Spatial resolutionΒΆ

The default nodal resolution of the model follows the electricity generation and transmission model PyPSA-Eur, which clusters down the electricity transmission substations in each European country based on the k-means algorithm. This gives nodes which correspond to major load and generation centres (typically cities).

The total number of nodes for Europe is set in the config.yaml file under clusters. The number of nodes can vary between 37, the number of independent countries / synchronous areas, and several hundred. With 200-300 nodes the model needs 100-150 GB RAM to solve with a commerical solver like Gurobi.

Not all of the sectors are at the full nodal resolution, and some demand for some sectors is distributed to nodes using heuristics that need to be corrected. Some networks are copper-plated to reduce computational times.

For example:

Electricity network: nodal.

Electricity residential and commercial demand: nodal, distributed in each country based on population and GDP.

Electricity demand in industry: based on the location of industrial facilities from HotMaps database.

Building heating demand: nodal, distributed in each country based on population.

Industry demand: nodal, distributed in each country based on locations of industry from HotMaps database.

Hydrogen network: nodal.

Methane network: single node for Europe, since future demand is so low and no bottlenecks are expected. Optionally, if for example retrofitting from fossil gas to hydrogen is to be considered, the methane grid can be nodally resolved based on SciGRID_gas data.

Solid biomass: choice between single node for Europe and nodal where biomass potential is regionally disaggregated (currently given per country, then distributed by population density within) and transport of solid biomass is possible.

CO2: single node for Europe, but a transport and storage cost is added for sequestered CO2. Optionally: nodal, with CO2 transport via pipelines.

Liquid hydrocarbons: single node for Europe, since transport costs for liquids are low.