y.. _data:

Data: Mass

Input Data for Mass Flows

At least two input files, such as the PV ICE baselines for crystalline silicon, are needed for the simulation:

  1. one file with module parameters throughout the years, for example baseline_US, and

  2. one or more files with process parameters for each material being analyzed in the module, for example baseline_glass.

See Module-Input-File and Material-Input-File for more details on input columns needed and their definition.

The baselines folder in the PV_ICE tool provides baseline scenarios for modules in the US and World level, as well as baseline_materials for 7 component materials of crystalline silicon PV modules. For more details on the source of these values, see the Jupyter Journal documentation of baselines. These input files represent an average crystalline silicon module and its changing component materials over time. These files can be modified by the user to explore a particular technology(s). The necessary parameters (columns) for the module input file and the material input file are described below.

Module Input File

Example File baseline_module_US.csv

year [years]: int Year. Each row will be a year that is studied in the simulation.

new_Installed_Capacity [MW]: float New installed PV capacity in MW. Additions of PV modules in nameplate MW peak in the specified year. Note this is NOT cumulative.

mod_eff [%]: float Module efficiency in percentage. Nameplate efficiency of the module. i.e.: 20.9 %.

mod_reliability_t50 [years]: float (optional) Module reliability parameter T50 in years. The number of years after the installation year at which 50% of the cohort of modules have failed

mod_reliability_t90 [years]: float (optional) Module reliability parameter T90 in years. The number of years after the installation year at which 90% of the cohort of modules have failed

mod_degradation [%]: float Module degradation rate in percentage. Percentage annual reduction of the module performance, relative to nameplate. i.e. 0.5 %.

mod_lifetime [years]: float Module lifetime in years. The lifetime of a module as defined by economic lifetime or warranty. i.e. 25 years.

mod_MFG_eff [%]: float Module Manufacturing Efficiency in percentage. Efficiency or yield of manufacturing modules. i.e. losses of modules and all associated products during production.

mod_Repair [%]: float Module Repair rate in percentage. Percentage of modules which are repaired after premature failure from the field. This parameter is applied only to modules failed through the Weibull function (i.e. T50 and T90). Repaired modules are returned to the field and continue generating energy at their cohort specified degradation rate.

mod_MerchantTail [%]: float Module Merchant Tail rate in percentage. Percentage of modules at EOL that are reused on-site. Merchant tail is an industry term referring to the time period after the PV system loan has been paid off. These modules remain in the field until all fail through Weibull probability functions.

mod_EOL_collection_eff [%]: float Module end of life collection efficiency in percentage. Percentage of modules collected from the field at end of life for sorting and disposition. i.e. 30%. Any modules not collected are automatically landfilled.

Path/Status Good

Path or status good refers to modules which have reached end of life through non-failure modes (i.e. not Weibull) and are still at >80% of nameplate power. The following parameters dictate the path of “good” status modules, and should ideally add to 100%; the landfill parameter will be adjusted if they do not add to 100%.

mod_EOL_pg0_resell [%]: float Module end of life path good 0 - Resell in percentage. Percentage of collected end of life good modules which are resold on the secondary market. Only applicable to modules which are above 80% of nameplate power at first EOL.

mod_EOL_pg1_landfill [%]: float (optional) Module end of life path good 1 - Landfill in percentage. Percentage of collected end of life good modules which are landfilled. This value is automatically adjusted in the code if the other path good parameters are more or less than 100%.

mod_EOL_pg2_stored [%]: float (BETA) Module end of life path good 2 - Stored in percentage. Percentage of collected end of life good modules which are stored or warehoused for future disposition. Currently, these modules remain stored; future code updates will allow for removal from storage.

mod_EOL_pg3_reMFG [%]: float Module end of life path good 3 - Remanufacture in percentage. Percentage of collected end of life good modules which are disassembled for component remanufacturing (ex: recovering the front glass intact for use in a new module).

mod_EOL_pg4_recycled [%]: float Module end of life path good 4 - Recycled in percentage. Percentage of collected end of life good modules which are sent to recycling for material recapture.

Path/Status Bad

Path or status bad refers to modules which have reached end of life through failure (i.e. Weibull) and/or are <80% of nameplate power. The following parameters dictate the path of “bad” status modules, and should ideally add to 100%; the landfill parameter will be adjusted if they do not add to 100%.

mod_EOL_pb1_landfill [%]: float (optional) Module end of life path bad 1 - Landfill in percentage. Percentage of collected end of life bad modules which are sent to the landfill.

mod_EOL_pb2_stored [%]: float (BETA) Module end of life path bad 2 - Stored in percentage. Percentage of collected end of life bad modules which are stored or warehoused for future disposition. Currently these modules remain in storage; future code updates will allow for removal from storage.

mod_EOL_pb3_reMFG [%]: float Module end of life path bad 3 - Remanufacture in percentage. Percentage of collected end of life bad modules which are disassembled for component remanufacturing (ex: recovering the front glass intact for use in a new module). This parameter is separated out from path good because the remanufacturing potential of a failed module might be lower than that of a good intact module.

mod_EOL_pb4_recycled [%]: float Module end of life path bad 4 - Recycled in percentage. Percentage of collected end of life bad modules which are sent to recycling for material recapture.

mod_EOL_reMFG_yield [%]: float Module end of life Remanufacture yield in percentage. Efficiency or yield of modules going through the disassembly process. i.e. in the attempt to disassmble the module something goes wrong and remanufacture of the components will not be possible. This parameter dictates BOTH good and bad path Remanufacture yield.

mod_EOL_sp_reMFG_recycle [%]: float Module end of life sub-path Remanufacture to Recycle in percentage. Percentage of modules which are unsuccessful in remanufacture and are subsequently sent to recycling instead (ex: during recovery of the front glass, it shatters, is recycled instead of remanufactured). This parameter dictates BOTH good and bad path Remanufacture to Recycling subpath.

Material Input File

Example File baseline_material_glass.csv

year : int Year. Each row will be a year that is studied in the simulation.

mat_virgin_eff [%]: float Material virgin efficiency. Efficiency or yield of all mining, extracting, and purifying processes for the material up to the point of entry into the module manufacturing line.

mat_massperm2 [g/m^2]: float Material mass per module meter squared in grams per meter squared. Mass of component material in grams per square meter of PV module.

mat_MFG_eff [%]: float Material Manufacturing Efficiency in percentage. Efficiency or yield of the manufacturing production line for the material - i.e. how much of the input material is incorporated into the module. (ex: silver in module versus silver paste used).

mat_MFG_scrap_Recycled [%]: float Material Manufacturing scrap Recycling rate in percentage. The percentage of the scrap generated at the PV manufacturing facility that is sent to recycling (internal or external).

mat_MFG_scrap_Recycling_eff [%]: float Material Manufacturing scrap Recycling Efficiency in percentage. Efficiency or yield of the material scrap recycling process.

mat_MFG_scrap_Recycled_into_HQ [%]: float Material Manufacturing Scrap Recycled into High Quality in percentage. Percentage of manufacturing scrap which is recycled into high quality/high purity material and used for non-PV applications (open-loop).

mat_MFG_scrap_Recycled_into_HQ_Reused4MFG [%]: float Material Manufacturing Scrap Recycled into High Quality and Reused for PV Manufacturing. Percentage of manufacturing scrap material which is recycled and used in the manufacturing of a new PV module (closed-loop).

mat_PG3_ReMFG_target [%]: float Material Path Good 3 - Remanufacturing Target in percentage. For the end of life modules which went through the remanufacture disassembly process, the fraction of this material which is a target of remanufacturing (ex: 100% of the glass is targeted for remanufacturing). The rate of remanufacturing for a particular material. Note: this variable applies to BOTH path good and path bad.

mat_ReMFG_yield [%]: float Material Remanufacturing Yield in percentage. Efficiency or Yield of the remanufacturing process for the material (i.e. what percent of glass is successfully cleaned for use in a new PV module).

mat_PG4_Recycling_target [%]: float Material path good 4 - Recycling Target in percentage. Percentage of the end of life material that is targeted/collected for recycling (i.e. 100% of aluminum is sent to recycling).

mat_Recycling_yield [%]: float Material Recycling Yield in percentage. Efficiency or Yield of the end of life recycling process, i.e. percentage of the material that is put through the process that is successfully recycled.

mat_EOL_Recycled_into_HQ [%]: float Material at End of Life Recycled into High Quality in percentage. Percentage of collected end of life material recycled into high quality/high purity material and used for non-PV module applications (open-loop).

mat_EOL_RecycledHQ_Reused4MFG [%]: float Material at End of Life Recycled into High Quality and Reused for PV Manufacturing in percentage. Percentage of end of life recycled material that is recycled into high quality/high purity material and used in the manufacture of a new PV module (closed-loop)

Scenario Creation Inputs

In addition to the above file inputs, there are a few parameters which are set at other times.

irradiance has a standard internal value of 1000.0 W/m^2. This value can be modified by ?!?!?!

The function calculateMassFlow can also take in weibullInputParams, bifacialityfactors, reducecapacity. WeibullInputParams can be use instead of T50 and T90 values. bifacialityfactors an be added to account for the contribution of bifacial modules. reducecapacity is used in combination with a modified irradience value to explore different locations.

Outputs of Mass Flow Calculations

PV ICE calculates effective capacity, virgin material demand, lifecycle wastes, and quantity of circular materials among other processes for each year dynamically. When the “calculateMassFlow” function is called, these annual results are appended to the dataframe loaded from Module and Material inputs. A description of the output columns is below.

PV ICE Outputs

Most Useful Outputs

This first set of output variables are the ones which are most useful as a user to anayze the scenarios. They are split into variables which consider the flow of modules on an area basis, and variables which track the material flows on a mass basis.

Module Outputs

Yearly_Sum_Area_disposedby_Failure [m2] : float and Yearly_Sum_Power_disposedby_Failure [W] : float The annual module area and power removed from the field through Weibull controlled failure.

Yearly_Sum_Area_disposedby_ProjectLifetime [m2] : float and Yearly_Sum_Power_disposedby_ProjectLifetime [W] : float The annual module area and power removed from the field by economic project lifetime.

Yearly_Sum_Area_disposed [m2] : float and Yearly_Sum_Power_disposed [W] : float The annual sum of module area and power disposed by all EOL modes.

landfilled_noncollected [m2] : float The annual module area of not collected at EOL. These are sent to landfill.

Repaired_[W] [W] : float and Repaired_Area [m2] : float The annual module area and power which are repaired and return to the field.

Resold_Area [m2] : float and Resold_[W] [W] : float The annual module area and power which are resold on the secondary market and return to the field.

Cumulative_Active_Area [m2] : float and Installed_Capacity_[W] [W] : float The running quantity of area and power active in the field. This is the basis of effective capacity.

Status_BAD_Area [m2] : float and Status_BAD_[W] [W] : float The annual module area and power designated as bad status, i.e. the area that reached EOL through failure and/or are less than 80% of nameplate power.

Area_for_EOL_pathsG [m2] : float and Power_for_EOL_pathsG [W] : float The annual module area and power designated as good status, i.e. the area that reached EOL through economic EOL and is at or above 80% of nameplate power.

WeibullParams [none] : float The calculated alpha and beta Weibull parameters based on T50 and T90.

EOL_Landfill0 [m2] : float The annual module area in total which is sent to the landfill, including all non collected area and the collected area (Landfill_0)

Landfill_0 [m2] : float The annual module area which is sent to the landfill after being collected. This does not include not collected landfill area.

EOL_BadStatus [m2] : float The annual sum of module area which is in the bad status category.

EOL_PG [m2] : float The annual sum of module area which is in the good status category.

EOL_PATHS [m2] : float The annual sum of module area including all good status and all collected bad status.

P2_stored [m2] : float The annual sum of good and bad status module area which is stored.

P3_reMFG [m2] : float The annual sum of good and bad status module area which is remanufactured.

P4_recycled [m2] : float The annual sum of good and bad status module area which is recycled.

ModuleTotal_MFG [m2] : float The annual total module area which is manufactured. This value accounts for the increase needed due to module manufacturing yield.

Material Outputs

mat_PG2_stored [g] : float The annual mass flow of EOL material that is stored.

mat_reMFG [g] : float The annual mass flow of EOL material that is remanufactured.

mat_reMFG_2_recycle [g] : float The annual mass flow of EOL material that unsuccessfully remanufactured and sent to recycling instead.

mat_recycled_all [g] : float The annual mass flow of EOL material that is sent to recycling, including remanufature to recycling and straight to recycling.

mat_recycled_yield [g] : float The annual mass flow of EOL material that is successfully recycled.

mat_EOL_Recycled_HQ_into_MFG [g] : float The annual mass flow of EOL material that is successfully recycled into high quality/high purity and is used in the manufacture of PV modules (closed-loop), offsetting virgin material demand.

mat_Manufacturing_Input [g] : float The annual mass flow of material entering material manufacturing (the precursor step to module manufacturing), including raw virgin material and recycled material. Remanufactured material skips this step, but does reduce this quantity.

mat_MFG_Scrap [g] : float The annual mass flow of material which was not successfully manufactured, manufacturing scrap, or unyield.

mat_MFG_Scrap_Sentto_Recycling [g] : float The annual mass flow of material manufacturing scrap which is sent to recycling.

mat_MFG_Recycled_HQ_into_MFG [g] : float The annual mass flow of material manufacturing scrap which is sucessfully recycled and is used in the manufacture of a PV module (closed-loop), offsetting virgin material demand.

mat_Virgin_Stock [g] : float The annual mass flow of virgin material demand.

mat_Total_EOL_Landfilled [g] : float The annual mass flow of EOL material which is landfilled.

mat_Total_MFG_Landfilled [g] : float The annual mass flow of material manufacturing scrap which is landfilled.

mat_Total_Landfilled [g] : float The annual mass flow of material which is landfilled, including EOL and manufacturing scrap.

Supporting Output Variables

This set of variables exist within the code and support the calculation of the more useful output variables (above). These variables are available if needed.

Module Outputs

Area [m2] : float This annual variable keeps track of the module area with additions and subtractions annually. This variable supports module mass flow calculations.

EOL_PG_Year_## [m2] : float This set of variables tracks how much area goes through the status/path good in the year

EOL_L0_Year_## [m2] : float This set of variables tracks how much area goes to the landfill on any particular year. This is the sum of all paths to the landfill.

EOL_BS_Year# [m2] : float This set of variables tracks how much area goes through the status/path bad in the year.

For each the good and bad status modules, there are designated paths available. The following variables are PG for path/status good and PB for path/status bad. The variable tracks the same area/mass flow for the respective module status. The path number designates the final destination: 1. Landfill 2. Storage 3. Remanufacture 4. Recycle

PG/PB1_landfill [m2] : float The annual module area of good/bad status modules which are sent to the landfill. This is partially controlled by user inputs.

PG/PB2_stored [m2] : float The annual module area of good/bad status modules which are sent to storage. This is partially controlled by user inputs.

PG/PB3_reMFG [m2] : float The annual module area of good/bad status modules which are sent to remanufacturing. This is partially controlled by user inputs.

PG/PB3_reMFG_yield [m2] : float The annual module area of status good/bad which is successfully remanufactured and sent on to material level remanufacturing.

PG/PB3_reMFG_unyield [m2] : float The annual module area of status good/bad which is NOT successfully remanufactured and sent on to material level remanufacturing.

PG/PB4_recycled [m2] : float The annual module area of good/bad status modules which are sent to recycling. This is partially controlled by user inputs.

Material Outputs

mat_L0 [g] : float The annual mass flow of material which is landfilled from the module not being collected at EOL.

mat_L1 [g] : float The annual mass flow of material which is landfilled intentionally after module collection.

mat_reMFG_mod_unyield [g] : float The annual mass flow of material contained in modules which were unsuccessfully remanufactured, module remanufacturing scrap. This material can either be landfilled (L2) or sent to recycling (reMFG to recycle module property).

mat_reMFG_target [g] : float The annual mass flow of material which is a remanufacturing target. This is determined by user input.

mat_reMFG_untarget [g] : float The annual mass flow of material which is NOT a remanufacturing target. This is the inverse of mat_reMFG_target.

mat_reMFG_yield [g] : float The annual mass flow of material which was successfully remanufactured. This is determined by user input.

mat_reMFG_unyield [g] : float The annual mass flow of material which was NOT successfully remanufactured. This is the inverse of mat_reMFG_yield.

mat_reMFG_all_unyields [g] : float The annual mass flow of material of all unsucessful remanufacturing from both the module and material flows. This summed path has the option of being landfilled or recycled.

mat_L2 [g] : float The annual mass flow of material which is unsuccessfully remanufactured and not sent to recycling, remanufacturing scrap which is landfilled or unrecoverable. Includes un-yields of module and material remanufacturing.

mat_recycled_PG4 [g] : float The annual mass flow of material sent to recycling from the module flow.

mat_recycled_target [g] : float The annual mass flow of material which is targeted for and sent to recycling. This can be smaller than mat_recycled_PG4.

mat_L3 [g] : float The annual mass flow of EOL material which is not targeted for recycling.

mat_L4 [g] : float The annual mass flow of EOL material which is unsuccessfully recycled, recycling scrap which is unrecoverable.

mat_EOL_Recycled_2_HQ [g] : float The annual mass flow of EOL material which is recycled into high quality/high purity material.

mat_EOL_Recycled_2_OQ [g] : float The annual mass flow of EOL material which is recycled into a lower quality/purity material not suitable for PV manufacturing, open-loop or downcycling.

mat_EOL_Recycled_HQ_into_OU [g] : float The annual mass flow of material which is recycled into high/puroty/high quality material and used for another industry, open-loop high quality recycling.

mat_EnteringModuleManufacturing_total [g] : float The annual mass flow of material entering module manufacturing, as determined by the annual deployment requirement accounting for the module manufacturing yield (i.e. this is larger than the material actually deployed).

mat_UsedSuccessfullyinModuleManufacturing [g] : float The annual mass flow of material which makes it into the module and is deployed.

mat_LostinModuleManufacturing [g] : float The annual mass flow of material lost during module manufacturing due to module yield.

mat_EnteringModuleManufacturing_virgin [g] : float The annual mass flow of virgin material which enters module manufacturing. This value is reduced by any closed-loop offsets.

mat_MFG_Scrap_Landfilled [g] : float The annual mass flow of material which is unsuccessfully manufactured and is landfilled (as opposed to MFG scrap recycled).

mat_MFG_Scrap_Recycled_Successfully [g] : float The annual mass flow of material manufacturing scrap which is sucessfully recycled.

mat_MFG_Scrap_Recycled_Losses_Landfilled [g] : float The annual mass flow of material which cannot be recovered from manufacturing scrap during recycling, and is landfilled. This is controlled by the yield of manufacturing scrap recycling.

mat_MFG_Recycled_into_HQ [g] : float The annual mass flow of material manufacturing scrap which is successfully recycled into high quality/high purity material.

mat_MFG_Recycled_into_OQ [g] : float The annual mass flow of material manufacturing scrap which is successfully recycled into a lower quality/purity not suitable for PV manufacturing, open-loop or downcycling.

mat_MFG_Recycled_HQ_into_OU [g] : float The annual mass flow of material manufacturing scrap which is successfully recycled into high quality/high purity and is used in another industry, open-loop recycling.

mat_Virgin_Stock_Raw [g] : float The annual mass flow of virgin material which is sent through virgin material processing. This is the amount of material extracted including overburden, the quantity accounts for the virgin material yield.

mat_Total_Recycled_OU [g] : float The annual mass flow of material from EOL and manufacturing which is recycled at a quality/purity not suitable for PV manufacturing, open-loop or downcycling.

PV ICE Mass Baselines References

This section documents data sources for PV ICE baselines. For the maths performed on the data from these sources, please see the baseline development documentation.

Module Baselines

Installed Capacity

Past

Installation data for solar pv installed in the US and globally from several IEA-PVPS T1 reports, Wood MacKenzie Power and Renewables Reports, and LBNL Utility-Scale Solar Reports. Note that installed capacity includes on and off grid, residential, commercial, and utility scale PV. Note that IEA PVPS data (US and global) pre-2009 data is assumed to be all silicon technology.

US Installations:

  • 1995 through 2008 taken from (K. Bolcar and K. Ardani, “National Survey Report of PV Power Applications in the United States 2010,” IEA-PVPS, National Survey T1-19:2010, 2010. [Online]. Available: https://iea-pvps.org/national-survey-reports/.)

  • 2009 taken from (M. Bolinger, J. Seel, and D. Robson, “Utility-Scale Solar 2019,” LBNL, Dec. 2019. Accessed: Aug. 13, 2020. [Online]. Available: https://emp.lbl.gov/sites/default/files/lbnl_utility_scale_solar_2019_edition_final.pdf.)

  • 2010 through 2019 taken from Wood Mackenzie Power & Renewables PV Forecasts Q2 of 2020 (“US PV Forecasts Q2 2020 Report,” Wood Mackenzie Power & Renewables.)

Other resources consulted include:

  • (F. H. Morse, “IEA PVPS Task 1 1993,” IEA-PVPS, IEA PVPS T1:1993, Mar. 1995. Accessed: Aug. 13, 2020. [Online]. Available: https://iea-pvps.org/wp-content/uploads/2020/01/tr_1993.pdf.)

  • (“IEA PVPS Task 1 1997,” IEA-PVPS, IEA PVPS T1:1997, Mar. 1997. Accessed: Aug. 13, 2020. [Online]. Available: https://iea-pvps.org/wp-content/uploads/2020/01/tr_1995_01.pdf.)

  • (“Trends in Photovoltaic Applications 2019,” IEA-PVPS, IEA PVPS T1-36:2019, Aug. 2019. Accessed: Aug. 12, 2020. [Online]. Available: https://iea-pvps.org/wp-content/uploads/2020/02/5319-iea-pvps-report-2019-08-lr.pdf.)

  • IRENA Solar Energy Data (https://www.irena.org/solar, and https://irena.org/Statistics/Download-Data)

Projections

Projection installation data for 2019 through 2050 options include:

  • Increasing deployment of 8.9% compound annual growth rate (CAGR) through 2050 (IRENA, “Future of Solar PV 2019,” IRENA, 2019. Accessed: Apr. 02, 2020. [Online]. Available: https://irena.org/-/media/Files/IRENA/Agency/Publication/2019/Nov/IRENA_Future_of_Solar_PV_2019.pdf.)

    1. Murphy et al., Electrification Futures Study: Scenarios of Power System Evolution and Infrastructure Development for the United States, NREL, NREL/TP-6A20-72330, 1762438, MainId:6548, Jan. 2021. Accessed: Apr. 15, 2021. https://www.osti.gov/servlets/purl/1762438/

  • W.J. Cole et al., Quantifying the challenge of reaching a 100% renewable energy power system for the United States, Joule, p. S2542435121002464, Jun. 2021, doi: 10.1016/j.joule.2021.05.011.

  • Ardani, Kristen, Paul Denholm, Trieu Mai, Robert Margolis, Eric O Shaughnessy, Timothy Silverman, and Jarett Zuboy. 2021. Solar Futures Study. EERE DOE. https://www.energy.gov/eere/solar/solar-futures-study.

  • Any other MW/year projection (annual not cumulative)

Module Properties

Average annual efficiency in % from:

  1. G.F. Nemet, Beyond the learning curve: factors influencing cost reductions in photovoltaics, Energy Policy, vol. 34, no. 17, pp. 3218-3232, Nov. 2006, doi: 10.1016/j.enpol.2005.06.020.

  2. International Technology Roadmap for Photovoltaic (ITRPV) 2021 Results, ITRPV, Apr. 2022 [Online]. Available: https://itrpv.vdma.org/

  3. International Technology Roadmap for Photovoltiac (ITRPV): 2020 Results, ITRPV, Apr. 2021. Accessed: Apr. 30, 2021. [Online]. Available: https://itrpv.vdma.org/documents/27094228/29066965/2021%30ITRPV/08ccda3a-585e-6a58-6afa-6c20e436cf41

Degradation rate of PV system (in percentage power loss per year):

  • Jordan, Dirk C., Kevin Anderson, Kirsten Perry, Matthew Muller, Michael Deceglie, Robert White, and Chris Deline. 2022. “Photovoltaic Fleet Degradation Insights.” Progress in Photovoltaics: Research and Applications n/a (n/a). https://doi.org/10.1002/pip.3566.

  • Lindig, Sascha, Julian Ascencio-Vasquez, Jonathan Leloux, David Moser, and Angele Reinders. 2021. “Performance Analysis and Degradation of a Large Fleet of PV Systems.” IEEE Journal of Photovoltaics 11 (5): 1312–18. https://doi.org/10.1109/JPHOTOV.2021.3093049.

Failure probability data, i.e. T50 and T90, in years:

  • D.C. Jordan, B. Marion, C. Deline, T. Barnes, and M. Bolinger, “PV field reliability status - Analysis of 100 000 solar systems,” Progress in Photovoltaics: Research and Applications, vol. n/a, no. n/a, Feb. 2020, doi: 10.1002/pip.3262.

Project lifetimes:

Module lifetime, representing the economic project life in years from:

  • (R. Wiser, M. Bolinger, and J. Seel, Benchmarking Utility-Scale PV Operational Expenses and Project Lifetimes: Results from a Survey of U.S. Solar Industry Professionals, 1631678, ark:/13030/qt2pd8608q, Jun. 2020. doi: 10.2172/1631678.)

Material Baselines

Glass

The ITRPV Results Reports for 2010 and forward provided glass thickness data, and where report data was missing, reasonable assumptions or interpolations were made. See jupyter journal “Glass per M2 Calculations” for each years calculations, and Supporting Material files for extracted data (“ITRPV - VDMA.” https://itrpv.vdma.org/).

Silicon

See Jupyter Journal “(baseline development) Silicon per m2” for calculations

  1. All ITRPV reports 2010 and forward

      1. Willeke, The Fraunhofer ISE roadmap for crystalline silicon solar cell technology, in Conference Record of the Twenty-Ninth IEEE Photovoltaic Specialists Conference, 2002., May 2002, pp. 53-57. doi: 10.1109/PVSC.2002.1190454.

      1. Sinke, A Strategic Research Agenda for Photovoltaic Solar Energy Technology - Research and development in support of realizing the Vision for Photovoltaic Technology, EU PV Technology Platform, Working Group 3, Oct. 2007. Accessed: Oct. 22, 2020. [Online]. Available: https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/strategic-research-agenda-photovoltaic-solar-energy-technology-research-and-development

    1. Sun, Solar PV module technology market report 2020, Wood Mackenzie Power & Renewables, 2020.

      1. Green, Photovoltaics: technology overview, Energy Policy, vol. 28, no. 14, pp. 989-998, Nov. 2000, doi: 10.1016/S0301-4215(00)00086-0.

  6. Different Wafer Sizes. https://sinovoltaics.com/learning-center/solar-cells/different-wafer-sizes/ (accessed Oct. 19, 2020).

    1. Barbose and N. Darghouth, Tracking the Sun 2019, LBNL, Oct. 2019. Accessed: Aug. 13, 2020. [Online]. Available: https://emp.lbl.gov/sites/default/files/tracking_the_sun_2019_report.pdf

    1. Bolinger, J. Seel, and D. Robson, Utility-Scale Solar 2019, LBNL, Dec. 2019. Accessed: Aug. 13, 2020. [Online]. Available: https://emp.lbl.gov/sites/default/files/lbnl_utility_scale_solar_2019_edition_final.pdf

    1. Costello and P. Rappaport, The Technological and Economic Development of Photovoltaics, Annu. Rev. Energy., vol. 5, no. 1, pp. 335-356, Nov. 1980, doi: 10.1146/annurev.eg.05.110180.002003.

    1. Mints, SPV Market Research: March 2020 Update. SPV Market Research, Mar. 2020.

      1. Maycock and P. O. Box, INTERNATIONAL PHOTOVOLTAIC MARKETS, DEVELOPMENTS AND TRENDS FORECAST TO 2010, p. 8, 1993.

      1. Maycock, World Photovoltaic Markets, in Practical Handbook of Photovoltaics, Elsevier, 2003, pp. 887-912. doi: 10.1016/B978-185617390-2/50039-8.

      1. Maycock, PV review: World Solar PV market continues explosive growth, Refocus, vol. 6, no. 5, pp. 18-22, Sep. 2005, doi: 10.1016/S1471-0846(05)70452-2.

Silver

See Jupyer Journal “(baseline development) Silver per m2” for calculations

        1. Phylipsen and E. A. Alsema, Environmental life-cycle assessment of multicrystalline silicon solar cell modules, Netherlands Agency for Energy and the Environment,NOVEM, Netherlands, Sep. 1995.

  2. All ITRPV reports 2010 and forward.

Copper (Encapsulated)

Under Development to better account for busbars, tabs, and wire technology See Jupyer Journal “(baseline development) Copper per module m2” for calculations

  1. Standard PV Ribbon Datasheet. Ulbrich Solar Technologies. Accessed: Jan. 14, 2021. [Online]. Available: https://www.pvribbon.com/wp-content/uploads/Datasheets/SPR_Datasheet.pdf

  2. All ITRPV reports 2010 and forward

Aluminum Frames

See Jupyter Journal “(baseline development) Aluminum Frames per m2” for calculations

      1. Peeters, D. Altamirano, W. Dewulf, and J. R. Duflou, Forecasting the composition of emerging waste streams with sensitivity analysis: A case study for photovoltaic (PV) panels in Flanders, Resources, Conservation and Recycling, vol. 120, pp. 14-26, May 2017, doi: 10.1016/j.resconrec.2017.01.001.

  2. All ITRPV 2010 and forward

Encapsulants

See Jupyter Journal “(baseline development) Encapsulants and Backsheets” for calculations

  1. All ITRPV 2010 and forward

Backsheets

See Jupyter Journal “(baseline development) Encapsulants and Backsheets” for calculations

  1. All ITRPV 2010 and forward

Data: Energy

The energy flows are based on the mass flows with units of energy per mass basis. As with the mass flows and to the best of our ability, the energy flows are sourced from real world values and literature, are dynamic to the annual level, and granular to specific processes. Below the variables are defined and their mass counterparts identified. For modules and each material, references used for creating the energy flow are listed as well.

Input Data for Energy Baselines

baseline_energy_module

year : int Year.

e_mod_MFG [kWh/m^2]: float The energy associated with the module level processes in manufacturing, including… Anything not captured in this energy is captured at the material level.

e_mod_Install [kWh/m^2]: float The energy assiciated with transporting the completed module to the installation site, and energies required to prepare the site and mount the panel.

e_mod_OandM [kWh/m^2]: float Energies associated with operation and maintenance of a PV site. This includes truck trips for maintenance, and any overnight energy required by the site. This can be set to 0 if desired.

e_mod_Repair [kWh/m^2]: float Energy required to complete an in-field, on-site repair to a module. This includes truck trips, and cumulative embodied energy of standard replacement parts (ex: junction box, backsheet tape).

e_mod_MerchantTail [kWh/m^2]: float For the reuse pathway “Merchant Tail”, this implies the module is not removed from the site at EoL and continues to generate energy. The energy associated with this reuse pathway is 0, and this variable is to account for the “benefit” of reuse in place.

e_mod_Demount [kWh/m^2]: float At EoL, modules must be removed from the site, regardless of their final disposition. This is the energy associated with demounting PV modules for EoL disposition. It includes truck trips and tooling needs.

e_mod_Landfill [kWh/m^2]: float The energy associated with transporting the modules to the nearest landfill. Truck trips or potentially train container trips are included in this energy.

e_mod_CollectedDisposition [kWh/m^2]: float For modules not sent straight to the landfill, they are considered “collected” in the mass flow to be actively dispositioned at EoL. This energy accounts for truck trips to a sorting facility, flash tester energy to power test unbroken modules, and any other sorting energies.

e_mod_Resell [kWh/m^2]: float The reuse pathway “resell” implies reuse on the 2ndary market, where a module is removed from the field, tested, and deemed sufficiently functional (>250W or >125W/m^2 of a 2 m^2 module) for resale. Currently, used modules from the USA are being sold out of country. Therefore, this energy value includes energy for minor repairs or testing, cleaning and packaging, and international shipping via container ship.

e_mod_Remanufacture [kWh/m^2]: float Modules which do not pass the collection/disposition flash test (<250W or <125/m^2 of a 2 m^2 module) OR are partially broken (ex: broken frame, cracked backsheet, bad junction box) may have the ability to recover still functional components, such as the glass or silicon cells, for direct reuse in manufacturing - i.e. remanufacture. This energy includes the energy associated with separating the targeted material from the rest of the module.

e_mod_Recycled [kWh/m^2]: float Modules which are sent for recycling. This energy value includes module level recycling process energies, such as removing frames, crushing, grinding and physical separation of materials. Each material then has recycling energy associated with individual material recovery and refinement.

baseline_energy_material

e_mat_extraction [kWh/kg]: float Energies associated with mining and extracting the material to a base level market available product (ex: MG-Si, silver bars)

e_mat_refinement [kWh/kg]: float Energies associated with turning the base level material product into the component or material composition used in PV manufacturing. This includes further purification steps as well as processing. These steps are particular to each material (ex: silicon from MG-Si to 9N Si, silver bar to silver paste). This includes the cumulative embodied energy of all non-tracked but process necessary materials, such as solvents, additives, in addition to all production steps required to generate the PV material product.

e_mat_MFG [kWh/kg]: float Energies associated with the material specificstep of a PV manufacturing line. This includes the equipment energy as well as the cumulative embodied energy of process necessary materials such as solvents. (ex: screen printing silver, IPA/acetone cleaning solvents)

e_mat_MFGScrap_Landfill [kWh/kg]: float The energy associated with landfilling the manufacturing scrap material. This includes truck trip to the landfill.

e_mat_MFGScrap_LQ [kWh/kg]: float The energy associated with recycling the MFG scrap to a low quality. This is the lowest energy level of recycling for a material. This includes all material specific processing and refining to return it to base level market available product.

e_mat_MFGScrap_HQ [kWh/kg]: float The energy associated with the refinement steps necessary to take the base level market product to a higher purity/quality such that it could be reused for PV Manufacturing or in a comparable alternate use (ex: computer chips). This energy is additive to e_mat_MFGScrap_LQ.

e_mat_MFGScrap_HQ4MFG [kWh/kg]: float The energy associated with making the refined material into the PV specific material for PV Manufacturing. This energy is additive to e_mat_MFGScrap_LQ and e_mat_MFGScrap_HQ. *SHOULD THIS BE DIFFERENT THAN HQ?*

e_mat_EoL_Remanufacture [kWh/kg]: float The energy associated with cleaning and prepping the material targeted for remanufacture such that it can be directly reused in MFG.

e_mat_RecycleScrap_Landfilled [kWh/kg]: float The energy associated with landfilling the inefficiencies from the material recycling process. This inlcudes truck trip to the landfill.

e_mat_Recycled_LQ [kWh/kg]: float The energy required to recycle the EoL material to a base level market available product. This includes process energy as well as cumulative embodied energy of process necessary non-tracked materials like solvents.

e_mat_Recycled_HQ [kWh/kg]:float The energy associated with the refinement steps necessary to take the base level market product to a higher purity/quality such that it could be reused for PV Manufacturing or in a comparable alternate use (ex: computer chips). This energy is additive to e_mat_Recycled_LQ.

e_mat_Recycled_HQ4MFG [kWh/kg]: float The energy associated with making the refined material into the PV specific material for PV Manufacturing. This energy is additive to e_mat_Recycled_LQ and e_mat_Recycled_HQ.

Outputs of Energy Calculations

mod_MFG:float The annual energy flow of energy associated with Manufacturing of each yearly cohort.

mod_Install:float The annual energy flow of energy associated with installing of each yearly cohort.

mod_OandM:float The annual energy flow of energy associated with O&M of all effective Capacity.

mod_Repair:float The annual energy flow of energy associated with repair of failed Modules that undergo repair pathway.

mod_Demount:float The annual energy flow of energy associated with demounting modules at end-of-life.

mod_Store:float The annual energy flow of energy associated with modules at end-of-life that undergo storage pathway.

mod_Resell_Certify:float The annual energy flow of energy associated with modules at end-of-life that undergo certification adn reselling pathway.

mod_ReMFG_Disassembly:float The annual energy flow of energy associated with modules at end-of-life that undergo dissaembly for remanufacturing.

mod_Recycle_Crush:float The annual energy flow of energy associated with modules at end-of-life that undergo recycling via crushing.

e_out_annual_[Wh]:float The annual energy flow of energy produced by the PV fleet effective capacity, considering installs minus degradation, failures, and modules that have ended their projectl ife.

Energy Data References

Module Energies

Module Manufacturing Energies from:

        1. Phylipsen and E. A. Alsema, Environmental life-cycle assessment of multicrystalline silicon solar cell modules, Netherlands Agency for Energy and the Environment,NOVEM, Netherlands, Sep. 1995.

  2. places

Material Energies

Glass

Silicon

Silver

Copper

Aluminum Frames

Encapsulants

Backsheets

References for Material Energies

Calculations for material baseline values can be found in Jupyter Journals “PV_ICEdocstutorialsbaseline development documentation”. Some of the primary references utilized for these calculations are listed here.

Glass

thickness data: ITRPV 2010-2021 module package (g-g vs g-b): ITRPV 2010-2021

Silicon

wafer thickness, cell size, kerf loss: ITRPV 2010-2021 mono-Si vs mc-Si marketshares: M. Bolinger, J. Seel, and D. Robson, Utility-Scale Solar 2019, LBNL, Dec. 2019. Accessed: Aug. 13, 2020. [Online]. Available: https://emp.lbl.gov/sites/default/files/lbnl_utility_scale_solar_2019_edition_final.pdf and G. Barbose and N. Darghouth, Tracking the Sun 2019, LBNL, Oct. 2019. Accessed: Aug. 13, 2020. [Online]. Available: https://emp.lbl.gov/sites/default/files/tracking_the_sun_2019_report.pdf

Silver

silver per cell: ITRPV 2010-2021

Copper

number of busbars: ITRPV 2010-2021 busbar dimensions: Standard PV Ribbon Datasheet. Ulbrich Solar Technologies. Accessed: Jan. 14, 2021. [Online]. Available: https://www.pvribbon.com/wp-content/uploads/Datasheets/SPR_Datasheet.pdf

Aluminum Frames

framed vs frameless: ITRPV 2010-2021 module size: J. R. Peeters, D. Altamirano, W. Dewulf, and J. R. Duflou, Forecasting the composition of emerging waste streams with sensitivity analysis: A case study for photovoltaic (PV) panels in Flanders, Resources, Conservation and Recycling, vol. 120, pp. 14-26, May 2017, doi: 10.1016/j.resconrec.2017.01.001.

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