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STORAGE OPTIMISATION

This theme cuts across the other four themes addressed by the Project. This theme encompasses monitoring, controlling, optimising and integrating into networks, energy storage technologies including batteries, fuel cells, power-to-gas and virtual storage, to fully realise their value.

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Advanced health monitoring and analysis methods for battery energy storage systems

The objective of this sub-theme is to investigate a new framework that integrates dynamic battery state estimation into charging/discharging algorithms to improve the charging efficiency, reliability and cycle life of batteries.

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The focus of the research will include:

  1. Modelling material properties and chemical processes via combined theoretical- experimental investigations;

  2. Developing effective and efficient on-line measurement to assist the estimation of time-varying parameters of the nonlinear battery models;

  3. Developing customer-tailored state-of-charge and remaining useful life estimation methods for batteries based on the dynamic models;

  4. Building a real-time RTDS-based hardware-in-the-loop test-bed for battery life cycle testing and model validation; and

  5. Developing adaptive charging algorithms for optimal scheduling, considering battery degradation and state estimation uncertainties.

Multi-scale analysis and networked control of energy storage systems

This sub-theme aims to unify communication and control theory into a single framework, enabling the development of wireless-communication-based control algorithms for operating distributed energy storage systems that account for the limited availability of underlying communication infrastructure.

The sub-theme consists of four objectives:

  1. analyse the impacts of wireless communication on the stability, performance and robustness of closed-loop control systems;

  2. derive stability conditions in terms of channel capacity, reliability and delay;

  3. develop a robust distributed control scheme that accounts for the properties of the developed wireless system; and

  4. unify theoretical analysis with real-world implementations and coordinate the design of cyber-physical architectures.

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Advanced operation and control methods for coordinating heterogenous energy storage devices

A variety of energy storage devices can be integrated with existing energy networks and complement each other to support an area. However, they are heterogeneous, owing to their differences in response times, control mechanics and charging/discharging efficiencies. Existing operation and control techniques may not be sufficient to accommodate their electrochemical/mechanical differences. In this sub-theme, advanced operation and control methods will be developed to coordinate different energy storage devices.

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The aims of this project are:

  1. Investigate the modelling of different energy storage devices;

  2. Develop appropriate distributed optimisation methods for operating heterogeneous energy storage devices; and

  3. Develop a multi-agent control method for coordinating diverse storage devices.

Optimal energy storage operation strategy considering demand changes

Existing energy storage operation strategies can be further extended to incorporate deep learning on demand forecasting and uncertainty to deliver an optimal operation strategy, as well as optimal energy system sizing recommendations based on customers’ demand profiles etc.

Corresponding key deliverables include:

  1. novel integrated energy storage technologies, building on different technologies and different mechanisms toward energy storage solutions with the most economic and efficient characteristics for grid-wide as well as distributed energy storage needs (grid, community, building, household and appliance level applications);

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2. methodologies and frameworks for integrating, optimising, and managing renewable generation and energy storage, including demonstrated application of the systems at three scales (appliances, end user/household, community/building), as well as their integration into overall energy systems;

3. a framework for economic valuation of energy storage solutions, as multi-purpose urban assets, for current and future economic contexts of the energy sector in Australia.

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Advanced monitoring and control of iron slurry and other flow battery systems

Existing methods of monitoring and control for flow batteries are limited to simple charging and discharging profiles. They are also based on oversimplified equivalent electrical circuit models and only work efficiently in limited state of charge ranges and only suitable with constant power supply (e.g. grid connections). In this subtheme, CIs, in consultation with the PO Fusion Power Systems, will develop a monitoring and control approach for iron slurry and other flow battery systems based on their mechanisms of electrochemical reactions. In addition, control of side reaction minimisation systems will be investigated.

This will include developments of an integrated approach to :

  • online monitoring of battery operation for real-time fault detection (e.g. state of charge, flow channel blockage, capacity loss monitoring and imbalance of electrolyte) and online fault detection techniques based on frequency response analysis and dynamic battery models;

  • optimal control of electrolyte flow rate, charging/discharging current and voltage, and the number of cells/stacks to be charged/discharged, using optimal control approaches (including model predictive control).

 

Expected advantages include:

  1. improved battery operation efficiency and safety (e.g. to avoid high concentration over-potential and H2 gassing);

  2. a wider state-of-charge (SOC) range; and

  3. greater flexibility in battery operation to allow optimal charging and discharging with time- varying charging/discharging power for integration with renewable power sources and power quality control.

Valuing storage in the national electricity market

The range of different energy storage technologies, including supercapacitors, batteries, thermal storage, virtual storage and electric vehicles, can provide flexibility over different timeframes. In this subtheme we aim to understand the impact and value of energy storage in a future National Electricity Market (NEM) with high penetration of renewable energy.
 

This will include:

  1. Developing open-source modelling frameworks and techniques to assess the impact and value of distributed and utility-scale storage with high penetration of renewable energy;

  2. Analysis of potential for distributed storage, load shifting and demand response and assessment of emerging impacts on market participants, including consumers, networks and system operators; and

  3. Using these models and analyses to explore appropriate market design and regulation for dispatchable storage technologies that facilitate renewables integration.

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