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Record W4401855077 · doi:10.2172/2432497

PV Lifetime Project (2024 NREL Annual Report)

2024· report· en· W4401855077 on OpenAlexaboutno aff
Chris Deline, Dirk Jordan, Bill Sekulic, Josh Parker, Byron McDanold, A. Anderberg

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
FundersOffice of Energy EfficiencySolar Energy Technologies OfficeSandia National LaboratoriesU.S. Department of EnergyOffice of Energy Efficiency and Renewable EnergyNational Renewable Energy Laboratory
KeywordsPhotovoltaic systemIrradianceDegradation (telecommunications)Environmental scienceSolar irradianceMeteorologyAtmospheric sciencesElectrical engineeringPhysicsEngineeringOptics

Abstract

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DOE's PV Lifetime project was initiated in 2016 with the goal of accurately characterizing the early-life evolution of photovoltaic (PV) field performance.Different PV cell and module technologies result in different initial degradation rates due to effects like light-induced degradation (LID) and light & elevated temperature-induced degradation (LeTID).To accurately characterize the initial field degradation of maximum power (Pmp) requires the use of high-accuracy indoor IV curve measurements at standard test conditions.Therefore, PV modules involved in this study are removed from the field once or twice per year and brought indoors for measurement under constant temperature and irradiance conditions.Current samples deployed and monitored in this way include Jinko Solar (2016), Trina Solar (2016), Hanwha Q-Cells (2017), Panasonic (2018), LG (2018), Canadian Solar (2018), Mission Solar (2019).Modules from Sunpreme (2019), and LONGi (2020) have been deployed and were first reported on in the 2022 report.For this report, initial baseline measurements for two additional partners are included: REC (2023) and Solaria (2023).Overall annual degradation rates are as follows: our first modules to be deployed (Jinko and Trina) have annual median degradation rate between -0.35%/yr and -0.55%/yr, mainly concentrated in the first year.The QCells mono-PERC and multi-PERC modules have an annual degradation rate of -0.4%/yr and -0.3%/yr respectively, also concentrated in the first year of operation.Mission Solar, LG and LONGi modules are all displaying modest degradation, better than -0.25% / year.Indeed, Mission Solar fielded modules degraded less than their control modules which remain indoors and un-exposed.By comparison, the Sunpreme n-HIT bifacial modules are showing a rapid loss rate around -2%/yr, or almost -8% total to date.This is largely attributed to loss in front-side Isc, and this rapid loss has been corroborated by comparing against RdTools degradation analysis, using real-time field performance data.Several module types exhibit strong seasonal performance change, consistent with LeTID susceptibility.This is characterized by lower indoor IV measurement after prolonged hightemperature exposure, and a recovery during cooler temperatures.This can result in a sawtoothtype response when sequential indoor measurements are taken in the spring and again in the fall.These types of profiles are visible in Jinko, Trina and Mission Solar module types.It is possible that Canadian Solar multi-PERC also follows this trend, but the measurement timing has not lined up to confirm this possibility.An analysis was conducted on the initial module performance relative to their nameplate rating.Most module types had initial performance right at nameplate rating, or within 1%: Jinko, Trina, LONGi, Panasonic, QCells and REC N-peak (TOPCon).Other module types came in 2% -3% below nameplate: Mission Solar and Solaria.The REC 405 Pure Alpha came 3%-4% below nameplate, which is outside of its stated accuracy bounds.It wasn't all bad news -LG modules were measured at 2% above nameplate.Finally, the Sunpreme heterojunction modules had inconsistent measurements which made it difficult to make any statements on their nameplate accuracy.v This report is

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.325
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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