Stability Analysis of Power System with Massive Power Electronic Devices. The decarbonization of Australia's power systems is to integrate massive renewable energy sources which are interfaced with many power electronic devices (PEDs). The fast and complex dynamics of PEDs have significantly changed the nature of the power system, which limits the applicability of existing tools and methods to assess its stability. The goal of this project is to gain a comprehensive insight into the stability of ....Stability Analysis of Power System with Massive Power Electronic Devices. The decarbonization of Australia's power systems is to integrate massive renewable energy sources which are interfaced with many power electronic devices (PEDs). The fast and complex dynamics of PEDs have significantly changed the nature of the power system, which limits the applicability of existing tools and methods to assess its stability. The goal of this project is to gain a comprehensive insight into the stability of a futuristic power system with high penetration of PEDs. The intended outcomes will be a model and data jointly driven methodology for high-efficient and real-time stability assessment. The methodology developed in this project will support Australia's transition to a stable, secure, and low-carbon power grid.Read moreRead less
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.Read moreRead less
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.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100059
Funder
Australian Research Council
Funding Amount
$445,007.00
Summary
Robust Renewables Hosting Capacity Enhancement for Distribution Networks. This project aims to quantify technical margins and devise novel robust renewables hosting capacity enhancement methods for active distribution networks. High renewables penetration has impaired power quality and network operational reliability, thus reducing renewables utilisation rate and impeding further installation. The intended outcomes are innovative data-driven robustness design methods against complex and uncertai ....Robust Renewables Hosting Capacity Enhancement for Distribution Networks. This project aims to quantify technical margins and devise novel robust renewables hosting capacity enhancement methods for active distribution networks. High renewables penetration has impaired power quality and network operational reliability, thus reducing renewables utilisation rate and impeding further installation. The intended outcomes are innovative data-driven robustness design methods against complex and uncertain operating conditions, which are able to secure increasing renewables penetration and installation. With emerging community battery and hydrogen electrolyser, a suite of operation and planning methods will be developed, allowing utility operators and government agencies to expedite zero-emission energy transition.Read moreRead less
A Next Generation Smart Solid-State Transformer for Power Grid Applications. The research aims to design, develop and implement a next generation, compact and light-weight, smart solid-state transformer with a newly developed high-frequency magnetic link and power converters that will provide a better and faster voltage transformation and regulation and support the power grids. The proposed research will revolutionize the power grids by replacing the traditional transformer with a new device mad ....A Next Generation Smart Solid-State Transformer for Power Grid Applications. The research aims to design, develop and implement a next generation, compact and light-weight, smart solid-state transformer with a newly developed high-frequency magnetic link and power converters that will provide a better and faster voltage transformation and regulation and support the power grids. The proposed research will revolutionize the power grids by replacing the traditional transformer with a new device made of solid-state power modules that will have multi-feature and multi-function ability and control facilities. The technology developed in this research will help make energy networks more efficient, smart, reliable and flexible, having direct benefits to renewable energy growth, with long-term impact on national economy.Read moreRead less
Compact reliable fault-tolerant modular high power converters. Compact reliable fault-tolerant modular high power converters. This project aims to deliver new and advanced converter hardware and control designs with drastically smaller reactive components that are cheaper to convert, more reliable and compact. Voltage and current-sourced modular multilevel converters have delivered the required voltage/current/power ratings for utility applications such as static compensators and high-voltage di ....Compact reliable fault-tolerant modular high power converters. Compact reliable fault-tolerant modular high power converters. This project aims to deliver new and advanced converter hardware and control designs with drastically smaller reactive components that are cheaper to convert, more reliable and compact. Voltage and current-sourced modular multilevel converters have delivered the required voltage/current/power ratings for utility applications such as static compensators and high-voltage direct current transmission. However, these energy storage components, including embedded batteries, are overwhelmingly large. Anticipated outcomes are that compact, cheaper and even more efficient power electronic energy converters will enable much needed sustainable energy grids; reduce the cost of integrating renewable energy generation in the grid and achieve even more efficient electronic control of electric systems.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100056
Funder
Australian Research Council
Funding Amount
$410,154.00
Summary
Accurate Fault Location Methods for Complex Power Networks. This project aims to devise novel algorithms to tackle one of the longstanding and challenging problems in power networks; finding the fault location in power lines. Recent bushfire preventive technologies that have been installed in power networks make the fault location process extremely challenging and time-consuming, leaving communities without power for many hours in extreme heatwave conditions.
The intended outcomes of the projec ....Accurate Fault Location Methods for Complex Power Networks. This project aims to devise novel algorithms to tackle one of the longstanding and challenging problems in power networks; finding the fault location in power lines. Recent bushfire preventive technologies that have been installed in power networks make the fault location process extremely challenging and time-consuming, leaving communities without power for many hours in extreme heatwave conditions.
The intended outcomes of the project are innovative algorithms that are able to pinpoint the fault location more accurately in complex networks, with many fewer measurement devices than conventional methods. This is expected to provide significant benefits for public safety and power supply reliability.Read moreRead less
Dynamics and Resilience of Complex Network Systems with Switching Topology . This project aims to develop a breakthrough methodology and new technology to analyse and integrate large-scale network systems, such as power grids, that involve large networks of components with switching connections. The project expects to create a new theoretical framework to tackle the challenges arising from switching topology resulted from switching connections, and methods to understand their behaviours and desi ....Dynamics and Resilience of Complex Network Systems with Switching Topology . This project aims to develop a breakthrough methodology and new technology to analyse and integrate large-scale network systems, such as power grids, that involve large networks of components with switching connections. The project expects to create a new theoretical framework to tackle the challenges arising from switching topology resulted from switching connections, and methods to understand their behaviours and design intervention strategies to achieve optimal outcomes. The expected outcome is a practical technology for industry applications, such as smart power grids. This should increase the reliability and resilience of the electricity networks against faults and cyber attacks.
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Quantification, optimisation, and application of deep uncertainty. This project aims to develop a framework for deep uncertainty quantification. There is currently a fundamental gap between deep learning research and the methods required to quantify and manage uncertainties. The research will propose a novel distribution-free methodology to generate deep predictive uncertainty estimates to avoid the assumptions of existing methods. The quality of estimates will be enhanced by applying an interva ....Quantification, optimisation, and application of deep uncertainty. This project aims to develop a framework for deep uncertainty quantification. There is currently a fundamental gap between deep learning research and the methods required to quantify and manage uncertainties. The research will propose a novel distribution-free methodology to generate deep predictive uncertainty estimates to avoid the assumptions of existing methods. The quality of estimates will be enhanced by applying an interval-based adversarial training step. The project is expected to help data-driven Australian organisations and industries to better quantify and manage forecasting uncertainties. This project will provide them with significant cost savings through better decision making and more robust planning.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100274
Funder
Australian Research Council
Funding Amount
$415,675.00
Summary
Graph Neural Networks for Efficient Decision-making towards Future Grids. This project aims to develop a breakthrough framework for decision-focused learning by integrating explainable graph neural networks and efficient computational methods. It expects to create new methodologies of graph representation learning for unlocking data insight with spatiotemporal knowledge while to build new accelerated optimisation theories for speeding up decision-focused learning model. The expected outcomes wil ....Graph Neural Networks for Efficient Decision-making towards Future Grids. This project aims to develop a breakthrough framework for decision-focused learning by integrating explainable graph neural networks and efficient computational methods. It expects to create new methodologies of graph representation learning for unlocking data insight with spatiotemporal knowledge while to build new accelerated optimisation theories for speeding up decision-focused learning model. The expected outcomes will advance big spatiotemporal data analytics and nonlinear optimisation theory for solving decision-making tasks towards a future energy system. This should promote the Australian power industry transition to a sustainable future grid based on a digitalisation approach to efficient energy management against climate changes.Read moreRead less