This README.md file is adapted from the original by Bryn Pickering

This model is pre-packaged and ready to be loaded into Calliope, based on 2015 input data. 2050scenarioexample.py is an example script to run the model. To run the model you will need to do the following:

a. Install a specific conda environment to be working with the correct version of Calliope (conda env create -f requirements.yml)

b. Include specific scenarios to pick up the relevant sectors. The default is: "industry_fuel,transport,heat,config_overrides,res_24h,gas_storage,link_cap_dynamic,freeze-hydro-capacities,add-biofuel,synfuel_transmission,north_sea" where:

• industry_fuel: Includes all non-electrical industry demands distributed by region, and the necessary technologies to generate those fuels synthetically. This includes e.g. annual methanol requirements for the chemical industry.

• transport: This ensures ICE and EV light and heavy vehicle technologies and annual demands are in the model. It also includes reference to constraints required to make smart-charging of EVs work (e.g. weekly demand requirements).

• heat: This ensures that all heat provision technologies and hourly demands are in the model. Carriers added are heat (space heating and hot water) and cooking. Technologies added can be found in heat-techs.yaml.

• config_overrides: This includes high-level simplifications, such as removal of technologies that are considered redundant (e.g. less interesting combined heat and power technologies).

• res_24h: Sets the model with a 24h resolution. Can be omitted or can be one of res_2h, res_3h, res_6h, res_12h, res_24h. The full hourly resolution model is too massive to run on a laptop.

• gas_storage: Includes underground methane storage facilities, based on latest data on a national level. Can be omitted to remove the option of this technology.

• link_cap_dynamic: Sets a limit on transmission line capacities. The limits are chosen subjectively based on current capacity, such that lines with smaller current capacities can proportionally increase much more (e.g. 100x) than larger lines (e.g. 2x). See national/links.yaml for other override options to apply here.

• freeze-hydro-capacities: Sets hydro capacities to equal "today's" capacities. This seems more reasonable than setting current capacities as upper limits, as this causes the model to install no hydro.

• add-biofuel: Enables a biofuel supply stream with a distinct biofuel carrier, with annual limits on biofuel that can be provided (based on JRC residuals). This differs from Euro-Calliope v1.0 which is a black box technology converting biofuel to electricity directly.

• synfuel_transmission: Enables methane and diesel to be distributed around all model regions, without losses. This can be useful to ensure that if diesel/methane is produced in region A for transport/heating, it can be consumed in region B.

• north_sea: Kills leftover countries from the full-scale Euro-Calliope model, subsetting the scope to the North-Sea region.

In addition, the North-Sea-Calliope-AWE-floatwind workflow has some extra scenarios that are included in the folder overrrides_Hiddevosthesis, being:

• The technologies are defined in renewables-techs.yaml. In locations.yaml, the available land area (in km^2), and minimal installed capacities of floating wind and offshore wind are defined, as well as max installed capacity for other technologies.

• 'scenario_2050' : These files all represent a different scenario throughout which cost inputs of one technology are varied.

scenario_2050_1_1 to scenario_2050_1_9 are for the offshore AWE scenarios

scenario_2050_2_1 to scenario_2050_2_11 are for the onshore AWE scenarios with power density of 2MW/km^2. To run the 4MW/km^2 or 8MW/km^2 scenarios, simply change the resource_area_per_energy_cap constraint in the renewable-techs.yaml file to 2.5 or 1.25 respectively and change the output netcdf file names.

scenario_2050_5_1 to scenario_2050_5_9 are for the floating wind scenarios. When running these scenarios, you have to disable the AWE techs by commenting the lines in renewable-techs.yaml where they are defined. Additionally, the awe techs have to be left out in the floatwind_groupconstraints.yaml and offshorewind_groupconstraints.yaml scenarios. Lastly, the awe techs have to be commented in the locations.yaml file.

• 'Land restricted scenarios': As mentioned in the paper, the land availability was restricted for the offshore AWE and floating wind scenarios. To do this, simply change the available_area constraint accordingly in locations.yaml

• 'floatwind_groupconstraints': maximum combined installed capacity for awe_deep and wind_floating. Override name: floatwind_cap_max

• 'offshorewind_groupconstraints': maximum combined installed capacity for awe_shallow and wind_offshore wind. Override name: offshorewind_cap_max

• 'onshorewind_min': minimal installed capacities for onshore wind turbines. Override name: onshorewind_cap_min

2050scenarioexample.py provides and example to run the model with the default settings (12h resolution) and additionally the following overrides: scenario_2050_2_11,floatwind_cap_max,offshorewind_cap_max,onshorewind_cap_min

The scripts to run all the different scenarios on the delftblue high performance cluster are included in the folder: 'scenario scripts'.

In addition, you can model 2030 or 2050 projection years. To model the 2030 year, you need to add some additional overrides.

For instance, for 2030: industry_fuel,transport,heat,config_overrides,gas_storage,link_cap_1x,freeze-hydro-capacities,synfuel_transmission,heat_techs_2030,renewable_techs_2030,transformation_techs_2030,2030_neutral,fossil-fuel-supply,res_24h,add-biofuel,coal_supply,north_sea. Here, various technology overrides are applied, along with fossil fuel technologies and a corresponding emission cap scenario.

c. run the model via the dedicated scripts found in this directory. This is a new part of the process, since we now rely on a new version of Calliope with all custom Euro-Calliope constraints added as 'custom constraints'. These scripts have been copied directly from snakemake, but you can load and run them in an interactive session / with your own python script to call them:

import create_input
create_input.build_model(path_to_model_yaml, scenarios_string, path_to_netcdf_of_model_inputs)

import run
run.run_model(path_to_netcdf_of_model_inputs, path_to_netcdf_of_results)