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Photovoltaic Lifetime Project

High-accuracy public data on photovoltaic (PV) module degradation from the Department of Energy (DOE) Regional Test Centers, along with updated methodologies, will increase the accuracy and precision of degradation profiles calculated for representative PV hardware installed in the U.S.

Project developers' assumptions on the initial performance of PV systems can affect calculations of project finance and commercial viability. Due to the typical slow pace of PV module degradation—often less than 1% per year—the reported degradation can be undetectable (within measurement uncertainty) for the first several years of operation. However, with careful indoor current-voltage (I-V) curve methods and higher frequency of measurement, greater accuracy in degradation profile can be distinguished. This effort investigates equipment widely deployed across the U.S. and addresses multiple deployment climates. In particular, a focus is on early-life degradation of PV modules, which may indicate stepwise degradation functions that are too subtle to be detected through typical outdoor monitoring. Because of the leveraged nature of PV project finance, low initial degradation is more beneficial than constant degradation through the project lifetime (see figure below).

A chart, showing low initial degradation results, has a gray triangle in the center

Low initial degradation (green curve) results in more-economical PV installations. Frequent intermediate measurements are required to distinguish one degradation profile from the other.

Tools and Capabilities

  • Long-term deployment of PV systems with public data through the Regional Test Centers (RTCs)
  • Validation and development of degradation rate standards
  • Degradation assessment of existing PV system data.

Projects

Current activities are funded by the DOE Energy Efficiency and Renewable Energy Office through the PV Lifetime Project and the SunShot National Laboratory Multiyear Partnership (SuNLaMP) project. Currently, three PV module types are being investigated through the PV Lifetime Project. Additional module types will be installed in following years. Additional system information can be found at Sandia National Laboratories' PV Performance Modeling Collaborative website and in the following publications: 

Jinko Solar

Photo of blue solar panels mounted on the ground.

Jinko Solar PV Lifetime installation at NREL.

PV systems composed of 28 modules each of Jinko JKM260P-60 and Jinko JKM265P-60 modules were deployed at the National Renewable Energy Laboratory (NREL) (Golden, CO) and Sandia (Albuquerque, NM). The systems are grid-tied through an ABB TRIO 20.0 inverter, in two strings of 14 modules apiece.

Initial results from the NREL site: Initial baseline PV data were taken September 2016, with the modules installed at Voc October 2016. The PV system was grid-tied in April 2017. An initial light-induced degradation of ˜1.5% was detected following 10+ kWh/m2 of light exposure.

A chart, showing one year performance loss totals for PV modules, has a downward trend and blue line across the top.

Jinko Solar JKM260 year-1 performance loss totals -3.7% including initial LID. A seasonal recovery is visible in the second year (possibly due to LeTID — the modules were confirmed to be LeTID sensitive in indoor tests). Overall 24-month change: -4% (including LID). Red trace shows indoor control modules.

A bar graph showing field degradation in annual IV curves. Mean: -1.20
A bar graph showing field degradation in annual IV curves. Mean: -2.21
A bar graph showing field degradation in annual IV curves. Mean: -0.17

Annual IV curves indicate the -1.4% field degradation was primarily from Isc and Voc loss.

Trina Solar

Photo of blue solar panels mounted on the ground.

Trina Solar PV Lifetime installation at NREL.

PV systems composed of 28 modules each of Trina TSM-PD05.08 260W and Trina TSM-PD05.05 255W (Black backsheet) modules were deployed at NREL (Golden, CO) and Sandia (Albuquerque, NM). The systems are grid-tied through an ABB TRIO 20.0 inverter, in two strings of 14 modules apiece.

Initial results from the NREL site: PV module baseline data were taken in October 2016, with modules installed October 26, 2016. The PV system was grid-tied in April, 2017. An initial light-induced degradation of less than 1% was detected following 10 kWh/m2 of light exposure.

A chart, showing modest change in the Trina PV modules, has a slight downward trend and a blue line across the top.

The majority of Trina modules measured showed modest change, with -2% loss in the first year including LID. One outlier module (M1610-0043) showed initially low STC performance and greater than typical year-1 loss (-4%) as well as a much more pronounced seasonality in year 2. This particular module specimen may also be LeTID sensitive.

QCells

Photo of a PV solar array.

QCells PV Lifetime installation at NREL.

PV systems composed of 28 modules each of QCells Q.Plus BFR-G4.1 280 (multi-PERC) and Q.Peak BLK-G4.1 290 (mono-PERC, black backsheet) modules were deployed at NREL (Golden, CO) and Sandia (Albuquerque, NM). The systems are grid-tied through an ABB TRIO 20.0 inverter, in two strings of 14 modules apiece.

Initial results from the NREL site: PV module baseline data were taken in July 2017, with modules installed October 27, 2017. An initial light-induced degradation of less than 1% was detected following 10 kWh/m2 of light exposure.

A chart, showing one year performance loss totals for OCells, has a steep downward trend and two blue lines across the top.

Initial year-1 performance loss of QCells Q-Peak 290 (monocrystalline PERC) modules totaled -3% including initial LID. Q-Plus 280 (multicrystalline PERC) showed a similar -2.5% first year loss.

Panasonic, Canadian Solar, LG

Photo of a row of solar panels installed at NREL.

Panasonic PV Lifetime installation at NREL.

Three separate PV systems were deployed in 2018, composed of 30 modules of Panasonic VBHN3305A16 (Heterojunction “HIT”), 28 modules of Canadian Solar CS6K-300MS (Mono-PERC), and 28 modules of LG LG320N1K-A5 (N-Type Mono-Si “NeON2”). The systems are grid-tied through HiQ ProHarvest inverters, in two or three strings apiece.

Initial results from the NREL site: PV module baseline data were taken in June 2018, with modules installed June - October 2018. Initial LID performance changes following 20 kWh/m2 of light exposure differed depending on product technology: Panasonic: +0.6%.  Canadian Solar: -0.5%. LG: 0%.

Mission Solar, Prism Solar, Sunpreme Bifacial Tracker

Photo of the PV cells on the underside of bifacial solar panels, with two men installing the system in the background.

Bifacial Tracker installation at NREL.

A 10-row single-axis tracked system was installed at NREL in 2018-2019. The site supports three PV Lifetime systems: 20 modules each of Mission Solar MSE360SQ6S (Mono-PERC), Sunpreme Maxima HxB 400 (bifacial HJT), and Prism Solar Bi72 (bifacial PERC). The systems are grid-tied through SolarEdge SE20k inverters, and utilize module-level power optimization to identify rear irradiance mismatch throughout the system.

PV module baseline data were taken in early 2019, with modules installed March 2019. A subset of data will be made available publicly. Stay tuned!

Photovoltaic Degradation Publications

Journal articles, technical reports, conference papers, and outreach documents related of PV degradation rate are published through DOE SuNLaMP-sponsored work. Check out a summary of pertinent available DOE-sponsored research on degradation rates.

RdTools (2017)

RdTools is a set of Python scripts and software for analysis of photovoltaic time-series data. The open-source tools were developed in collaboration with industry to bring together best practices and years of degradation research from NREL.

Additional details on software methodology and updates can be found on the RdTools info page and on the GitHub software repository.

Two graphs labeled "Clear-sku-based degradation Results"

RdTools system analysis includes filtering, normalization based on measured or modeled irradiance and degradation distribution calculation.

Progress and Frontiers in PV Performance (2016)

Different reliability failure modes may present themselves as performance loss that is non-linear, or piecewise linear. The crystalline silicon PV module below exhibited stable performance from 2006 through 2016 until a cell crack led to a hot spot and a sudden non-linear performance drop in maximum power.

Two charts showing I-V measurements with four different colored lines.

The complete presentation on degradation can be found as part of an SPI 2016 workshop.

Insights into PV Levelized Cost of Energy through a New Degradation Study (2016)

An update to the original PV Degradation Rates paper has summarized over 11,000 data points and has distinguished between high-quality studies (multiple measurements) and single-point measurements that depend on the nameplate value of PV modules being correct. Using only high-quality data for crystalline silicon modules yields a degradation rate of 0.5% per year. See the blog post and the complete paper.

A chart showing degradation rates with three different colored lines.

Histograms of all data, high-quality data, and the median per study and system presented as the normalized frequency (a). Cumulative distribution functions for high-quality crystalline silicon systems and modules (b). The median is indicated by a dashed horizontal line; 0.5%/year and 1%/year degradation are indicated as a dashed and dash-dotted line, respectively. The number of data points for the respective subsets is given in parentheses.

PV Degradation Methodology — A Basis for a Standard (2016)

Real-time outdoor data can be mined to extract system and module performance. However, the methodology used to filter and analyze the data can directly impact the calculated rate, particularly for short data time-series. In particular, two methods are compared: standard linear regression, and a year-on-year method.

A scientist works on a PV panel.

Outdoor data can indicate system degradation with time, but seasonal performance obscures underlying degradation trends.

1603 Treasury Data Lifts the Veil on PV System Performance (2014)

An analysis of 1.7 gigawatts of PV installations (> 50,000 unique systems) has shown several trends. The first is that large-scale reliability problems have not been a problem in the first four operational years of these systems. Secondly, the systems in general performed better than expected—by 2%–4% on average. View the blog post and download the complete papers (paper 1 and paper 2).

A map of the United States with black dots showing the solar installations.

Geographic distribution of installations included in the 1603 Treasury grant system survey (over 50,000 systems)

A chart showing the degradation rate compared to the frequency with blue bars and one red line.

Photovoltaic Degradation Rates — An Analytical Review (2011)

A review of the existing literature has identified 2,000 uniquely measured degradation rates. Median degradation rates for these modules are 0.5% per year. A long tail of lower-reliability products increases the average to 0.8% per year. This study was updated in 2016 (see above) with a significantly increased sample size. Read the original study.

Contact Us

For additional questions or comments, please contact the RTC team overseeing this effort:

Dr. Chris Deline

Colorado RTC Lead, Colorado PV Lifetime Lead

Dr. Deline is the Colorado RTC Lead and leads the PV Lifetime effort at NREL. He is an NREL engineer who specializes in the characterization, modeling, and analysis of PV systems, especially under non-optimal (e.g., shaded) conditions.

Email

Dr. Dirk Jordan

NREL Senior Reliability Engineer

Dr. Jordan is a senior reliability engineer at NREL heading up analytical research on PV performance and reliability. Dr. Jordan is a six-sigma black belt and has authored some of the most-cited papers on PV degradation rates.

Email

Dr. Joshua Stein

SANDIA PV Lifetime Lead

Dr. Stein is a distinguished member of the technical staff at Sandia and the author of many papers related to the performance modeling of solar systems.

Email