The Vitocal 250-A Pro boasts a flow temperature of up to 70 C, a heating output of up to 39.5 kW and a cooling output of up to 21.7 kW and according to the German manufacturer, it is one of the quietest of its kind on the market. Its coefficient of performance is 5.6.
A research team in China has developed a novel thin-silicon wafer reinforced ring (TSRR) to protect ultra-thin wafers and solar cells during production. This technique consists of applying the ring at the edge of thin wafers and is compatible with all silicon solar module technology.
Sticky Solar Power is taking orders for industrial-scale versions of its novel room-temperature cell interconnection system, which is reportedly well-suited for back-contact (xBC), perovskite, and heterojunction cell technologies.
California startup Planted Solar uses construction robots and high-density arrays to deliver what the company says are higher energy outputs and lower balance of system costs.
Portuguese and Italian researchers have shown that the levelized cost of hydrogen (LCOH) is lower onshore and that PV-wind configurations reduce the LCOH up to 70%, while Lhyfe says it has started collaborating on a hydrogen storage project.
Canon has announced a new functional material for perovskite thin film passivation that potentially improves durability of perovskite solar cells while enabling a mass-production process. The Japanese company aims to start commercial production of the material in 2025.
Swedish solar developer Alight has obtained a grid connection for its 100 MW solar project in Eurajoki, western Finland. Construction is expected to start later this year.
Scientists in the UK developed a controller for B2B trading platform that considers thermal and visual comfort. Their modeling shows that participating in local energy trading increases the robustness of the control systems in residential microgrids in face of uncertainty in the occupant comfort level.
Scientists in Spain have developed thermal image mapping on dense and high-resolution point clouds representing status and geometry of PV modules and automatic identification of individual solar panels in 3D space. The proposed methodology was found to provide “exceptionally high” accuracy.
Fraunhofer ISE researchers are applying deep learning and digital twin modelling tools to optimize PV tracker control systems for use in farming and biodiversity projects. The goal is to be able to automatically position the modules throughout the day to meet the needs of the plants growing below, in light of the microclimatic conditions, and the need to optimize yield.
This website uses cookies to anonymously count visitor numbers. View our privacy policy.
The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.