The Top 3 by E3
Welcome to E3 Consulting's The Top 3 by E3! We are delighted that you are taking the time to check out our series on the profession of Independent Engineering. Our podcast aims to introduce listeners to project finance and engineering. During each episode, we will examine a topic we encounter in our daily lives as technical advisors. Topics will range from the profession of Independent Engineering to hydrogen, wind, solar, and energy storage, among many others. While we can't touch on everything about a topic during our series, we will provide listeners with the "top three" takeaways. We want to thank Joseph McDade for allowing us to use his music, Elevation, as our theme. Please check him out at https://josephmcdade.com.Again, thanks for listening, and if you have any suggestions for upcoming topics, please reach out to us at e3co@e3co.com. The E3 Crew
The Top 3 by E3
Series Episode Two: Climate Data in PVsyst
Daniel Tarico and Frances Wilberg-Plourde delve into PV system modeling, specifically focusing on using climate data in PVsyst software. The discussion covers how climate data, such as irradiance, temperature, and wind speed, are critical for modeling PV system performance and affect energy production. The data is typically provided in an 8760 format, representing each hour of the year.
Frances explains that PVsyst relies on typical meteorological year (TMY) files, which aggregate data from several years to represent an average year. These files are compiled from various data sources, each with its own methods and algorithms for processing weather data, including satellite and ground-based measurements.
Three primary climate data sources are discussed: the National Solar Radiation Database (NSRDB), Meteonorm, and Solar Anywhere. The NSRDB offers free data with decent accuracy, though it tends to underestimate irradiance and is not recommended for final modeling. Meteonorm, a paid service, offers synthetic data that can be useful for preliminary models but may not be precise enough for financing decisions. Solar Anywhere is considered the most accurate but comes with a cost, providing high spatial and temporal resolution data, which is especially useful for detailed production estimates and project evaluations.
Key takeaways include the importance of using location-specific data for accurate modeling, understanding the differences between data sources and their methods, and the potential benefits of paid data services for high-accuracy predictions, particularly for long-term financial planning.