ABOUT

ABOUT

Solarisᴬᴵ Pty Ltd is a SaaS O&M system for solar farms and large-scale photovoltaic (PV) installations developed at UQ.

The O&M platforms use advanced algorithms to analyse customer data to maximize energy output by reducing faults, underperformance, soiling and preventing future maintenance. This SaaS-Artificial Intelligence (AI) based system minimizes O&M costs to site owners, plus helps maximize energy output to the power grid.

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 O&M system. The O&M platforms 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 O&M platforms 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.

INVESTORS

MEET THE TEAM

  • Associate Professor Rahul Sharma

    Senior UQ Consultant

  • Derek Stephens

    COO

  • Ajay Hemanth

    Manager AI & Data Analytics

  • Dr Gayan Lankeshwara

    Research Specialist