The modelling team are developing a novel method which takes a whole systems approach to simulate energy transitions towards a low carbon world.

The modelling team, led by Dr Adam Hawkes and Dr Sara Giarola,  include Alex Kell, Dr Pedro Gerber Machado and Diego Moya

The Imperial team have developed MUSE-Global, a 28-region implementation in the MUSE modelling framework, capable of assessing pathways to achieving the Paris Agreement on climate change mitigation.

What is an Energy Systems Model?

With more innovative technologies including renewables, increasing energy demands, and the threat of climate change, the energy system is constantly evolving. However, there is a very complex relationship between the energy system and the economy, technology, investors and consumers, the environment, and policies.

Energy system models can be used to make sense of these complexities, and study how changes can be managed. They have a huge range of potential uses, from building understanding around the key characteristics of successful technologies through to assessing the economic impact of energy and climate policy.

How does MUSE differ from other Energy Systems Models?

The MUSE (ModUlar energy system Simulation Environment) model is unique:

  1. An agent-based approach. MUSE models real investors. The behaviour of businesses and consumers can be tailored to be appropriate for each investor type in each sector.
  2. Micro-motivations lead to macro whole system outcomes. The complex behaviour and interactions of individual investors leads to the emergence of novel insights system wide.
  3. An economic equilibrium. MUSE finds a price-quantity based tension between supply and demand to achieve an equilibrium in every sector and every region modelled.
  4. A technology rich approach. Each technology is individually characterised regarding costs and engineering performance. MUSE can model thousands of technologies simultaneously.
  5. Flexible temporal and spatial resolution. Complementary research enables detailed characterisation of energy resources, infrastructure, and the distribution of demand.
  6. The MUSE code is open–source. Anyone can use it for their own work.

Who will be able to use the model?

Everyone. MUSE is designed for use by a range of beneficiaries, ranging from those who wish to input their own data and use inbuilt MUSE features, through to those who wish to develop new functionality and incorporate it within the highly flexible and professionally coded Python framework. For example, industry will be able to use it for technology/R&D roadmapping and strategy development, while it will help policy makers and international governments make future plans for climate change mitigation.

What will the model be used for?

  • Potential uses of MUSE are endless – researchers are constantly devising new ways to use it – and Imperial College welcomes novel and ambitious projects.
  • Our priorities are R&D road-mapping and strategy development with industry, while it can also help policy makers and governments make plans for climate change mitigation.
  • Explore the key characteristics of technologies that can be pivotal in reducing global greenhouse gas emissions at low cost.
  • Test different strategic scenarios of energy system investment in terms of timing, location and purpose. For example, examining the impact of CO2 removal technology on mitigation pathways.
  • Help international institutions build credible technology-rich global pathways of climate change mitigation, taking in to account sub-regional spatial characteristics of demand and resources, regional policy and markets, and local investors and consumers.

If you’d like more information…

Please contact us at SGI@imperial.ac.uk if you want more information on the Energy Systems Model.

You can also read about the model in an interview with Dr Adam Hawkes for Oil & Adjacent Gas ‘A thoroughly modern Engery Systems Model’. 

If you want to read more about the topic ‘Energy systems modeling for twenty-first century energy challenges‘ in Renewable and Sustainable Energy Reviews
33 (74–86) 2014 (only institutions with Elsevier access will be able to get the full article).