Networked control for distributed renewable energy systems integration. The project aims to develop novel networked and coordinated control methods that greatly increase the capacity of the existing Australian power networks to host growing amounts of roof-top photovoltaic (PV) generation and customer load. These methods reduce the current need for high levels of continuing capital investments by optimally managing the existing network assets to fully exploit the inherent capabilities of PV inve ....Networked control for distributed renewable energy systems integration. The project aims to develop novel networked and coordinated control methods that greatly increase the capacity of the existing Australian power networks to host growing amounts of roof-top photovoltaic (PV) generation and customer load. These methods reduce the current need for high levels of continuing capital investments by optimally managing the existing network assets to fully exploit the inherent capabilities of PV inverters and new distributed battery storages that are now appearing at the domestic and network level. The project plans to combine robust networked control with stochastic optimisation methods to extract the best value from existing and new assets, while improving the load and generation hosting capability, for a given level of reliability.Read moreRead less
Machine learning techniques for fuel loss detection at service stations. This project aims to develop effective techniques to identify the sources of fuel losses, such as leaks and calibration errors in underground storage tanks at service stations. Monitoring fuel losses at service stations is influenced by many external factors which can be difficult to predict. The project expects to use machine learning to develop the techniques and test them with live data at service stations. The expected ....Machine learning techniques for fuel loss detection at service stations. This project aims to develop effective techniques to identify the sources of fuel losses, such as leaks and calibration errors in underground storage tanks at service stations. Monitoring fuel losses at service stations is influenced by many external factors which can be difficult to predict. The project expects to use machine learning to develop the techniques and test them with live data at service stations. The expected outcomes are a set of tailor-made machine learning techniques for effective fuel loss detection and a software suite that can be easily incorporated into the normal operation of service stations. This should reduce the costs to the petroleum industry from wasteful leaks and the environmental damage caused by these leaks. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100445
Funder
Australian Research Council
Funding Amount
$408,000.00
Summary
Engineering triple-phase boundary for superior aqueous metal-air batteries. This project aims to advance development of high-performance rechargeable aqueous zinc-air (Zn-air) batteries by engineering the triple-phase boundary to increase battery efficiency and power density for practical applications. There is an urgent need to develop sustainable and efficient energy storage and conversion systems to underpin technological development with increasing demand for superior battery technologies fo ....Engineering triple-phase boundary for superior aqueous metal-air batteries. This project aims to advance development of high-performance rechargeable aqueous zinc-air (Zn-air) batteries by engineering the triple-phase boundary to increase battery efficiency and power density for practical applications. There is an urgent need to develop sustainable and efficient energy storage and conversion systems to underpin technological development with increasing demand for superior battery technologies for portable electronics, renewable power sources and electrified vehicles. This project expects to accelerate the commercialisation of rechargeable aqueous Zn-air batteries and progress global commitments to new clean energy sources and storage technologies that are efficient, cost-effective and reliable.Read moreRead less