Data, tools and energy modelling

Data sets to use with energy modelling

To plan for future energy needs, we need two things: an accurate model, and relevant data sets. We are developing a true-to-physics model of the entire energy system in Australia (see our Systems Science Toolbox below), and gathering, curating and cleaning Australian energy system data sets that can be used with the model to answer any number of questions.

The Systems Science Toolbox

Wrangle less, model more

The Systems Science Toolbox provides curated, clean datasets and transparent models, streamlining your path to analysis. You can model the whole energy system including electricity, gas, liquid fuels and heat, and interconnected systems such as water and transport, or just select relevant datasets to use in your work. With seamless integration into your existing workflows to reduce setup time, you can focus on what really matters: delivering high-impact insights to drive real change.

What makes the Systems Science Toolbox different

• The ability to combine real customer insights from our Living Lab with other system datasets, to understand how the preferences of everyday energy users affect the energy system. 
• The ability to ‘zoom out’ your view to the whole of Australia, or ‘zoom in’ as tight as a suburb or precinct
• The modelling framework is founded on physical realities (conservation of mass and energy, engineering performance, etc), unlike economics-based approaches. It can show whether a scenario will actually work, be resilient, and function in a future climate, for example.
• Users can get under the hood, explore sensitivities, and understand the drivers behind a scenario result, rather than just receiving a report with the outcomes.

Using Model-Based Systems Engineering to analyse the whole energy system

NEAC is founded on Model-Based Systems Engineering principles and techniques. We have created a tool to model and analyse Australia’s energy system as a whole, including related systems such as water and transport, and imports and exports. The multi-energy system model can help to answer questions with cross-sectoral interdependencies. 

For example, it can answer these questions:

1. Energy system resilience and emergency preparedness

• How can sustainable energy infrastructure, including community solar and battery programs, enhance resilience to extreme weather events and other emergency situations?
• What impact would an emergency shutdown of a gas processing plant have on downstream electricity production, hydrogen production, and household heating?

2. Infrastructure evolution

• How can Australia’s electricity infrastructure and markets evolve to accommodate new demands from electric vehicles and billions of distributed energy resources?
• If Australia adopted nuclear power, what impact would a nuclear power plant have on the network and local water resources?

3. Industrial sector and cross-sectoral impacts

• How can industrial hubs optimise heat use and maintain energy reliability amid disruptions in gas processing or other critical infrastructure?

4. Resource constraints and supply chain vulnerabilities

•  How is the transition to sustainable energy constrained by the availability of critical minerals and manufacturing capacity?
• If a large hydrogen project were to commence operation, how would that impact water supplies and the electricity network?

5. Social equity

• How can Australia ensure that the energy transition produces equitable outcomes across diverse communities, including managing the impacts on late adopters during regional gas phaseouts?

We have used the Systems Science Toolbox to understand current baselines, study resilience evaluate net zero pathways and optimise energy system operation^1,2,3,4. 

[1]  D. Thompson. The American Multi-modal Energy System: Model Development with Structural and Behavioral Analysis using Hetero-functional Graph Theory. PhD thesis, Thayer School of Engineering at Dartmouth, 2023.

[2]  D. Thompson and A. M. Farid. A hetero-functional graph structural analysis of the American multi-modal energy system. Sustainable Energy, Grids, and Networks, 38(1):101254–101269, 2024.

[3] A. M. Farid. A Hetero-functional Graph Resilience Analysis for Convergent Systems-of-Systems. Available at: https://arxiv.org/abs/2409.04936, 2024.

[4] W. C. Schoonenberg and A. M. Farid. Hetero-functional Network Minimum Cost Flow Optimization. Sustainable Energy Grids and Networks, 31(100749):1–18, 2022.