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Research Topic : Microarray analysis
Australian State/Territory : VIC
Socio-Economic Objective : Energy Systems Analysis
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  • Funded Activity

    Discovery Projects - Grant ID: DP130100156

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Congestion control of networks: a unified stochastic framework. Systems such as the internet, wireless networks and the power grid require efficient allocation of shared resources. This research will develop ways to reduce delays in the internet and allow for growth in the power grid, without requiring additional infrastructure.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP180101309

    Funder
    Australian Research Council
    Funding Amount
    $321,000.00
    Summary
    Dynamic Deep Learning for Electricity Demand Forecasting. This project aims at developing a deep learning technology for high resolution electricity demand forecasting and residential demand response modelling. Electricity consumption data are dynamic and highly uncertain. The deep learning technology expects to provide accurate demand forecasting, and thus enabling optimal use of existing grid assets and guiding future investments. The expected outcome can support data-driven decision-making in .... Dynamic Deep Learning for Electricity Demand Forecasting. This project aims at developing a deep learning technology for high resolution electricity demand forecasting and residential demand response modelling. Electricity consumption data are dynamic and highly uncertain. The deep learning technology expects to provide accurate demand forecasting, and thus enabling optimal use of existing grid assets and guiding future investments. The expected outcome can support data-driven decision-making in Australia's electricity distribution network planning and operation by considering future challenges such as integrating battery storage and electric vehicles into the grid, and thus providing reliable energy. The project expects to train next generation expert workforce for Australia's future power grid.
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    Funded Activity

    Discovery Projects - Grant ID: DP140100544

    Funder
    Australian Research Council
    Funding Amount
    $331,000.00
    Summary
    Exploring Emerging Collective Behaviours in Large-Scale Data-Driven Networked Systems. Understanding emerging collective behaviours in large-scale data-driven networked systems and developing methodology and approach for pattern identification and intervention are very important for high impact applications such as smart energy supply using smart meters. This project will propose a new theory for the developments, which will enhance Australia's leading position in this research and provide a cut .... Exploring Emerging Collective Behaviours in Large-Scale Data-Driven Networked Systems. Understanding emerging collective behaviours in large-scale data-driven networked systems and developing methodology and approach for pattern identification and intervention are very important for high impact applications such as smart energy supply using smart meters. This project will propose a new theory for the developments, which will enhance Australia's leading position in this research and provide a cutting-edge technology for industrial applications and training of the next generation of leading researchers.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200101414

    Funder
    Australian Research Council
    Funding Amount
    $393,000.00
    Summary
    Loss-based Bayesian Prediction. This project proposes a new paradigm for prediction. Using state-of-the-art computational methods, the project aims to produce accurate, fit for purpose, predictions which, by design, reduce the loss incurred when the prediction is inaccurate. Theoretical validation of the new predictive method, without reliance on knowledge of the correct statistical model, is an expected outcome, as is an extensive numerical assessment of its performance in empirical settings. T .... Loss-based Bayesian Prediction. This project proposes a new paradigm for prediction. Using state-of-the-art computational methods, the project aims to produce accurate, fit for purpose, predictions which, by design, reduce the loss incurred when the prediction is inaccurate. Theoretical validation of the new predictive method, without reliance on knowledge of the correct statistical model, is an expected outcome, as is an extensive numerical assessment of its performance in empirical settings. The new paradigm should produce significant benefits for all fields in which the consequences of predictive inaccuracy are severe. Problems that lead to substantial economic, financial or environmental loss if predictions are incorrect will be given particular attention.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP200100056

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Transforming Microgrid to Virtual Power Plant –ICT Frameworks,Tools,Control. The project aims to enhance large scale renewable penetrations to national power grid by advancing control, optimization, and ancillary services of Virtual Power Plants (VPPs), considering different disruptive events including recent South Australian blackout. This project expects to create new control, frame communication architecture, develop plug and play type IoT enabled grid interfacing inverter, and optimize resou .... Transforming Microgrid to Virtual Power Plant –ICT Frameworks,Tools,Control. The project aims to enhance large scale renewable penetrations to national power grid by advancing control, optimization, and ancillary services of Virtual Power Plants (VPPs), considering different disruptive events including recent South Australian blackout. This project expects to create new control, frame communication architecture, develop plug and play type IoT enabled grid interfacing inverter, and optimize resource management for distributed VPPs. The anticipated benefits from this institutional level collaborations are that VPPs help in enhancing national power grid operations during normal and disruptive conditions when more renewables are connected and also secure benefits of consumers, prosumers, and grid operators.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP180103217

    Funder
    Australian Research Council
    Funding Amount
    $402,934.00
    Summary
    Power system security assessment given massive intermittent energy sources. This project aims to develop new models and analysis methods to investigate the impact of massive intermittent energy sources (IESs) on the performance and security of power grids. Furthermore, advanced control strategies will be developed to enhance the security. The outcomes can provide useful guidelines to assist the Australian power industry and the government in realising the renewable energy target. Furthermore con .... Power system security assessment given massive intermittent energy sources. This project aims to develop new models and analysis methods to investigate the impact of massive intermittent energy sources (IESs) on the performance and security of power grids. Furthermore, advanced control strategies will be developed to enhance the security. The outcomes can provide useful guidelines to assist the Australian power industry and the government in realising the renewable energy target. Furthermore considering serious blackout can not only cause economic losses, but also larger disturbance in other critical infrastructure, this project also contributes to national security.
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