Implement scenario path

[ClaraBuettner]

No description provided.

[ulfmueller]

I will try to implement a pypsa-eur myopic scenario pathway creation in this branch.

[ulfmueller]

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P-e manipulator					todo	Issue
	2025	2030	2035	2045/longterm
drop_biomass()	no	no	no	yes
drop_urban_decentral_heat()	yes	yes	yes	yes
district_heating_shares()	yes	yes	yes	yes	Nutzen der Status Quo Werte aus p-e (basierend auf hotmaps) zur Interpolation mit eGon100RE – Werten	#307
update_heat_timeseries_germany()	yes	yes	yes	yes	Neu anwerfen des eGon-Codes für alle Jahre mit ‚interpolierten‘/recherchierten/von pyspa-eur deutschlandweiten Jahressummen	#308
update_electrical_timeseries_germany()	yes	yes	yes	yes		#309
geothermal_district_heating()	?	?	?	?	V0.12. Hat geothermal elec und heat. wie wird georeferenziert in eGon-data, wenn nicht, dann evtl. einfach weglassen/ von p-e machen lassen	#323
h2_overground_stores()	yes	yes	yes	yes
drop_new_gas_pipelines()	yes	yes	yes	yes
drop_fossil_gas()	no	no	no	yes
rual_heat_technologies()				yes/no
of which task kick out gas boiler	no	no	no	yes/no
of which task kick out solar thermal	no	no	no	no

[ClaraBuettner]

I checked how geothermal power plants are distributed within powerd-data. It considers if there is a geothermal potential next to the district heating grid. So I guess it makes sense to keep our implementation since the spatial distribution make a larger difference.

[CarlosEpia]

Regarding the bus carriers and quantities, using the last versions of status2019 and eGon100RE, we have the next differences and questions to be solved for the intermedium scenarios:

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	status2019	eGon100RE	Diff	Note
rural_heat	3627	3639	12	Small difference. Probably gone with scenarios based on the same network?
urban_central_water_tanks	0	14	14	Is it ok to have a very small number of buses? When to include this?
CH4	1	633	632	When to include the CH4 network?
battery	0	14	14	Is it ok to have a very small number of buses?
H2_saltcavern	0	205	205	When to include this?
central_heat_store	0	3723	3723	OK
rural_water_tanks	0	14	14	Is it ok to have a very small number of buses? When to include this?
Li ion	0	3615	3615	When to include this?
H2	0	633	633	When to include this?
AC	12052	12053	1	Gone with scenarios based on the same network
220 kV	1213	1216	3	Gone with scenarios based on the same network
380 kV	1408	1413	5	Gone with scenarios based on the same network
110 kV	9431	9424	-7	Gone with scenarios based on the same network
Li_ion	0	14	14	Is it ok to have a very small number of buses?
dsm	0	3579	3579	When to include this?
urban_central_heat	0	14	14	Is it ok to have a very small number of buses?
CH4_for_industry	0	14	14	Should it even exist?
central_heat	1868	3723	1855	When to include the new buses?
rural_heat_store	0	3625	3625	When to include the new buses?

What do you think @ClaraBuettner and @ulfmueller? Do you see strange values (especially in eGon100RE) that we must deal with before the next run?

[ClaraBuettner]

Are these all buses in all considered countries?
I think the 14 buses that exist for some carriers could come from pypsa-eur for the foreign countries. Some of the names should be aligned I think (e.g. urban_central_water_tanks = central_heat_store; Li ion = Li_ion ...)

[CarlosEpia]

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	status2019	status2019	status2019	eGon100RE	eGon100RE	eGon100RE
	Total	DE	Foreign	Total	DE	Foreign	Diff_total	Diff_DE	Diff_foreign	Note
110 kV	9431	9401	26	9424	9394	26	-7	-7	0	Gone with scenarios based on the same network
220 kV	1213	1189	24	1216	1192	24	3	3	0	Gone with scenarios based on the same network
380 kV	1408	1375	33	1413	1380	33	5	5	0	Gone with scenarios based on the same network
AC	12052	11965	83	12053	11966	83	1	1	0	Gone with scenarios based on the same network
battery	0	0	0	14	0	14	14	0	14	Do we need buses for batteries?
central_heat	1868	1868	0	3723	3723	0	1855	1855	0	When to include the new buses?
central_heat_store	0	0	0	3723	3723	0	3723	3723	0	OK
CH4	1	1	0	633	619	14	632	618	14	When to include the CH4 network? How to proceed with the CHPs?
CH4_for_industry	0	0	0	14	0	14	14	0	14	Should it even exist?
dsm	0	0	0	3579	3579	0	3579	3579	0	When and how to include this?
H2	0	0	0	633	619	14	633	619	14	When to include this?
H2_saltcavern	0	0	0	205	205	0	205	205	0	When to include this?
Li ion	0	0	0	3615	3615	0	3615	3615	0	When to include this?
Li_ion	0	0	0	14	0	14	14	0	14	Change the name to “Li ion”?
rural_heat	3627	3627	0	3639	3625	14	12	-2	14	Small difference in DE. Probably gone with scenarios based on the same network. When to include the foreign buses?
rural_heat_store	0	0	0	3625	3625	0	3625	3625	0	When to include the new buses?
rural_water_tanks	0	0	0	14	0	14	14	0	14	Change the name to “rural_heat_store”?
urban_central_heat	0	0	0	14	0	14	14	0	14	Change the name to “central_heat”? When to include this?
urban_central_water_tanks	0	0	0	14	0	14	14	0	14	Change the name to “central_heat_store”? When to include this?

@ClaraBuettner good point. I updated the table to show the differences including specific country data. So far the questions are mostly about when to include the extra buses and how. In the case of the CH4 network, which has only 1 bus in the status2019, the changes in the intermedium scenarios will require major intervention. e.g. CHP generators.

[ClaraBuettner]

We can create status2019 and eGon100RE in one pipeline to make sure that the same results from osmTGmod are used (see #342).
The demand time series in foreign countries in the status2019 are the ones from 2019 although the weather and calender year for all other time series is 2011. This should be considered when creating the intermediate scenarios. I would suggest to directly use the demand time series from pypsa-eur (they are available for all years) to avoid any problems.

[CarlosEpia]

We can create status2019 and eGon100RE in one pipeline to make sure that the same results from osmTGmod are used (see #342). The demand time series in foreign countries in the status2019 are the ones from 2019 although the weather and calender year for all other time series is 2011. This should be considered when creating the intermediate scenarios. I would suggest to directly use the demand time series from pypsa-eur (they are available for all years) to avoid any problems.

Sure. I think using the demand time-series from Pypsa-eur as you suggested is our best option.