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""" |
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Created on Tue May 24 14:42:05 2022 |
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Plotdatascn.py defines functions to plot to provide a better context of the different parameters part of |
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scenarios eGon2035 and eGon100RE . |
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@author: Alonso |
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""" |
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import logging |
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import os |
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from matplotlib import pyplot as plt |
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import geopandas as gpd |
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import matplotlib as mpl |
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import pandas as pd |
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from egon.data import db |
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logger = logging.getLogger(__name__) |
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if "READTHEDOCS" not in os.environ: |
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from geoalchemy2.shape import to_shape |
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__copyright__ = ( |
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"Flensburg University of Applied Sciences, " |
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"Europa-Universität Flensburg, " |
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"Centre for Sustainable Energy Systems, " |
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"DLR-Institute for Networked Energy Systems" |
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) |
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__license__ = "" |
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__author__ = "" |
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def plot_installedcapacity(carrier, scenario="eGon2035"): |
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""" |
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Plots color maps according to the capacity of different generators |
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of the two existing scenarios (eGon2035 and eGon100RE) |
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Parameters |
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---------- |
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carrier : generators |
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The list of generators: biomass, central_biomass_CHP, central_biomass_CHP_heat, |
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industrial_biomass_CHP, solar, solar_rooftop, wind_offshore, wind_onshore. |
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scenario: eGon2035, eGon100RE |
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Returns |
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---------- |
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""" |
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# This function must be called while in the folder |
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# that contains the file egon-data.configuration.yaml. |
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con = db.engine() |
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# imports buses of Germany |
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SQLBus = ( |
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"SELECT bus_id, country FROM grid.egon_etrago_bus WHERE country='DE'" |
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) |
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busDE = pd.read_sql(SQLBus, con) |
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busDE = busDE.rename({"bus_id": "bus"}, axis=1) |
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# Imports grid districs |
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sql = "SELECT bus_id, geom FROM grid.egon_mv_grid_district" |
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distr = gpd.GeoDataFrame.from_postgis(sql, con) |
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distr = distr.rename({"bus_id": "bus"}, axis=1) |
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distr = distr.set_index("bus") |
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# merges grid districts with buses |
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distr = pd.merge(busDE, distr, on="bus") |
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# Imports generator |
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sqlCarrier = "SELECT carrier, p_nom, bus FROM grid.egon_etrago_generator" |
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sqlCarrier = "SELECT * FROM grid.egon_etrago_generator" |
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Carriers = pd.read_sql(sqlCarrier, con) |
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Carriers = Carriers.loc[Carriers["scn_name"] == scenario] |
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Carriers = Carriers.set_index("bus") |
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CarrierGen = Carriers.loc[Carriers["carrier"] == carrier] |
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# merges districts with generators |
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Merge = pd.merge(CarrierGen, distr, on="bus", how="outer") |
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Merge.loc[Merge["carrier"] != carrier, "p_nom"] = 0 |
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Merge.loc[Merge["country"] != "DE", "p_nom"] = 0 |
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gdf = gpd.GeoDataFrame(Merge, geometry="geom") |
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pnom = gdf["p_nom"] # |
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# 0.95 quantile is used to filter values that are too high and make noise in the plots. |
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max_pnom = pnom.quantile(0.95) |
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gdf = gdf.to_crs(epsg=3857) |
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fig, ax = plt.subplots(1, 1) |
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ax.set_axis_off() |
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plt.title(f" {carrier} installed capacity in MW , {scenario}") |
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cmap = mpl.cm.coolwarm |
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norm = mpl.colors.Normalize(vmin=0, vmax=max_pnom) |
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gdf.plot( |
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column="p_nom", |
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ax=ax, |
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legend=False, |
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legend_kwds={"label": "p_nom(MW)", "orientation": "vertical"}, |
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cmap=cmap, |
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norm=norm, |
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edgecolor="black", |
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linewidth=0.1, |
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zorder=2, |
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) |
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scatter = ax.collections[0] |
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cbar = plt.colorbar(scatter, ax=ax, extend="max") |
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cbar.set_label("p_nom(MW)", rotation=90) |
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return |
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openego /
eGon-data
