If you want real long-term reliability data for PV modules, you rarely get a better testbed than a mountain.
On Loser near Altaussee, a PV plant commissioned by Energie AG has been operating since 1988 (built 1988–1989): 30 kW, 598 modules, about 32,000 kWh/year, installed at roughly 1,600 m elevation, facing south at 60° tilt. Over three decades, this site has effectively delivered field reliability data under harsh alpine conditions (snow/ice load, weather exposure, thermal cycling).
The key takeaway isn’t “PV degrades” (everything does). It’s this:
PV is fundamentally durable — but the spread in lifetime performance is driven by BOM.
1) Same environment, different outcomes: BOM is the lever
The plant uses three 1988-era module types (Siemens, Arco, Kyocera) — a rare apples-to-apples comparison under the same operating conditions.
Field / subsystem long-term figures show clearly different degradation levels:
- Arco: -20.4% total (≈ -0.68%/year)
- Siemens: -13.4% total (≈ -0.45%/year)
- Kyocera: -6.1% total (≈ -0.20%/year)
The poster summarizes the likely root cause directly: differences in design and BOM (e.g., cells, backsheets, encapsulants) can “drastically” influence annual degradation..
2) Why encapsulant × backsheet matters so much
When we talk about BOM, we don’t mean “nice-to-have details.” In the field, material selection determines how well the laminate protects cells and interconnects from moisture ingress, corrosion, and chemical aging.
The Loser poster describes distinct material-related patterns across the three types:
- Siemens: yellowing attributed to a change at the backsheet/encapsulant interface — with no impact on electrical performance reported.
- Kyocera: no material degradation and low annual losses.
- Arco: encapsulant discoloration, many glass breaks, and effects impacting electrical performance.
Notably, the subsystems were identified as using EVA encapsulant and TPT (Tedlar/PVF) backsheet, yet the failure signatures differed significantly by type.
This strongly suggests it’s not just “EVA yes/no” — it’s the material pairing + processing + interface stability that shapes the degradation pathway.
3) Why EL and flash tests can miss the real risk
Standard tests like EL and flash/I-V are valuable — they tell you what a module can deliver today and help reveal typical electrical defects.
But the Loser case highlights something critical for repowering and second-life decisions: material/interface effects can progress without immediately showing up electrically. The poster explicitly notes interface-related discoloration “without impact on electrical performance.”
For second-life economics, that’s the difference between:
For second-life economics, that’s the difference between: “It passes today” and “It’s likely to remain stable.” In other words: you need a risk view, not only a snapshot.
4) The 2nd Cycle approach: understand materials → quantify risk → scale reuse
This is exactly where 2nd Cycle focuses: making PV circularity scalable with reliable decisions across reuse, repair, and recycling.
How we translate inspection into a reuse decision:
We complement electrical testing with a standardized, high-resolution condition assessment and material classification, so modules can be grouped into material/risk classes rather than judged by appearance or a single measurement.In practice, that means combining:
- high-resolution visual condition capture and photometric methods,
- UV-based condition signals (many aging signatures become far more discriminative),
- spectroscopic material identification. (NIR as non-destructive material identification approache).
Those signals are then interpreted through a multi-stage AI evaluation (quality control → classification → risk scoring). The goal: consistent decisions at scale, not one-off expert judgement.
5) What operators, EPCs, and O&M teams should take away
- PV is proven durable — even in demanding alpine conditions.
- BOM drives lifetime risk — especially the encapsulant/backsheet interface as a protection system.
- EL/flash are necessary, not sufficient if you want to price second-life risk properly.
- Circularity at scale needs material condition + data, not assumptions.
Outlook
Material characterization is the next step that turns a “great case study” into repeatable, scalable decision logic. And Loser provides an unusually strong foundation: harsh environment, long runtime, and real-world data.
If you’re dealing with underperforming strings or repowering decisions, we can help assess your modules and translate results into clear actions:.Contact.
Bild PV-Anlage Loser im Winter © Energie AG