Renewable energies represent a significant opportunity to meet the world's energy needs while maintaining a viable environment for generations to come. The future electricity grid will feature millions of intermittent and distributed generation sources, will support a significant penetration of electric vehicles, and will give greater incentives and control to consumers to optimise their energy usage. It will also require an unprecedented level of automation, to self-manage, self-reconfigure and self-heal. This vision challenges the human-controlled, top down management style of the current grid which relies on the existence of few, predictable and rapidly adjustable fossil fuel generators. It calls for a fundamental paradigm shift in the way power systems are planned and operated, underpinned by a new generation of communication, control, data analytics, and optimisation technologies.
The College of Engineering and Computer Sience at ANU is developing new technologies based on mathematical optimisation and artificial intelligence, to support the future of energy systems and the transition from today's power systems. Our group of 15 researchers and PhD students collaborates with Australian and overseas utilities, and with overseas research institutions such as Los Alamos National Research Laboratory.
- Demand management: we design and evaluate incentive mechanisms that encourage consumers to shift demand and reduce the network's peak load. We also develop optimisation software that help consumers to make optimal decisions about their energy consumption and reduce their bill.
- Microgrids: a vision of the future grid is as a network of carbon neutral communities called microgrids, which balance their own renewable generation, storage, and loads, and provide ancillary services to the grid. We are investigating the optimal design and operations of microgrids.
- Power systems planning and operations: we automate and optimise planning and operational decisions to enable the future grid to operate economically and reliably under the dynamic and unpredictable conditions arising with renewable energy.
- Resiliency and self-healing: we automate power system restoration following incidents ranging from minor outages to natural disasters. This reduces outage time, fines for utilities, and costs to society. Our research is used by the US Department of Homeland Security in hurricane response.