A University of Exeter team has tested single-axis tracking systems for floating solar across 12 UK sites, finding azimuthal tracking delivers the largest energy gains and lowest levelized cost of energy (LCOE).
In a new weekly update for pv magazine, Solcast, a DNV company, reports that early 2026 will bring mixed solar conditions globally, with strong prospects in eastern Australia and eastern China, but cloudier-than-normal outlooks for much of Europe, Asia, and parts of the US early in the year.
Scientists have developed a floating PV digital twin system, trained on data from 155 physical experiments, using a two-tier artificial neural network (ANN) with a high-fidelity model and a reduced-order model. Predictive performance reached R2 values of 0.9996 for PV surface temperature and 0.9189 for power output.
Research commissioned by the UK government finds rooftop solar panels can significantly influence fire behavior, particularly when the height gap between modules and the roof surface falls below critical limits.
UK-based GlobalData says Taiwan is on course to more than double its current solar capacity by the end of 2035.
A US solar industry group has outlined a nine-point policy agenda calling on New York City’s incoming mayor to accelerate rooftop solar and battery deployment to address grid reliability risks, energy costs and climate targets.
London-based consultancy GlobalData says Poland could add between 3 GW and 4 GW of solar annually through to the middle of the next decade.
The levelized cost of building a solar project in New York far exceeds the expected revenue from selling solar power, says a NYPA plan, with project success potentially depending on the sale of renewable energy credits at a satisfactory price.
Solar plus storage can also offer winter reliability improvements and limit gas consumption, finds a report from Synapse Energy Economics and the Solar Energy Industries Association.
A team of Sweden-based researchers has developed a snow loss model to estimate snow-induced PV power losses on an hourly basis. The proposed approach relies solely on data from remote sensing sources, such as aerial imagery, LIDAR, and satellite data.
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