With power ranging from 2-6 kW in the seven-device series, the Sun2000-2-6KTL-L1 string inverters offer efficiencies of 98.2-98.4%. The 12kg products measure 365x365x156mm and feature two maximum power point tracking channels.

Chinese industrial conglomerate and string inverter maker Huawei used a virtual show to launch its Sun2000-2-6KTL-L1 residential single-phase inverter series. The new products feature artificial intelligence, enabling them to “continue self-learning from the database of millions of arcs’ features,” stated the manufacturer.

Huawei said the seven products each measure 365x365x156mm, weigh 12kg and offer two maximum power point tracking (MPPT) channels. MTTP voltage ranges from 90-560 V for the products and the maximum input current for MPPT is 12.5 A.

With power ranging from 2 to 6 kW, the inverter efficiencies are 98.2-98.4%, for a European-rated efficiency of 96.7% and 97.8%. Maximum input voltage for all devices is 600 V.

Parameters

The series is said to operate at altitudes lower than 4,000 meters and temperatures of between -25 and 60 degrees Celsius. “Equipped with AI [artificial intelligence] technologies, our AFCI [arc fault circuit interruption] feature could continue self-learning from the database of millions of arcs’ features and provides ultimate safety,” Huawei said. “In addition, with new Pinpoint Arc Fault Positioning, now, arcing troubleshooting time can be reduced by 80%.”

The inverters are said to be compatible with the Huawei Smart ESS Battery 5 kWh – 30kWh product and LG Chem’s RESU 7H_R/10H_R residential storage system, as well as with Huawei’s new Sun2000-450W-P power optimizer, which was also launched during the virtual show.

Huawei recently unveiled a technology roadmap explaining how it intends to integrate artificial intelligence in its inverters. The manufacturer said its string inverters will be improved for high-precision, real-time data collection with real-time control of string-level energy yield optimization, DC arc detection and response to grid-tied control – including real-time inference, execution and self-closed-loop control capabilities.