Production models serve as crucial benchmarks for the performance of solar projects and, ultimately, their financial returns. Financial institutions enlist independent engineers (IE) to scrutinize production models provided by developers and independent power producers (IPPs) in order to make pivotal investment decisions. Developers and IPPs embarking on long-term projects also analyze production models to weigh module options beyond upfront expenses, aiming to identify the solutions that will yield the greatest value throughout the project’s lifespan.

Performance models depend on PAN files to capture the characteristics of a solar module that influence its performance. The precision of module data within these files is crucial for producing reliable performance forecasts. Regrettably, PAN files are frequently accepted without thorough scrutiny of the underlying data or an assessment of their alignment with the actual information. It is imperative for stakeholders in solar projects to recognize the discrepancies in PAN files, grasp how variable data can directly influence performance models, and undertake comprehensive evaluations to ascertain the bankability of PAN files to the fullest extent possible.

PAN files, denoted by the extension “.PAN,” are compact text files that hold the necessary data for characterizing a module’s performance. Although primarily utilized for simulations in the well-known software PVsyst, they can also be applied in various other production modeling tools.

Suppliers usually furnish PAN files, which may stem from either manufacturer or third-party testing laboratory data. A PAN file comprises several distinct components, each playing a role in the module’s performance during simulation: