Aussie Solar Batteries has entered into a landmark research partnership with the University of New South Wales (UNSW) to develop next-generation, AI-enabled energy systems.
The collaboration centres on a major research and commercialisation project titled AI-Enabled Smart Energy Hub for Virtual Power Plant (VPP)
The project forms part of the federal government-funded Trailblazer for Recycling and Clean Energy (TRaCE) initiative, led by UNSW in partnership with the University of Newcastle and is designed to fast-track the commercial readiness of advanced clean-energy technologies.
Under the agreement, UNSW researchers from the School of Electrical Engineering and Telecommunications will work alongside Aussie Solar Batteries to design, develop and test AI- driven energy management platforms capable of optimising solar and battery systems across both residential and commercial environments.
The research will focus on forecasting, demand-side management, optimisation algorithms and digital-twin modelling to enable smarter coordination of distributed energy resources and more efficient virtual power plant deployment.
Aussie Solar Batteries CEO, Steven Yu, said the partnership represents a decisive step in bridging the gap between academic innovation and practical energy solutions.
“This collaboration allows us to take world-class research out of the lab and apply it directly in real homes and businesses,” Yu said.
“By combining UNSW’s AI and energy expertise with our large-scale deployment capability, we can accelerate smarter, more efficient solar and battery networks across Australia.”
The partnership is designed to ensure new technologies are tested under real operating conditions, improving grid stability, lowering costs and unlocking greater value from distributed energy assets.
Yu said smarter batteries and AI-driven energy systems are the future of the grid.
“There’s a significant gap between research and technology that actually works at scale,” Yu said.
“This project is about closing that gap and fast-tracking solutions that improve reliability, reduce energy costs and unlock the full potential of virtual power plants.”
The research project will run through to December 31, 2026.