropriations Act of 2016 extended it once again, through 2019. This most-recent extension brought several other changes as well. For commercial projects, the prior requirement that a project be “placed in service” (i.e., operational) by the reversion deadline was relaxed to enable projects that merely “start construction” by the deadline to also qualify. Moreover, rather than reverting from 30% directly to 10% in 2020, the credit will instead gradually phase down to 10% over several years: to 26% in 2020, 22% in 2021, and finally 10% for projects that start construction in 2022 or thereafter. Moreover, in June 2018, the IRS issued “safe harbor” guidance clarifying that any project that qualifies for the 30%, 26%, or 22% ITC by starting construction in 2019, 2020, or 2021, respectively, will have until the end of 2023 (i.e., up to 4 years for projects that start construction in 2019) to achieve commercial operations without having to demonstrate a continuous work effort. In practice, this safe harbor guidance likely means that most utility-scale solar projects deployed through 2023 will continue to benefit from the full 30% ITC. Finally, as of October 2019, there were ongoing efforts including bills introduced in both the U.S. House and Senateto extend the 30% ITC for another five years, before the step- down begins. The 30% ITC has aided the utility-scale solar market over the years by enabling lower PPA prices that make solar more affordable, leading to greater deployment. One visible testament to its importance, at least historically, is 2016s record spike in deployment (see Figure 1), which was driven by the scheduled end-of-2016 reversion of the ITC to 10% (though, as noted above, that reversion was ultimately deferred by the late-December 2015 extension through 2019). Barring yet another extension, similar high deployment levels are expected over the next few years, in advance of the step down to 10% (Figure 1). 9 Defining “Utility-Scale” Determining which electric power projects qualify as “utility-scale” (as opposed to commercial- or residential-scale) can be a challenge, particularly as utilities begin to focus more on distributed generation. For solar PV projects, this challenge is exacerbated by the relative homogeneity of the underlying technology. For example, unlike with wind power, where there is a clear difference between utility-scale and residential wind turbine technology, with solar, very similar PV modules to those used in a 5 kW residential rooftop system might also be deployed in a 100 MW ground-mounted utility-scale project. The question of where to draw the line is, therefore, rather subjective. Though not exhaustive, below are three differentand perhaps equally validperspectives on what is considered to be “utility-scale”: Through its Form EIA-860, the Energy Information Administration (“EIA”) collects and reports data on all generating plants of at least 1 MW of capacity, regardless of ownership or whether interconnected in front of or behind the meter (note: this report draws heavily upon EIA data for such projects). In their Solar Market Insight reports, Wood Mackenzie and SEIA (“Wood Mackenzie/SEIA”) define utility-scale by offtake arrangement rather than by project size: any project owned by or that sells electricity directly to a utility (rather than consuming it onsite) is considered a “utility-scale” project. This definition includes even relatively small projects (e.g., 100 kW) that sell electricity through a feed-in tariff (“FiT”) or avoided cost contract (Munsell 2014). At the other end of the spectrum, some financiers define utility-scale in terms of investment size, and consider only those projects that are large enough to attract capital on their own (rather than as part of a larger portfolio of projects) to be “utility-scale” (Sternthal 2013). For PV, such financiers might consider a 40 MW (i.e., $50 million) project to be the minimum size threshold for utility-scale. Though each of these three approaches has its merits, this report adopts yet a different approach: utility-scale solar is defined herein as any ground-mounted solar project that is larger than 5 MWAC (separately, ground-mounted PV projects of 5 MWAC or less, along with roof- mounted systems of all sizes, are analyzed in LBNLs annual Tracking the Sun report series). This definition is grounded in consideration of the four main types of data analyzed in this report: installed prices, O Fiorelli and Zuercher - Martinson 2013). This report uses inverter loading ratio, or ILR. 16 This is analogous to the boost in capacity factor achieved by a wind turbine when the size of the rotor increases relative to the turbines nameplate capacity rating. This decline in “specific power” (W/m2 of rotor swept area) causes the generator to operate closer to (or at) its peak rating more often, thereby increasing capacity factor. 17 Power clipping, also known as power limiting, is comparable to spilling excess water over a dam (rather than running it through the turbines) or feathering a wind turbine blade. In the case of solar, however, clipping occurs electronically rather than physically: as the DC input to the inverter approaches maximum capacity, the inverter moves away from the maximum power point so that the array operates less efficiently (Advanced Energy 2014; Fiorelli and Zuercher - Martinson 2013). In this sense, clipping is a bit of a misnomer, in that the inverter never really even “sees” the excess DC powerrather, it is simply not generated in the first place. Only potential generation is lost. 17 projects, the median ILR has increased over time, from around 1.2 in 2010 to 1.33 in 2018. Fixed- tilt projects commonly feature higher ILRs than tracking projects, consistent with the notion that fixed-tilt projects have more to gain from boosting the ILR in order to achieve a less-peaky, “tracking-like” daily production profile. Since 2013, however, the median ILR of tracking and fixed-tilt projects has been nearly the same, and in 2016 and 2017 tracking projects even outpaced fixed-tilt installations (1.33 vs. 1.31). 2018 projects reverted again to the traditional relationships (1.41 for fixed-tilt, 1.31 for tracking), pushed by high-ILR projects in Florida and the Northeast. The overall ILR range among all projects in 2018 remains quite large (1.14 to 1.59), pointing to continued diversity in design practices. Figure 7. Trends in Inverter Loading Ratio by Mounting Type and Installation Year Utility-scale PV battery projects are becoming more common Despite an increasing number of announcements about new PV battery projects in the pipeline (see, for example, Table 3, Figure 37, and Figure 38), relatively few projects have been built to date. In 2018, seven new projects featuring batteries connected to utility-scale PV plants came online (see Figure 3). Three of these new batteries were added to existing PV-only projects that came online in 2016 (foreshadowing the potential for a large retrofit market) while the other four were installed concurrently with new PV projects. All seven of these new storage projects use lithium-ion batteries, sized to match 5-135% of the corresponding PV capacity (in MWAC terms). Most focus predominantly on the ability to shift energy for later use (up to 5 hours at full capacity), while the primary purpose of one system is the provision of grid reliability services in a region that is home to many large renewable energy projects. 18 2.2 Installed Project Prices (641 projects, 22.9 GWAC) This section analyzes installed price data from a large sample of the overall utility-scale PV project population described in the previous section.18 It begins with an overview of installed prices for PV projects over time, and then breaks out those prices by mounting type (fixed-tilt vs. tracking), project size, and region. A text box at the end of this section compares our top-down empirical price data with a variety of estimates derived from bottom-up cost models. Sources of installed price information include the Energy Information Administration (EIA), the Treasury Departments Section 1603 Grant database, data from applicable state rebate and incentive programs, state regulatory filings, FERC Form 1 filings, corporate financial filings, interviews with developers and project owners, and finally, the trade press. All prices are reported in real 2018 dollars. In general, only fully operational projects for which all individual phases were in operation at the end of 2018 are included in the sample19i.e., by definition, our sample is backward-looking and therefore may not reflect installed price levels for projects that are completed or contracted in 2019 and beyond. Moreover, reported installed prices within our backward-looking sample may reflect transactions (e.g., entering into an Engineering, Procurement, and Construction or “EPC” contract) that occurred several years prior to project completion. In some cases, those transactions may have been negotiated on a forward-looking basis, reflecting anticipated future costs at the time of project construction. In other cases, they may have been based on contemporaneous costs (or a conservative projection of costs), in which case the reported installed price data may not fully capture recent fluctuations in component costs or other

2019-12-01 75页 5星级

CEEP-BIT：2019年光伏及风电产业前景预测与展望（13页）.pdf

平价时代即将到来，风电也将开始通过竞价倒逼行业降成本和技术进步，上游供给受钢价和技术创新影响。2018 年 11 月，钢价指数下滑至 118.5，且技术进步带来毛利。叶片方面中材科技的市占率第一，发明.

2019-12-01 13页 5星级