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Predict solar project energy output
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Detailed solar resource validation and assessment
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Combining satellite data with on-site measurements
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Estimated energy uncertainties and related data inputs
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Energy estimate for refinancing or asset acquisition
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Understand output variability across wide geo regions
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See below the PVPMC webinar organized by Sandia where Branislav Schnierer, PV Modeling Specialist from Solargis talked about the technical aspects of self-shading analysis.

Watch the webinar here.

Download presentation slides from here.

Keep reading

Why to use satellite-based solar resource data in PV performance assessment
Best practices

Why to use satellite-based solar resource data in PV performance assessment

It is widely accepted that high-standard pyranometers operated under rigorously controlled conditions are to be used for bankable performance assessment of photovoltaic (PV) power systems.

How Solargis is improving accuracy of solar power forecasts
Best practices

How Solargis is improving accuracy of solar power forecasts

Just as there are horses for courses, different forecasting techniques are more suitable depending on the intended forecast lead time.

How to calculate P90 (or other Pxx) PV energy yield estimates
Best practices

How to calculate P90 (or other Pxx) PV energy yield estimates

To assess the solar resource or energy yield potential of a site, we model the solar resource/energy yield using best available information and methods. The resulting estimate is the P50 estimate, or in other words, the “best estimate”. P50 is essentially a statistical level of confidence suggesting that we expect to exceed the predicted solar resource/energy yield 50% of the time. However, ...