openego / powerd-data

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Model the neighboring countries in the historic sq #8

Closed ulfmueller closed 1 year ago

ulfmueller commented 1 year ago

Different options to decide on:

At first, probably stick to the current implementation of using p-e-s. Here we have to check:

ulfmueller commented 1 year ago

I would stick to the secondly mentioned option and see the firstly mentioned option as a very nice-to-have

ulfmueller commented 1 year ago

concerning our status quo year 2019 maybe we can use this here: https://github.com/PyPSA/pypsa-eur/blob/master/config.default.yaml#L116

ulfmueller commented 1 year ago

As a minimal approach, I would leave the current status of p-e-s as it is in order to get the neighboring grid topology hence then based on a gridkit abstraction of 2018. In addition I created a branch in which I added two functions to get historic generation capacities and demand time series for the neighboring countries. @CarlosEpia if you like, as we talked about feel free to follow up on this by a) creating mean values from the 15-min demand time values towards hourly values b) executing the mentioned functions and write the data in our etrago tables for the scenario status2019

Thanks a lot!

CarlosEpia commented 1 year ago

Hi Ulf. Here is the list of carriers from entso-e and the proposed carriers for our scenario2019. { 'Biomass': "biomass", 'Fossil Brown coal/Lignite': "lignite", 'Fossil Coal-derived gas': "coal", 'Fossil Gas': "CH4_NG", 'Fossil Hard coal': "coal", 'Fossil Oil': "oil", 'Fossil Oil shale': "oil", 'Fossil Peat': "biomass", 'Geothermal': "geo_thermal", 'Hydro Pumped Storage': "Hydro Pumped Storage", 'Hydro Run-of-river and poundage': "run_of_river", 'Hydro Water Reservoir': "reservoir", 'Marine': "marine", 'Nuclear': "nuclear", 'Other': "others", 'Other renewable': "others", 'Solar': "solar", 'Waste': "others", 'Wind Offshore': "wind_offshore", 'Wind Onshore': "wind_onshore", }