CROSS harmonising assumptions

Comparable results

Comparability
CROSS harmonises key modelling assumptions such as population, GDP, energy demand and technology costs to enable meaningful comparison of energy system model results

Shared input data

Reference
Key drivers such as population, GDP, energy demand and technology costs are defined using common reference ranges.

Continuously updated

Dynamic
Assumptions are regularly reviewed and updated based on research developments and official data sources.

CROSS harmonises key modelling assumptions such as population, GDP, energy demand and technology costs to enable meaningful comparison of energy system model results.

About

Assumptions

Why harmonising assumptions matters?

Energy system models rely on many input assumptions, including population growth, economic development, technology costs and energy demand patterns.

If each modelling team uses different assumptions, the resulting scenarios become difficult to compare. Differences in results may simply reflect different input values rather than genuine differences in modelling approaches.

To address this challenge, CROSS provides a set of harmonised modelling assumptions that serve as common reference values across modelling teams. This allows scenario results to be compared in a meaningful and transparent way.

The harmonised assumptions support the comparison of results across models participating in the CROSS scenarios framework.

What is included in harmonised assumptions

CROSS assumptions cover the main drivers used across energy system modelling frameworks

Technologies

Investment costs, efficiencies and performance parameters

Macro-economic variables

Population, GDP, Households

Demands

Annual demand of different energy end uses

Demand behaviour

Demand hourly profiles and EV charging profiles

Fuel import prices

Import prices of energy carriers

Resources

Renewable and biomass potentials

Get the latest assumptions

Browse and download the most recent harmonised assumptions and their versions via CROSSDat.

Full reports

Assumptions reports describe the available data and their estimation

How this connects to the CROSS ecosystem

Harmonised assumptions link the data and documentation layers of CROSS so users can move from inputs to scenarios and results with full transparency

CROSSDat

CROSS scenarios