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Rounak Kharait, E3's Executive Director of Solar, and Daniel Tarico, E3's Director of Renewables, discuss solar O&M cost models, suggesting that they need to be changed and made more realistic to reflect the true lifecycle maintenance requirements of utility-scale projects. Some of the highlights of the podcast are shown below:

• Daniel brings expertise from metallurgy, construction, and tracker manufacturing to solar O&M discussions
• Early solar financing models incorrectly assumed minimal maintenance would be needed throughout project lifetimes
• Solar plants experience increasing failure rates and maintenance costs as they age, similar to automobiles or other mechanical products
• Standard assumptions ignore the wear-out aspect of aging equipment
• Without the ITC, economic models must shift to focus on long-term performance and realistic maintenance budgeting
• Projects in markets where production is the primary value driver need more accurate revenue and OPEX models
• Major equipment can last a long time if designed well and properly maintained

If you have questions or suggestions for future podcast topics, please reach out at to us at e3co@e3co.com. The full white paper on this topic is available for download on our website .

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In this final episode in the PVsyst series, Daniel Tarico and Frances Plourde discuss the impact of system design on photovoltaic (PV) system modeling, focusing particularly on shading losses and module mismatch within the context of using the PVsyst software.

Frances also covers light-induced degradation (LID), which happens when PV modules are first exposed to sunlight, particularly affecting crystalline silicon modules with certain dopants. LID is a one-time effect but can reduce module efficiency by 1-3%. This factor must be accounted for when designing and modeling PV systems, especially for long-term performance projections.

The conversation highlights the importance of considering the long-term effects of module degradation, mismatch losses, and shading when designing and financing PV systems.

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In the third episode of the PVsyst series, Daniel Tarico and Frances Wilberg-Plourd from E3 discuss the interpretation of PVsyst reports and how they relate to PV system energy estimation, specifically focusing on how PVsyst calculates energy production using statistical probabilities.

Key points:

1. PVsyst Report Overview: The report begins with system inputs such as equipment, location, orientation, and shading factors, and then presents energy estimates, including monthly generation based on climate data. The final report includes an energy waterfall diagram showing energy production and losses on both the DC and AC sides of the system.
2. P50 and Probabilistic Estimates: The P50 value represents the long-term average expected energy production. It's based on probabilistic modeling, considering weather variability. The system's actual performance will, in some years, exceed or fall short of the P50 estimate, with a 50/50 chance of being above or below the predicted value.
3. Other Probabilistic Levels (P75, P99): Other probabilities, like P75 and P99, indicate more conservative estimates. The P99 represents energy production that the system is expected to exceed in 99% of years. These are useful for ensuring energy and revenue guarantees.
4. Degradation and Performance Tracking: Module degradation typically leads to a half-percent annual decrease in energy production, impacting long-term projections. If system production drops faster than expected, it might indicate issues requiring attention.

The episode emphasizes the importance of accurate and up-to-date data in PVsyst reports to ensure reliable energy and financial forecasts.