Researchers in the Netherlands developed a model to identify tolerable degradation rates of the top cell in perovskite-silicon tandem modules. Simulations showed that an increase in tandem module efficiency from 28.0% to 32.9% could raise the tolerable degradation rate by approximately 50%.
An international study finds that successful agrivoltaic projects require farm-specific, holistic co-design that integrates PV layout with agricultural mechanization from the earliest planning stages. Without proper alignment between machinery, crops, and PV systems, agrivoltaics risk major land loss, lower field efficiency, and higher operating costs, undermining farm profitability.
In a new weekly update for pv magazine, OPIS, a Dow Jones company, provides a quick look at the main price trends in the global PV industry.
Brookfield has appointed Santander and Barclays to manage the sale of X-Elio, valued at more than €4 billion ($4.7 billion) including debt. If completed, it would be the company’s second major divestment in Spain in two years.
The multi-project cluster includes the world’s largest single-site electrochemical energy storage facility: the 4 GWh Envision Jingyi Chagan Hada Energy Storage Power Station.
Swiss startup Sun-Ways is testing removable solar panels installed on an operational railway line through a pilot project with French railway operator SNCF in Switzerland.
Xilia Group has introduced composite frames for solar modules made from glass fiber–reinforced polyurethane. The company says the frames reduce weight, resist corrosion, and eliminate the need for grounding.
German researchers have developed a sodium-ion battery technology using lignin-based hard carbon as the negative electrode. The 1 Ah battery cell prototype showed no significant degradation after 100 charging and discharging cycles.
German inverter and battery manufacturer SMA Solar Technology AG has unveiled a modular lithium iron phosphate battery system for commercial and industrial applications, with capacities ranging from 89 kWh to 197 kWh and integrated cybersecurity features.
South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring irradiance sensors during operation, using routine meteorological data instead. The model reportedly showed strong out-of-sample performance while outperforming conventional irradiance-based approaches, particularly under noisy or inconsistent data conditions.
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