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06 - Comparing data - Enable scenario projection comparison#

This training course provides guidance on how you can document typical numerical data from climate and energy modelling so that the likelihood of a good-quality semi-automated scenario projection comparison based on the Open Enrgy Knowledgegraph (OEKG) increases.

You can provide feedback to this course on github: https://github.com/OpenEnergyPlatform/academy/issues/174

For whom is this training and what can you learn?#

This course is aimed at researchers, no matter whether you have programming skills or not, who

  • want to publish their data on the OEP
  • want that their data enables good quality scenario projection comparisons

After reading the sections of this training course you will

  • be able to document key scenario projection data in a way that helps the Open Energy Knowledge Graph (OEKG) to process semi-automated scenario projection comparisons

Why is it important to document my numerical data in a certain way?#

The OEP allows you to contribute numerical data in any structure and in any unit you want to. This is an important design feature of the OEP: it allows for a broad contribution of scenario projection data from heterogenous backgrounds. By allowing this, the OEP makes it easy for its users to contribute their data, without forcing them to invest additional time to obey to a mandatory format.

This potential heterogenity of how numerical data is structured and documented in terms of units, makes it challenging for semi-automated scenario projection comparisons to provide spot on results.

Thus we decided to provide some guidance on how to document your data so that the likelihood increases this data contributes to good quality semi-automated scenario projection comparisons that - sometime in the future - the OEKG will offer on the OEP.

Below we compiled a limited list of key input- and output data to many energy systems models. For those we suggest to report data in specific units.

Below we summarise this in a tabular format for easy reference. We name the variable / parameter and the unit we suggest you to report that information.

If a variable / parameter is already represented in the Open Energy Ontology (OEO) we link to its definition the first time it occurs below so that you can check for its exact definition.

Key output data#

Data Suggested unit Note
GHG emissions per sector Mt CO2e if possible by sector using a CRF sector division or a CRF-based sector division
CO2 emissions Mt CO2e if possible by sector using a CRF sector division or a CRF-based sector division
marginal cost of electricity generation Euro (base year) / MWh real monetary values allow easier comparison
levelised cost of electricity generation Euro (base year) / MWh real monetary values allow easier comparison
net electricity imports GWh
total gross electricity generation GWh
total net electricity generation GWh
(peak electricity generation) GWh

Key input data#

Data Suggested unit Note
GDP Million Euro (base year) real monetary values allow easier comparison
Gross value added per sector Million Euro (base year) real monetary values allow easier comparison
Population persons
International natural gas import price Euro (base year) / MWh real monetary values allow easier comparison
International crude oil import price Euro (base year) / MWh real monetary values allow easier comparison
International coal import price Euro (base year) / MWh real monetary values allow easier comparison
Total primary energy consumption MWh
Primary energy consumption by energy carrier MWh
Total final energy consumption MWh
Final energy consumption by sector MWh
Final energy consumption by energy carrier MWh
Steel production Mt
Cement production Mt
Passenger transport performance (all modes) Million pkm
Freight transport performance (all modes) Million tkm
Heating degree days °C temperature sum
Cooling degree days °C temperature sum
Total Generation capacity MW
Generation capacity by energy carrier MW
Energy storage MWh
Grid restrictions true/false

About this course#

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