Centre for Future Energy Networks
We carry out internationally-recognised research in the fields of energy and power networks and intelligent grid technologies towards the development of future electrical power grids.
Our research is reshaping electricity networks to fit the special conditions and challenges within Australia – that is, managing abundant energy sources for a relatively small population across large geographical areas.
One such example is the National Electricity Market (NEM) transmission path down the east coast of Australia which is the longest in the world.
We're also providing our talented students studying this field and industry partners with a deeper understanding of these ongoing obstacles.
Our research
We focus on a range of research initiatives orientated to an era of constrained-carbon systems. Our key areas are:
Grid operations and planning
The traditional highly-centralised grid structure is being questioned for its long-term suitability.
New ideas such as microgrids and smart grids are likely to change grids especially at distribution levels.
It must be secure, and interact with associated networks such as water, gas, transport and telecommunication.
We work on a range of problems related to future energy grids including the impact of renewables, demand response and energy storage, and their impact on grid stability.
Our work focuses on the physical power systems and ensuring secure system operations and promoting efficient system expansion planning in industrial practices.
We have extensive experience in areas such as:
- generic constraints for electricity market operations and planning,
- power system load modeling,
- power system Var control and prediction,
- power system forecasting and predictive control,
- fast simulation techniques for system dynamic analysis,
- electricity market simulation and system vulnerability, and
- stability assessment techniques.
Our experts: Professor David Hill, Associate Professor Jin Ma, Associate Professor Gregor Verbic
Our collaborators: University of Newcastle, University of Queensland, UNSW
Industry partners: Numerous industry and government stakeholders played an advisory role
We assisted the CSIRO in delivering the first analytical framework of its kind to systematically investigate the most economically efficient energy network (electricity and natural gas) configurations for Australia.
With this framework, Australia will be able to identify the lowest cost pathway to integrate significant amounts of large and small scale renewables into our grid with existing technologies while maintaining operational stability.
This will pave the way for significant emissions reductions in Australia’s most carbon intensive economic sector.
Advanced modelling and analytical techniques are now being developed to provide a suite of tools to expand our understanding of:
- the total costs of transmission and distribution systems for standard and alternative grid topologies
- the development and treatment of methods to deal with increasing renewable energy supply of 20% and beyond
- potential market failures in current system planning and operations in dealing with intermittent renewable generation
- the full benefit of demand side measures in reducing total system cost, i.e. the investment and operating costs of generation, storage, transmission and distribution assets
- potential policy and regulatory models that would help Australia implement the most optimal, technologically feasible outcome.
We will study scenarios out to 2050 driven by fuel prices, policy, market and grid planning paradigms.
Analytical techniques are being developed for grid performance assessment and optimal design in terms of reliability, cost and carbon emission limits.
Our expert: Associate Professor Jin Ma
Supported by the University of Sydney Bridging Funding, this project will develop load modelling theories applicable to versatile loads with high modelling accuracy.
Based on these new models, we will investigate the stability of an electricity network when the loads are more actively involved in system controls such as in demand-response schemes.
Distributed control
Work on distributed control was started with our participation in the Australian government’s Smart Grid Smart City (SGSC) project.
This led to the view that smarter grids go beyond providing enhanced data from the grid; there should be more capability to operate and control the whole system in a distributed way with new structures, which would allow new technologies like demand-side control and control using energy storage.
To achieve the required performance from any future grid, the control system will need to take account of diverse data; process this data in a timely and distributed manner; optimise across different voltage levels; and send appropriate control instructions for the optimum operation of all system components.
The fundamental building blocks for advanced smart grids are well established in our centre research, namely power networks and markets, telecommunications, data mining and learning, constrained optimisation, and distributed control.
The research work is exploring demand response mechanisms, scaling solutions, reducing peak demand, enhancing reliability and then enabling new capabilities for future grids, particularly substantially decreasing levels of carbon emissions.
Our experts: Associate Professor Gregor Verbic
Our collaborators: Australian National University, University of Tasmania
Industry partners: Reposit Power and TasNetworks
CONSORT is a multi-disciplinary collaborative project that will develop an innovative automated control platform and new payment structures.
It will enable consumers with PV-battery systems to provide support services to a constrained electricity network.
These new capabilities will be demonstrated during peak load events on Bruny Island, Tasmania, to relieve the undersea cable supplying the island and reduce the need for expensive diesel generators.
Our experts: Professor David Hill, Associate Professor Jin Ma
Our collaborators: University of Hong Kong, Imperial College London
This proposal addresses the sustainability of electrical power delivery systems.
The traditional paradigm of generation following demand, where millions of diverse customer actions are balanced with the controlled output of a small number of major generation plants, cannot handle the distributed and variable nature of solar and wind energy sources.
We're exploring a new paradigm, which is adaptive in the sense of demand following generation.
The load devices contribute to overall balancing and welfare of the system in processes of demand response and load control.
Thus future smart loads, using advanced power electronics, and the control and communication systems must themselves be adaptive to the dynamically changing power generation and circumstances.
The four research teams will be led by internationally renowned experts in the key areas:
- power systems,
- power electronics,
- computer networking and
- control technology.
The investigators will add special skills for particular projects.
By integrating these areas in a balanced way, the aim is to build a unique research capability which can support the future industry in the Pearl River Region and beyond.
The team will build on several of its own highly innovative ideas that have shown promise for the proposed research, namely (i) electric springs, (ii) granular modelling and control and (iii) adaptive networking (integrated with communication, control and security).
Grid integration
Our grid integration all aim to facilitate the greater penetration of new technologies such as distributed generation, large-scale renewable power, energy storage and electronic vehicles.
Many projects involve novel designs for power electronic converters. A theme is how to ensure distributed generation and demand response can also participate in system services.
Projects with vendors, including ABB for solar energy management systems, have begun or are being set up. This work informs the modeling needed for the planning and smart grids research.
Our experts: Professor David Hill, Associate Professor Jin Ma, Associate Professor Gregor Verbic
We aim to establish an essential part of infrastructure required for experimental research in the area of distributed resources under smart grid.
The innovative theoretical methodologies being developed under existing or completed competitive research projects in this area will be validated through experimental research.
The proposed experimental platform will also help to resolve technical issues related to future power supply systems including
- real-time data from smart meters,
- application of vehicle to grid systems,
- demand management,
- control, and
- protection aspects under uncertain nature of renewable energy sources.
This will bring together the researchers in this area to utilise the facility for collaborative research.
Our experts: Professor David Hill
Energy systems are undergoing unprecedented transformations with the incorporation of renewable energy sources, advanced transmission facilities, and emerging power-to-gas technologies.
All these changes, while potentially making energy system more responsive, efficient and resilient, also pose significant implementation challenges.
We aim to resolve key technical barriers to facilitate the deployment of clean energy highway, enabling operations across interdependent domains to ensure more sustainable solutions for energy generation, delivery, and utilisation in this new energy era.
The outcome will include a sound and robust suite of models and associated methodologies for study, analysis, and design of the clean energy highway.
Our experts: Professor Jianguo Zhu, Dr Sinan Li,
The initiation of MagNet Engine to advance scholarly research and design practices in power magnetics.
MagNet Engine offers a software suite incorporating cutting-edge models that predict the magnetic properties of various soft materials with better performance than traditional curve-fitting models, such as the Steinmetz equation.
MagNet Engine is a transparent, accessible, flexible, and continuously evolving power magnetics design tool, providing:
- use of multiple cutting-edge core loss model,
- customized magnetic working conditions,
- hysteresis (B-H) loop visualization,
- core loss density prediction, and
- exporting hysteresis data.
Its user-friendly design, coupled with advanced modelling and visualization capabilities, makes it an invaluable resource for anyone involved in the study or application of power electronics.