Solar Plant Degradation and its Causes

The first drop often appears early through light-induced effects; the larger concern is the slow accumulation of long-term damage across years of operation. [2,3,4,12]

Environmental and operating stressors that accelerate module decline. [4,5,11]

At its core, degradation means lower energy yield, weaker financial performance, and a higher chance that small defects evolve into hotspots, leakage, or component replacement events. [1,4,5]

 

1. Core degradation mechanisms

Several mechanisms can act at the same time. The table below condenses the ones that matter most in day-to-day asset management. [3,4,5,11,12]

 

2. Environmental conditions that speed up decline

• Heat: reduces conversion efficiency immediately and accelerates longer-term chemical aging.

• Humidity: supports corrosion, moisture ingress, insulation loss, and weaker adhesion between layers.

• Dust and soiling: block light, create non-uniform heating, and may slash output in harsh locations.

• Snow, ice, wind, and hail: add mechanical load or shock that can trigger frame stress and microcracks.

• Terrain, altitude, and albedo: change UV intensity, reflected light, and local microclimate around the array.

Climate change matters here.

More extreme heat, stronger storms, shifting rainfall, and ash or smoke deposition can make future degradation patterns harsher than past assumptions.

Degradation tends to compound over the asset life if early issues are left unmanaged. [1,4,5,6,10]

 

3. How operators detect degradation

No single test is enough. High-performing operators combine regular inspections with electrical data and image-based diagnostics so they can move from symptom to root cause faster. [4,7,8,9]

• Visual inspection: finds yellowing, burn marks, corrosion, cracked glass, frame damage, and obvious delamination.

• I–V curve analysis: shows shifts in short-circuit current, open-circuit voltage, fill factor, or insulation behavior.

• Infrared thermography: reveals hotspots, connection resistance problems, and bypass-diode issues.

• Electroluminescence imaging: maps microcracks, inactive cell areas, and hidden electrical defects with high sensitivity.

• Continuous monitoring: tracks performance ratio, string current, and site-to-site variance to flag subtle underperformance.

 

Monitoring is most effective when it closes the loop from data to action. [7,8,9]

The operational goal is simple: identify which issues are harmless drift, which require cleaning or repair, and which are severe enough to threaten lifetime yield or safety. [4,7,8]

 

4. What actually slows degradation

Degradation cannot be eliminated, but it can be slowed materially through better design choices and disciplined operations. [4,5,6,8,12]

Where Enectiva fits in
Advanced monitoring platforms help centralize site data, spot underperformance earlier, and support predictive maintenance. They do not stop degradation physics, but they do reduce avoidable losses by shortening the time between anomaly and intervention.

Degradation curve and how it’s calculated

A degradation curve plots normalised PV performance versus time. For modules, this is often % of rated power. For plants, use weather‑normalised PR or kWh/kWp so year‑to‑year irradiance differences don’t distort the trend.

Step-by-step calculation process (clear workflow)

• Step 1 — Choose the metric: module power (%), PR, or kWh/kWp.
• Step 2 — Clean the data: remove periods of known outages, curtailment, commissioning changes, and major repairs.
• Step 3 — Normalise: correct for irradiance and temperature where possible (especially for plant-level PR).
• Step 4 — Build a time series: calculate the metric monthly or annually at consistent intervals.
• Step 5 — Estimate degradation rate using one of the methods below, then validate it against events (cleaning, repairs, inverter swaps).

Calculation methods you can use

Method A (recommended for plants): linear regression slope

Fit a straight line to normalised performance (e.g., monthly PR) vs time. The slope (negative) is the degradation rate. This is widely used because it reduces noise from weather and operations.

Method B: simple average annual loss (quick estimate)

Degradation rate (%/year) ≈ ((P₀ − Pₙ) / P₀) ÷ n × 100

Where P₀ is initial performance and Pₙ is performance after n years.

Method C: compounded (exponential) degradation (common in modelling)

Assume a constant annual factor:

Pₙ = P₀ × (1 − r)ⁿ

Solve for r:

r = 1 − (Pₙ / P₀)^(1/n)

Worked example

Assume P₀ = 100% and Pₙ = 88% after n = 20 years.

• Simple average: (100 − 88)/100) ÷ 20 × 100 = 0.6% per year
• Compounded: r = 1 − (0.88)^(1/20) ≈ 0.64% per year

Bottom line
Solar degradation is inevitable, but unmanaged degradation is optional. The winning combination is durable design, climate-aware maintenance, and data-driven operations that preserve long-term energy yield.

Conclusion

Solar degradation is inevitable but unmanaged losses are optional. The most cost-effective way to protect lifetime yield is to separate true aging (the long-term trend) from avoidable underperformance (soiling, shading, loose terminations, inverter derating, and downtime). A degradation curve built from normalised metrics (PR or kWh/kWp) makes this visible. With disciplined inspections, fast fault response, and data-driven O&M, most plants can keep ‘apparent degradation’ close to the expected curve and improve ROI.

References

[1] Jordan, Dirk C., and Sarah R. Kurtz. "Photovoltaic Degradation Rates—An Analytical Review: Preprint." National Renewable Energy Laboratory (NREL), June 2012. https://docs.nrel.gov/docs/fy12osti/51664.pdf

[2] Sopori, Bhushan, Prakash Basnyat, Srinivas Devayajanam, Sudhakar Shet, Vishal Mehta, Jeff Binns, and Jesse Appel. "Understanding Light-Induced Degradation of c-Si Solar Cells: Preprint." NREL, 2012. https://docs.nrel.gov/docs/fy12osti/54200.pdf

[3] Luo, Wen, Yidong Shen, Alexandre S. M. Vaughan, and others. "Potential-induced degradation in photovoltaic modules: a critical review." Energy & Environmental Science, 2017. https://docs.nrel.gov/docs/fy17osti/67341.pdf

[4] Köntges, Marc, Sarah Kurtz, Corinne Packard, Ulrike Jahn, Karl A. Berger, Kazuhiko Kato, Thomas Friesen, Haitao Liu, and Mike Van Iseghem. "Review of Failures of Photovoltaic Modules." IEA PVPS Task 13 Report T13-01:2014, March 2014. https://iea-pvps.org/wp-content/uploads/2020/01/IEA-PVPS_T13-01_2014_Review_of_Failures_of_Photovoltaic_Modules_Final.pdf

[5] Köntges, Marc, Gernot Oreski, Ulrike Jahn, Magnus Herz, Peter Hacke, Karl-Anders Weiss, Guillaume Razongles, Marco Paggi, David Parlevliet, Tadanori Tanahashi, and Roger H. French. "Assessment of Photovoltaic Module Failures in the Field." IEA PVPS Task 13 Report T13-09:2017, May 2017. https://www.tuv.com/content-media-files/master-content/services/products/p06-solar/solar-downloadpage/report-iea-pvps-t13-09_2017_assessment-of-pv-module-failures-in-the-field.pdf

[6] Schill, Christian, Anne Anderson, Christopher Baldus-Jeursen, Laurie Burnham, Leonardo Micheli, David Parlevliet, Eric Pilat, Bengt Stridh, and Elías Urrejola. "Soiling Losses – Impact on the Performance of Photovoltaic Power Plants." IEA PVPS Task 13 Report T13-21:2022, December 2022. https://iea-pvps.org/wp-content/uploads/2023/01/IEA-PVPS-T13-21-2022-REPORT-Soiling-Losses-PV-Plants.pdf

[7] Jahn, Ulrike, Magnus Herz, Marc Köntges, David Parlevliet, Marco Paggi, Ioannis Tsanakas, Joshua S. Stein, Karl A. Berger, Samuli Ranta, Roger H. French, Mauricio Richter, and Tadanori Tanahashi. "Review on Infrared and Electroluminescence Imaging for PV Field Applications." IEA PVPS Task 13 Report T13-10:2018, March 2018. https://iea-pvps.org/wp-content/uploads/2020/01/Review_on_IR_and_EL_Imaging_for_PV_Field_Applications_by_Task_13.pdf

[8] Perry, Kirsten, Quyen Nguyen, Dirk Jordan, Chris Deline, and Burton Putrah. "Relating Aerial Infrared Thermography Defects to Photovoltaic Performance: Preprint." NREL/CP-5K00-90316, June 2024. https://docs.nrel.gov/docs/fy24osti/90316.pdf

[9] Chaplains, Eleftheria. "PV cell and module degradation, detection and diagnostics." World Renewable Energy Congress, 2014/2016 conference paper. https://ueaeprints.uea.ac.uk/56369/1/EKaplani_PVdegradation_WREC2014_paper.pdf

[10] IPCC. "Climate Change 2023: Synthesis Report." Intergovernmental Panel on Climate Change, 2023. https://www.ipcc.ch/report/ar6/syr/downloads/report/IPCC_AR6_SYR_FullVolume.pdf

[11] Sinha, Ashutosh, and others. "UV-Induced Degradation of High-Efficiency Silicon PV Modules with Different Cell Architectures." Progress in Photovoltaics, 2023. https://docs.nrel.gov/docs/fy23osti/81471.pdf

[12] Köntges, Marc, Jay Lin, Alessandro Virtuani, Gabriele C. Eder, Junjie Zhu, Gernot Oreski, Peter Hacke, Joshua S. Stein, Laura Bruckman, and others. "Degradation and Failure Modes in New Photovoltaic Cell and Module Technologies." IEA PVPS Task 13 Report T13-30:2025, February 2025. https://iea-pvps.org/wp-content/uploads/2025/02/IEA-PVPS-T13-30-2025-REPORT-Degradation-and-Failure.pdf

[13] TNO. "Failure Rate of Photovoltaic Modules and Their Collection Numbers for Recycling." TNO 2025 R12777, December 2025. https://publications.tno.nl/publication/34645527/9HO99RIY/TNO-2025-R12777.pdf