China’s Livoltek says it has developed 120 kW electric-vehicle chargers with 140 kW input and a 100 kWh LFP battery, supporting the CHAdeMO, GB/T, CCS1, and CCS2 standards.
The Hungarian company said its new products can handle a load of 300 kg. The modules are available with power outputs of 23.65 W and 59.68 W and can be integrated with wood-plastic composite, wood, stone, or ceramic floorings.
Scientists have developed a novel method that uses live video feed to detect shadows on solar panels. It uses computer vision techniques, such as gamma transform and histogram matching, resulting in performance that is reportedly better than conventional techniques, especially in large arrays.
The EU-funded Laperitivo project aims for 22% efficiency in 900 cm² opaque perovskite modules and 20% efficiency in semi-transparent ones. The project partners include imec, Fraunhofer ISE, TotalEnergies, and EDF.
By coating the iron sulfide cathodes in polymers, a research team was able to create transition-metal sulfide-based lithium batteries with stable cycling and high safety. After 300 cycles, a lithium carbide iron disulfide pouch cell retained 72.0% capacity with no capacity degradation after 100 cycles.
GE Vernova has developed a 2,000 V (DC) utility-scale inverter, to be used in a North American pilot operation starting in early 2025. The inverter offers up to 6.0 MVA of output power.
Researchers have measured the power loss of a 50 W panel stationed in a 30-meter wave tank. Based on ten different scenarios, they were able to draw an empirical equation for the prediction of power loss, with the highest loss being measured at 12.7%.
The Hungarian government says 20,000 households have signed up for its PV subsidies scheme, which offers up to HUF 5 million ($14,125) per home installation. The original HUF 75.8 billion budget was increased by HUF 30 billion in July.
German fluid management company Lutz-Jesco introduced a system aimed at supporting pumping and water disinfection in cases of blackouts. The hub is preconfigured to work with solar panels, a battery charge controller, an inverter, and cabling.
The novel method uses the YOLOv8 framework, integrating an attention mechanism and a transformer model. It was tested on a dataset of 4,500 electroluminescence images against several other models and its results were up to 17.2% more accurate.
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