BNZ, a Barcelona-based independent power producer (IPP), has announced a 49 MW solar project in northern Portugal in partnership with GRS, a Madrid-based solar engineering, procurement and construction (EPC) contractor.
German PV project developer Fellensiek Projektmanagement GmbH & Co. KG has filed for insolvency due to claims from an unnamed investor. However, the company’s 20 project entities remain unaffected, and buyers are being sought for their sale.
Finland’s Wartsila Energy has released a new turnkey battery energy storage system (BESS) with new fire-safety features.
Oxford PV is delivering its first commercial perovskite solar modules to US customers. The 72-cell solar modules have an efficiency of 24.5% and, according to the company, can generate up to 20% more energy than conventional silicon modules.
Sweden-based Innoventum has launched a solar carport line equipped with bifacial modules in a larch wood structure. The solution may include electric vehicle charging, energy storage, LED lighting, and inverter systems.
Two “ethical” hackers from the Dutch Institute of Vulnerability Disclosure (DIVD) have identified six vulnerabilities in Enphase IQ Gateway devices. The researchers are now working with the US inverter manufacturer to address the bugs in the next version of the product.
Renewables developer Q Energy has closed €50.4 million ($55.7 million) in financing for a 74.3 MW floating solar plant in northeastern France. Construction is already underway, with commissioning planned for the first quarter of next year.
Sweden’s Enerpoly has ambitious plans to make its 6,500m2 plant the center of global and European zinc-ion battery innovation. It is aiming for final capacity of 100 MWh annually by 2026.
Rabot Charge, a German renewable energy supplier, says the average spot electricity price in August rose slightly from July to €0.082 ($0.09)/kWh. The increase was due to a slightly below-average share of renewable sources in grid electricity.
Conceived by French scientists, the novel system uses ensemble learning and does not require anything more than a commercially available optimizer. Before it makes a decision, the method combines K nearest neighbors, support vector machine, and decision tree learning. Accuracy is reportedly up to 89%.
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