The global solar photovoltaic (PV) industry is at a critical juncture, with technological and financial advancements demanding a paradigm shift in how project simulations are conducted. Marcel Suri, CEO of Solargis, emphasizes the urgent need for new industry standards to underpin greater efficiency, accuracy, and market resilience, particularly as reliance on outdated datasets jeopardizes the financial viability of modern, complex PV installations. The current landscape, marked by sophisticated technologies like bifacial modules and intelligent trackers, necessitates a deeper, data-driven approach to performance modeling.

Historically, simple empirical models and low-resolution Typical Meteorological Year (TMY) datasets sufficed for PV simulations. However, TMY, which aggregates historical data into an "average" year, fails to account for critical short-term (intra-hourly), interannual, and long-term climate variability, including extreme weather events. Its hourly time resolution smooths out crucial fluctuations, leading to overly optimistic predictions and sub-optimal system designs that cannot anticipate "non-typical" weather scenarios, thereby skewing expected performance and jeopardizing financial viability.

To mitigate these risks, the industry must adopt high-resolution Time Series data as the new standard. This approach breaks down each year into 15-minute intervals, spanning up to 30 years of history, providing over a million data points per parameter compared to the 8,760 in hourly TMY models. This granularity allows developers to capture rapid changes in solar radiation, understand year-on-year variations, and distinguish between natural cycles and climate change trends, enabling more accurate PV design, performance evaluations, and ultimately, more bankable projects in an unpredictable climate.

The proliferation of bifacial PV modules, offering higher energy yields, further underscores the need for advanced modeling. Traditional PV simulation tools, relying on simplified isotropic sky models, struggle to accurately simulate rear-side solar radiation for bifacial modules. This leads to inaccurate energy yield estimates and sub-optimal system designs. Solargis advocates for the adoption of physical-based models, such as ray tracing combined with the anisotropic sky model, which captures the dynamic behavior of the sky dome and surrounding surfaces. Coupled with accurate site-specific ground albedo data and sub-hourly time series data, these advanced computation techniques ensure precise simulations, allowing developers to fully realize the potential and reliable financial returns of bifacial technology.

Beyond data and modeling, the industry faces persistent challenges from outdated approaches, lack of standardization, and insufficient verification of technical specifications for PV components, notably modules (PAN files) and inverters (OND files). The current plain text file formats are prone to uncontrolled modification and sharing, leading to inaccuracies, inefficiencies, and disputes. This reliance on unverified data extends beyond simulations, impacting project design and overall bankability. Establishing robust standards for accessing, using, and distributing these critical specifications is essential to enhance the accuracy of simulations and ensure the overall success and financial confidence in solar projects.