Everything starts with knowing what to measure, how precisely, and how often.
Every reading is graded on arrival: plausibility bounds, cross-validation against string and plant sums, and communication-quality flags (RS485 · PLC) catch bad data at the source.
Suspect readings are flagged and excluded from calculations automatically — never silently blended in. Data gaps stay visible, not hidden behind an interpolated line.
Every downstream analysis ships with its own confidence grade — how trustworthy the underlying data was, and how sure the result is. Shown in full further down this page.
This resolution is what laboratory-grade performance analysis requires. Most field systems approximate it at the inverter level. SunSniffer delivers it at every module, every string, continuously — checked, graded, and only then handed to the four engines below.
Two identical modules measured on different days — different irradiance, different temperature — can't be compared directly. A raw kWh reading tells you almost nothing about whether a module is actually healthy.
TrueSTC evaluates thousands of suitable voltage and temperature measurements from each monitored module. Data quality rules exclude unsuitable operating phases, cloud effects, shading, gaps and outliers before a repeatable STC-equivalent comparison value is produced. The proprietary calculation remains part of the SunSniffer analytics engine.
The result can be compared with a datasheet starting point, an individual laboratory reference, technically similar modules or an agreed performance threshold. Repeated values create the module's performance history.
Compare that to the alternative: a laboratory flash is a high-quality reference — but a snapshot, gone the moment the module is back in the rack. TrueSTC accumulates instead of snapshotting: thousands of suitable readings pile up over days and weeks, building a repeatable comparison value and a living performance history. See how it was validated ↓
When you need the number, it is already there.
TrueSTC is available as a subscription add-on within the WebPortal.
Bypass diodes are the single most failure-prone electrical component in a PV module. A short-circuit failure is invisible to most monitoring systems until measurable yield loss occurs — by which point the diode may have been under chronic thermal stress for months. A failed diode under reverse current flow is a primary ignition source in solar fires.
DiodeVital continuously analyses the switching cycles, duration, and thermal behaviour of every bypass diode in every junction box, applying Coffin-Manson thermal-fatigue modelling to the accumulated stress history.
It identifies elevated stress before failure — with a number attached, not just a binary fault flag — and flags actual failures in near real time.
Any anomaly-detection system needs an expected-performance baseline to compare against. If that baseline is arbitrary, so are the alerts it produces.
SunSniffer integrates PVLib directly into the analytics platform — the de facto open-source PV performance modelling library, maintained by Sandia National Laboratories with the global PV research community, and used industry-wide to model expected plant performance.
Expected output is calculated for the exact irradiance, temperature and spectral conditions observed at your site. Deviations are flagged as physics-based anomalies — not arbitrary thresholds.
TrueSTC and DiodeVital are proprietary engines — but a number you cannot interrogate is a number you cannot fully trust, and one you definitely cannot adapt to a plant-specific question.
So the workflow around them is open. Inside the WebPortal, a visual workflow editor lets you see every input and result, adjust thresholds, or compose an entirely new calculation from module, string and weather data — a plant-specific threshold, a custom quality metric, a bespoke model.
Saved results become first-class data, traceable back to the raw measurements — feeding reports, or Ray, directly. No exports, no separate spreadsheet, no mystery step in between.
Ray is not a general chatbot answering from what it remembers. Every question is answered by calling TrueSTC, DiodeVital, PVLib or your own SunSniffer Engine workflows — live, over MCP — and narrating only what those calls return.
This is the same architectural choice behind everything else on this page: no step between measurement and answer is hidden. Ray's job is narration and synthesis of real tool output — not invention.
That is also why every answer can be traced back to the raw 15-second measurements behind it, the same way every engine result can — shown next.
Ray works from approved measurements, documented analytics and defined economic or contractual rules. Missing information is shown as a gap; the responsible professional remains in control of the decision.
If the data behind a question is too thin — too few clean readings, no clear-sky day yet, a gap in the string — Ray says so, and tells you what's missing. It does not fill the gap with a plausible-sounding guess.
The available evidence does not compress different measurement tasks into one artificial accuracy number. It separately tests absolute laboratory agreement, transfer of an individual reference to a changed state and detection of soiling losses against an independent field reference.
Across three measurement campaigns, TrueSTC demonstrates very good typical agreement with laboratory flasher values, robust transfer of individual reference values to changed operating states and high-accuracy detection of soiling losses.
Different campaigns, different measurement tasks — no pooled product-accuracy figure.
The full source list behind these figuresGerman engineering has a word for what happens after a loss is confirmed and a crew is sent into the plant: Sockelblindheit — standing in front of a hundred modules with nothing to point at.
Modules in a string are in series: one current flows through all of them, and the strings on one MPP input of the inverter sit at one voltage. When a module weakens, the string current is forced through it anyway — and the loss appears as a drop in that module's voltage. The power loss is real, measurable at the module, and unattributable in the MPP tracker's number.
With many weak modules in a string the effect slides: at some point the accumulated loss pulls the string current itself down. The signature changes — the missing address does not.
That is why SunSniffer measures voltage and temperature at every module: the loss surfaces exactly where it occurs.
What locating the loss recoversThermographic results depend on the operating and viewing conditions of the flight. A different angle, irradiance level, temperature state, wind condition or reflection can change the image. Each campaign also requires image processing and reliable mapping of findings to physical module positions.
In a published Helmholtz comparison, power-loss estimates derived from thermography carried 8.3% uncertainty. Electrical losses below 5% were not reliably identified by the thermal assessment criteria.
Source: Teubner et al. (2017), Comparison of Drone-based IR-imaging with Module Resolved Monitoring Power Data, Energy Procedia 124, pp. 560–566 · in our reference list
Below the thermal threshold, the loss is not underestimated. It is not seen.
See the full drone-vs-continuous comparisonIndependent verification from institutions and operators with rigorous testing standards.
These frameworks provide technical context for PV performance measurement, commissioning and rapid-shutdown interfaces. Product-specific conformity depends on the applicable documentation and project configuration.
All SunSniffer data processing and storage takes place on European servers.
This is not a marketing claim — it is an architectural choice, reflecting the platform's foundation in a country where data sovereignty and engineering precision are taken seriously. GDPR-compliant. Designed for the bankability and audit requirements that institutional solar operators face.
Full technical documentation, whitepapers, and peer-reviewed references are available on request.
We are happy to talk to engineers, scientists, asset managers and consultants at any depth of detail. The science is open. The measurements are real.