Best practices

Watch the PVPMC webinar organized by Sandia where Branislav Schnierer, PV Modeling Specialist from Solargis talked about the technical aspects of self-shading analysis.

Solargis’ Technical Director, Tomas Cebecauer, and Managing Director, Marcel Suri speak about the core ingredients for a reliable database, Solargis’ ongoing efforts to enhance and validate its data services, and how users of Solargis’ data can most effectively undertake their own validation using on-site measurements.

Bad data in equals bad data out. This well-known phrase is very relevant in a context of technical design and energy simulation of photovoltaic (PV) power plants. Most solar companies understand this and are carefully evaluating uncertainty of solar resource data used for feasibility purposes ...

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, ...

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

In collaboration with our partners, GeoSUN Africa and Suntrace, we have recently installed a total of 10 solar measuring stations across Zambia and Maldives.

Accurate solar resource data is needed for planning, engineering and financing of a solar energy project.

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.

On Monday 23 Feb 2015 at 16:00 UTC, Marcel Suri (Solargis) and Tom Hoff (Clean Power Research) present the use of weather satellite data