Australia's clean energy transition depends on generating more renewable power. However as solar farms continue to expand across the country, advanced data-driven tools are becoming increasingly important to maximise their performance, reduce costs and improve reliability.
A recently launched project in the National Industry PhD Program is researching just this. The research will be conducted by PhD candidate Matteo Galli (pictured left) with academic support from Dr Giovanni Picotti (pictured right) from QUT (Queensland University of Technology), and the industry mentorship of Michael Hall from Sprint Digital.
The team brings together the commercial AI, data engineering and software development capabilities of Sprint Digital with the renewable energy research expertise of QUT (Queensland University of Technology) to investigate how digital twin technology can transform the management of photovoltaic assets. Together, the team will explore innovative approaches to monitoring degradation, predicting maintenance requirements, optimising panel cleaning schedules and improving battery dispatch decisions using real-time operational and environmental data. The goal is to deliver a commercially deployable decision-support platform that reduces solar farm operating costs, extends asset life and improves renewable energy reliability across the Australian grid.