Best practices

As solar farms become increasingly complex, de-risking bifacial projects by reducing the uncertainty around albedo will be crucial. We sat down with Vicente Lara-Fanego
PhD, Weather and Solar Modelling Expert, and Harsh Goenka, Business Development Manager, to discuss Solargis’ new two-part report on this little understood data source

Ten years ago, an average solar PV project was a relatively simple affair, comprising 10MW of fixed, monofacial modules. The market has moved on a long way since then. Now, typical solar farms approach 100MW in size and may use a range of technologies such as bifacial, intelligent tracking and floating modules, creating new possibilities for more efficient energy production.

Solar power’s star is rising resolutely, as lower costs of production open up new markets around the world and solar projects scale up, rapidly. In the last two decades, the size of solar installations has increased dramatically, and we are witnessing the rise of ‘megaprojects’.

Branislav Schnierer, PV Modeling Expert at Solargis, discusses the most common problems and best practices for taking and quality-controlling ground measurements. Webinar was recorded for PVPMC 2020 event in China.

Satellite maps are a basic tool for decision makers, planners and developers of photovoltaic (PV) power plants. They are essential for site-selection, land evaluation and understanding the local topography. They play an indispensable role, especially for the evaluation of sites in unknown territories and in peculiar climate zones.

Global Photovoltaic Power Potential by Country is an innovative new study developed by Solargis for the World Bank. The study aims to assess the potential for solar PV in every country, capitalising on several new, market-first, metrics and techniques.

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, ...

The process of estimating solar radiation data uncertainty can be sometimes unclear. We've tried to summarise in 4 simple steps.

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