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Module Underperformance – Part 1: The Sun’s Potential
Modules can underperform due to a variety of environmental and non-environmental factors. While good design and operational practices can help mitigate non-environmental issues, the environment itself remains unpredictable. We can only estimate its impact and verify or dismiss its influence on system performance. Understanding these variables is essential for accurately assessing the true potential of a solar system.
For owners and financiers, knowing the real risks—not just the average projected by models—can make a big difference. It helps in identifying the actual performance potential of a system, both in modeling and real-time monitoring. This insight ensures more reliable long-term planning and better investment decisions.
So, what are the main environmental drivers? There are several, but they can be broadly categorized into two key areas:
1. **Part 1 – The Sun’s Potential (Weather Data)**
2. **Part 2 – The Sun’s Availability (Snow, Soiling, Shade)**
**Part 1 – The Sun’s Potential**
Weather data, such as that from NREL NSRDB, NASA, or synthetic sources like Meteonorm, forms the foundation of solar performance models. These datasets are crucial because they determine the expected energy output of a system. However, not all weather data files perfectly align with recent trends, which can lead to inaccuracies in predictions.
To reduce risk, it's important to understand the confidence level of your weather data. Here are four ways to do that:
1. **Compare Weather Data to Historical Trends**
By analyzing each year’s weather independently, you can build a statistical confidence level. This allows you to adjust the weather data for greater accuracy. For example, a 40-year analysis of an NSRDB TMY dataset shows how confident we can be in the data.
2. **Use PVSYST Confidence Tools**
PVSYST offers built-in tools to calculate standard (P50) and higher confidence (P90–P99) models based on the input data. These tools help quantify uncertainty and improve model reliability.
3. **Compare PVSYST Results with Statistical Bounds**
You can scale your PVSYST model using P50 and P90 lower bounds from historical data. If the model performs below the lower bound, it's conservative; otherwise, adjustments may be needed for long-term performance guarantees.
4. **Compare Actual Performance with Predicted Models**
Using a weather-adjusted ratio, you can compare real-world performance against the original model. This helps identify discrepancies and refine future projections.
**Who conducts these detailed assessments?**
Pure Power has a dedicated engineering team that specializes in weather analysis, PVSYST modeling, and historical performance reviews. Their expertise ensures accurate assessments and reduces the risk of underperformance in your next project.
By working with experienced professionals, you can save time, reduce costs, and ensure your solar system delivers the performance you expect. Reach out to Pure Power today to learn more about how they can support your renewable energy goals.