The novel approach reduces the effort required when modelling the energy systems of a large number of countries. In her Masters’ thesis, Stephany developed a standardized set of rules for modelling prototypical energy systems that group countries facing similar challenges, so-called archetypes. The archetypes provide an adequate starting point to develop a set of solutions towards the decarbonisation of several countries’ electricity systems.
To reach climate targets, it is important to develop cost-efficient decarbonisation pathways for all countries around the world. This is not a trivial task; the process is data intensive and time-consuming, particularly when applying a global scope. In addition, many countries lack publicly available information about the energy system and its challenges.
In studies by the IEA, for example, countries are summarized into geographical regions, building a regional and global storyline towards decarbonisation. However, results for a region might not be representative of all countries within it, and some countries might not be able to directly apply the results to their situation.
To tackle this problem, Martin Kueppers at the energy system modelling team in Siemens developed the idea of classifying countries into archetypes in his dissertation work. The idea implies clustering countries based on socio-economic, climatic/geographic, and energy-related data irrespective of their geographical location. This way, the archetypes represent energy systems applicable to all UN member countries.
Moreover, the clustering provides an overview of different countries with similar challenges and the creation of a transferable database between them. This makes it possible to compare how similar countries have tackled common challenges. For example, if one country has started a phase-out strategy, other countries within the same archetype could learn from its example. Additionally, we found that the countries in each archetype would need similar technologies for decarbonization. For example, countries with high PV penetration have similar storage needs.
Once the archetypes were determined, two questions arose:
- How can we create an energy model for the archetypes based on the gathered set of data?
- Are the results from the model representative of the countries within it?
These were the questions that Stephany worked on in her Masters’ thesis. In it, she developed a framework and set of standardized rules to model each archetype’s energy system and evaluate its performance against specific country results. Overall, the results confirmed that archetypes are an adequate approach to derive a set of solutions for the decarbonisation of several countries and can yield significantly better results than geographical clustering into regions.
If you want to find out more about the concept, read the published paper at Elsevier’s Applied Energy Journal, or the pre-print version freely accessible at TechRxiv.
