Imagine this: your team has developed a groundbreaking bifacial solar module. The lab results are phenomenal, and projections show impressive energy gains. You take this data to financiers, but they hesitate. Their question is simple: „Can you prove these numbers in a bankable PVSyst simulation?“
Suddenly, the gap between a promising prototype and a financeable project feels like a chasm. For investors and project developers, if it’s not accurately modeled in PVSyst, it might as well not exist. Standard datasheets are a starting point, but they often fail to capture the unique behavior of innovative module designs, especially bifacial ones.
This begins the journey from the lab to bankability. It’s a process of transforming precise, empirical test data into the digital DNA of your solar module—the .PAN and .OND files that drive accurate energy yield simulations.
WHAT ARE .PAN AND .OND FILES, AND WHY DO THEY MATTER?
Think of PVSyst as the industry-standard flight simulator for solar projects. Before you build a multi-million-dollar power plant, you run countless simulations to predict its performance, energy output, and ultimately, its financial return.
The .PAN (for the PV module) and .OND (for the inverter) files are the detailed blueprints that tell the simulator exactly how your specific components will behave.
- .PAN File: This is the module’s „digital twin.“ It contains its electrical characteristics, how it responds to different light levels and temperatures, and its physical properties.
- .OND File: This file defines the inverter’s performance, including its efficiency curves and power conversion behavior.
For a project to be bankable, investors need to trust these files implicitly. Generic or inaccurate files lead to unreliable simulations, creating financial risk and undermining investor confidence.
THE DATASHEET DILEMMA: WHEN „STANDARD“ ISN’T GOOD ENOUGH
So, why can’t you just use the numbers from a standard manufacturer datasheet? While useful, datasheets represent an idealized model under specific, controlled conditions (Standard Test Conditions, or STC). The real world is far messier.
In practice, real-world module performance can deviate significantly from datasheet values due to variations in materials, manufacturing processes, and environmental conditions. For innovative technologies like bifacial modules with new encapsulants or cell designs, these deviations are even more pronounced. A datasheet simply cannot capture the nuanced physics of rear-side gain under varying ground conditions (albedo).
That’s why creating custom, empirically validated .PAN files is no longer a luxury—it’s a necessity for projects aiming for accurate forecasting and successful financing.
THE STEP-BY-STEP PROCESS: FROM RAW DATA TO A BANKABLE SIMULATION
Creating a high-fidelity .PAN file is a meticulous process of translating physical measurements into a digital format. It involves characterizing the module under a range of conditions that reflect its future operating environment.
Step 1: Foundational Measurements – The I-V Curve
Everything starts with the I-V (Current-Voltage) curve. This curve is the module’s fundamental electronic signature, showing its power output at different loads under controlled illumination.
To generate a reliable I-V curve, you need a high-precision solar simulator, or „flasher.“ A AAA-class flasher is the gold standard, ensuring the light source is uniform, stable, and spectrally correct. Multiple measurements are taken at various irradiance levels (e.g., 1000 W/m², 800 W/m², 200 W/m²) to build a comprehensive performance map. This detailed dataset forms the core of the PVSyst model, defining how the module responds as the sun’s intensity changes throughout the day.
Step 2: Understanding Temperature – Measuring Thermal Coefficients
Solar modules get hot, and their performance changes with temperature. These changes are defined by three key thermal coefficients:
- Alpha (α): The change in short-circuit current (Isc) with temperature.
- Beta (β): The change in open-circuit voltage (Voc) with temperature.
- Gamma (γ): The change in maximum power (Pmax) with temperature.
While datasheets provide these values, they are often nominal. By precisely measuring the module’s I-V curve in a climate chamber at different temperatures (e.g., 25°C, 50°C, 75°C), you can determine the actual thermal coefficients. This step is critical for accurate energy yield predictions in hot climates.
Step 3: Capturing Light at All Angles – The IAM Profile
The sun isn’t always directly overhead. The Incidence Angle Modifier (IAM) describes how a module’s power output decreases as sunlight hits it at an angle. This factor is crucial for modeling energy production during the early morning and late afternoon.
Generating an accurate IAM profile involves measuring the module’s output while rotating it relative to a stable light source. This empirical data provides a far more realistic input for PVSyst than the theoretical IAM models often used, especially for modules with advanced anti-reflective glass coatings or unique cell structures.
Step 4: The Bifaciality Factor – Quantifying the Rear-Side Gain
This is the most critical—and often mischaracterized—parameter for bifacial modules. The bifaciality factor is the ratio of rear-side power to front-side power under the same illumination.
Simply stating a bifaciality of „70%“ or „80%“ is not enough. A bankable model requires validating this factor through controlled, repeatable lab measurements. This involves flashing the module on the front side, then carefully flipping it and flashing the rear side under identical conditions. This empirical measurement removes ambiguity and provides a verifiable number that financial models can rely on.
Step 5: Assembling the Digital Twin – Creating the .PAN and .OND Files
With all this empirical data—I-V curves at multiple irradiances, precise thermal coefficients, the IAM profile, and a validated bifaciality factor—the final step is to input it into specialized software that generates the PVSyst .PAN file.
Each piece of data populates a specific field within the file, building a comprehensive and accurate digital twin of the module. This isn’t just a collection of numbers; it’s a scientifically validated performance model ready for rigorous energy yield analysis.
WHY EMPIRICAL DATA IS NON-NEGOTIABLE FOR BIFACIAL TECHNOLOGY
For bifacial modules, relying on theoretical or datasheet values is a recipe for inaccurate forecasts. The real-world gain depends heavily on the module’s specific design and materials. Understanding how the different components interact is key, and this can only be determined through material testing and lamination trials. These trials provide the physical basis for the performance characteristics measured in the lab.
By investing in the creation of empirical .PAN files, you are essentially de-risking your technology. This process is fundamental when prototyping new solar module concepts, as it provides the hard data needed to prove their value to the market. It shows investors that your performance claims aren’t just theoretical; they’re backed by verifiable, third-party data. This builds the confidence required to finance your project.
FREQUENTLY ASKED QUESTIONS (FAQ)
What is PVSyst?
PVSyst is a software suite used by engineers, researchers, and investors to simulate the performance of photovoltaic energy systems. It has become the global industry standard for energy yield assessments and is crucial for project financing.
Can I create these files myself from a datasheet?
You can create a basic .PAN file from a datasheet within PVSyst. However, this file will lack the precision and validation of one created from empirical lab measurements. For bankable projects or new technologies, a datasheet-based file is generally considered insufficient.
What’s the difference between a .PAN and an .OND file?
A .PAN file describes the photovoltaic module (the panel), containing its electrical and thermal characteristics. An .OND file describes the inverter, detailing its efficiency in converting DC power from the modules into AC power for the grid. Both are needed for an accurate system simulation.
How often should these files be updated for a module series?
A .PAN file should be generated for each distinct module design. If you make any significant changes to the materials (e.g., new encapsulant, different glass, updated cell technology) or the manufacturing process, a new set of characterization tests should be performed and a new .PAN file created to reflect the updated performance.
YOUR NEXT STEP TOWARDS BANKABLE ENERGY YIELDS
Transforming lab data into a bankable PVSyst model is the critical link between innovation and commercial success. It replaces assumptions with certainty and builds the foundation of trust needed to secure project financing.
If you’re developing the next generation of solar modules, don’t let your hard work get stalled by a simulation gap. Consider how empirical data can validate your performance claims and accelerate your path to market.