ABOUT

UQ’s Associate Professor Rahul Sharma, School of Electrical Engineering & Computer Science (EECS), has led the technology development and spin-out of the Solarisᴬᴵ SaaS platform. The back-end O&M functions are based on the physics associated with solar PV cells, their current-voltage characteristics and experimental observations. The technology is designed around the relationship of string current levels w/fault types, fault location, number of panels per string and the panel types. It creates base and progression performance distribution mappings to foresee where maintenance work needs to be prioritized to minimize system unavailability times. The back-end O&M functions use advanced algorithms to help reduce the number of losses in grid-connected PV systems. The system can be used at sites without additional hardware by monitoring groups of PV panels at the array level. The system monitors fault detection, equipment underperformance, PV soiling levels and performs predictive maintenance using AI.