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Merged
julianbornemann merged 4 commits into from
Aug 26, 2026
Merged

Add global data #52

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8200560
Add global data
viktorosenberg Aug 19, 2026
01d365e
Add more global time series
viktorosenberg Aug 19, 2026
631f01c
Add global data for time series, only missing PSNG, heat and hydro ROR
viktorosenberg Aug 20, 2026
b6b5bcd
Added global data for Hydro ROR
viktorosenberg Aug 25, 2026
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2 changes: 2 additions & 0 deletions Data/Timeseries/TS_COOL_LOW/Assumptions.txt
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Expand Up @@ -18,3 +18,5 @@ For capitals/countries not represented in Hotmaps, nearby countries/regions were
The cooling profiles generated from Hotmaps were then normalized to creat the TS_COOL_LOW.


Global data
Source: ERA5 with GENeSYS-MOD_RES_Tool.ipynb from GIS_&_Timeseries_Tool in GENeSYS_MOD.tools; 2026.07.21; Viktor Rosenberg <viktor.jonberg@gmail.com>
17,524 changes: 8,762 additions & 8,762 deletions Data/Timeseries/TS_COOL_LOW/TS_COOL_LOW.csv
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6 changes: 5 additions & 1 deletion Data/Timeseries/TS_HP_AIRSOURCE/Assumptions.txt
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Expand Up @@ -9,4 +9,8 @@ Assumptions:
- The time-specific COP is calculated based on desired indoor and outdoor temperatures.
- Then, each individual hour value is normed to the mean, which creates a timeseries that varies around the base value of 100%.
- A value of e.g. 120% would thus mean that in the particular hour, the heat pump uses 120% more energy than on average.
- The average efficiencies for heat pumps are given in the parameters (InputActivityRatio)
- The average efficiencies for heat pumps are given in the parameters (InputActivityRatio)


Global data
Source: ERA5 with GENeSYS-MOD_RES_Tool.ipynb from GIS_&_Timeseries_Tool in GENeSYS_MOD.tools; 2026.07.21; Viktor Rosenberg <viktor.jonberg@gmail.com>
17,524 changes: 8,762 additions & 8,762 deletions Data/Timeseries/TS_HP_AIRSOURCE/TS_HP_AIRSOURCE.csv
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6 changes: 5 additions & 1 deletion Data/Timeseries/TS_HP_GROUNDSOURCE/Assumptions.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -9,4 +9,8 @@ Assumptions:
- The time-specific COP is calculated based on desired indoor and outdoor temperatures.
- Then, each individual hour value is normed to the mean, which creates a timeseries that varies around the base value of 100%.
- A value of e.g. 120% would thus mean that in the particular hour, the heat pump uses 120% more energy than on average.
- The average efficiencies for heat pumps are given in the parameters (InputActivityRatio)
- The average efficiencies for heat pumps are given in the parameters (InputActivityRatio)


Global data
Source: ERA5 with GENeSYS-MOD_RES_Tool.ipynb from GIS_&_Timeseries_Tool in GENeSYS_MOD.tools; 2026.07.21; Viktor Rosenberg <viktor.jonberg@gmail.com>
17,524 changes: 8,762 additions & 8,762 deletions Data/Timeseries/TS_HP_GROUNDSOURCE/TS_HP_GROUNDSOURCE.csv
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2 changes: 2 additions & 0 deletions Data/Timeseries/TS_HYDRO_ROR/Assumptions.txt
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@@ -0,0 +1,2 @@
Global data
Source: ERA5 with modified GENeSYS-MOD_RES_Tool.ipynb from GIS_&_Timeseries_Tool in GENeSYS_MOD.tools; 2026.08.25; Viktor Rosenberg <viktor.jonberg@gmail.com>
17,524 changes: 8,762 additions & 8,762 deletions Data/Timeseries/TS_HYDRO_ROR/TS_HYDRO_ROR.csv
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10 changes: 10 additions & 0 deletions Data/Timeseries/TS_LOAD/Assumptions.txt
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Global data, 2026.08.15; Viktor Rosenberg <viktor.jonberg@gmail.com>
Source:
- For Europe Open Power System Data platform (2020) with aggregated hourly national data from the ENTSO-E Transparency Platform
- For Africa, Asia-Rest, FSU, Middle East and Central & South America generated data from https://zenodo.org/records/6569890
- For North America national data was compiled, summarised and normalised. US - https://www.eia.gov/electricity/gridmonitor/dashboard/electric_overview/US48/US48. Canada made out of three regions, Alberta - https://www.aeso.ca/market/market-and-system-reporting/data-requests/hourly-load-by-area-and-region/, Ontario - https://reports-public.ieso.ca/public/Demand/, Quebec - https://donnees.hydroquebec.com/explore/dataset/historique-demande-electricite-quebec/information/?refine.date=2019. Mexico data gathered from https://cenace.streamlit.app/#downloading-data for three grid networks.
- For India national data was collected and normalised, though for year 2019. Data collected from https://www.kaggle.com/datasets/shubhamvashisht/hourly-load-india-electrical-load-forecasting?resource=download
- For China generated data from https://zenodo.org/records/8322210 (did not include Mongolia)
was used
- For Oceania region was treated as Australia and New Zealand due to limited data availability, with Australia only being covered as southern and eastern regions. Australia - https://www.aemo.com.au/energy-systems/electricity/national-electricity-market-nem/data-nem/aggregated-data. New Zealand - https://www.ea.govt.nz/data-and-insights/datasets/wholesale/generation/generation-output/
- For Japan and Korea national data was collected and normalised. Japan - https://isep-energychart.com/en/graphics/electricityproduction/?region=all&period_year=2018&period_month=4&period_day=1&period_length=12+months&display_format=residual_demand. South Korea - https://www.data.go.kr/en/data/15065266/fileData.do
17,524 changes: 8,762 additions & 8,762 deletions Data/Timeseries/TS_LOAD/TS_LOAD.csv
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2 changes: 2 additions & 0 deletions Data/Timeseries/TS_PV_AVG/Assumptions.txt
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Global data
ERA5 with GENeSYS-MOD_RES_Tool.ipynb from GIS_&_Timeseries_Tool in GENeSYS_MOD.tools; 2026.07.21; Viktor Rosenberg <viktor.jonberg@gmail.com>
17,524 changes: 8,762 additions & 8,762 deletions Data/Timeseries/TS_PV_AVG/TS_PV_AVG.csv
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2 changes: 2 additions & 0 deletions Data/Timeseries/TS_PV_INF/Assumptions.txt
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Global data
ERA5 with GENeSYS-MOD_RES_Tool.ipynb from GIS_&_Timeseries_Tool in GENeSYS_MOD.tools; 2026.07.21; Viktor Rosenberg <viktor.jonberg@gmail.com>
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