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Australian State/Territory : QLD
Scheme : Discovery Projects
Australian State/Territory : VIC
Research Topic : STORAGE
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  • Funded Activity

    Discovery Projects - Grant ID: DP160103567

    Funder
    Australian Research Council
    Funding Amount
    $330,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP140100193

    Funder
    Australian Research Council
    Funding Amount
    $330,000.00
    Summary
    Understanding dissipation, thermal conduction and diffusion in superionic conductors using ab initio nonequilibrium molecular dynamics simulation. Lithium ion batteries are widely used in computers, cars and more recently in aircraft. However they may exhibit thermal runaway leading to fire. Recently these problems have grounded the fleet of Boeing 787 aircraft, worldwide. Understanding superionic conduction is of thus of considerable technological importance. The project will focus on understa .... Understanding dissipation, thermal conduction and diffusion in superionic conductors using ab initio nonequilibrium molecular dynamics simulation. Lithium ion batteries are widely used in computers, cars and more recently in aircraft. However they may exhibit thermal runaway leading to fire. Recently these problems have grounded the fleet of Boeing 787 aircraft, worldwide. Understanding superionic conduction is of thus of considerable technological importance. The project will focus on understanding mass and heat flow in superionic conductors using a new molecular simulation technique that the team has recently developed. This technique combines nonequilibrium statistical mechanics and ab initio molecular dynamics simulation. The project will learn how heat is generated and conducted through these materials and how temperature influences these processes, and how heat and mass flow couple together.
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    Funded Activity

    Discovery Projects - Grant ID: DP180101051

    Funder
    Australian Research Council
    Funding Amount
    $362,666.00
    Summary
    Smart micro learning with open education resources. This project aims to enhance personalised learning systems for mobile device users . Open online education is gaining in popularity with its ease of use. The project tackles the problems in relation to more and more popular mobile and ‘micro learning’, where people learn on the move and within small units of time. Ontology and machine learning technologies used in this project will help to optimise the offering of open education resources, by p .... Smart micro learning with open education resources. This project aims to enhance personalised learning systems for mobile device users . Open online education is gaining in popularity with its ease of use. The project tackles the problems in relation to more and more popular mobile and ‘micro learning’, where people learn on the move and within small units of time. Ontology and machine learning technologies used in this project will help to optimise the offering of open education resources, by providing solutions meeting each individual learner’s needs. The main outcome will consolidate a cloud based micro learning framework through integrating a group of novel algorithms.
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