renewable_feedin¶
Central module containing all code dealing with processing era5 weather data.
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class
MapZensusWeatherCell
(**kwargs)[source]¶ Bases:
sqlalchemy.ext.declarative.api.Base
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w_id
¶
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zensus_population_id
¶
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class
RenewableFeedin
(dependencies)[source]¶ Bases:
egon.data.datasets.Dataset
Calculate possible feedin time series for renewable energy generators
This dataset calculates possible feedin timeseries for fluctuation renewable generators and coefficient of performance time series for heat pumps. Relevant input is the downloaded weather data. Parameters for the time series calcultaion are also defined by representative types of pv plants and wind turbines that are selected within this dataset. The resulting profiles are stored in the database.
- Dependencies
- Resulting tables
supply.egon_era5_renewable_feedin
is filled
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name
= 'RenewableFeedin'¶
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version
= '0.0.7'¶
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federal_states_per_weather_cell
()[source]¶ Assings a federal state to each weather cell in Germany.
Sets the federal state to the weather celss using the centroid. Weather cells at the borders whoes centroid is not inside Germany are assinged to the closest federal state.
Returns: GeoPandas.GeoDataFrame – Index, points and federal state of weather cells inside Germany
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feedin_per_turbine
()[source]¶ Calculate feedin timeseries per turbine type and weather cell
Returns: gdf (GeoPandas.GeoDataFrame) – Feed-in timeseries per turbine type and weather cell
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heat_pump_cop
()[source]¶ Calculate coefficient of performance for heat pumps according to T. Brown et al: “Synergies of sector coupling and transmission reinforcement in a cost-optimised, highlyrenewable European energy system”, 2018, p. 8
Returns: None.
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insert_feedin
(data, carrier, weather_year)[source]¶ Insert feedin data into database
Parameters: - data (xarray.core.dataarray.DataArray) – Feedin timeseries data
- carrier (str) – Name of energy carrier
- weather_year (int) – Selected weather year
Returns: None.
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offshore_weather_cells
(geom_column='geom')[source]¶ Get weather cells which intersect with Germany
Returns: GeoPandas.GeoDataFrame – Index and points of weather cells inside Germany
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turbine_per_weather_cell
()[source]¶ Assign wind onshore turbine types to weather cells
Returns: weather_cells (GeoPandas.GeoDataFrame) – Weather cells in Germany including turbine type