Migrate transmission grid functions to eTraGo

[ClaraBuettner]

eGo currently includes functions which analyze only the transmission grid side. It would be better to migrate them to eTraGo, or replace them with existing eTraGo-functions.

eGo/ego/tools/economics.py

Lines 117 to 162 in d121771

	def etrago_convert_overnight_cost(annuity_cost, json_file, t=40, p=0.05):
	"""Get annuity cost of simulation and calculation total
	``overnight_costs`` by given capital costs and lifetime.
	Parameters
	----------
	json_file : :obj:dict
	Dictionary of the ``scenario_setting.json`` file
	_start_snapshot : int
	Start point of calculation from ``scenario_setting.json`` file
	_end_snapshot : int
	End point of calculation from ``scenario_setting.json`` file
	_p : numeric
	interest rate of investment
	_T : int
	lifetime of investment
	Returns
	-------
	overnight_cost : numeric
	Scenario and calculation total ``overnight_costs`` by given
	annuity capital costs and lifetime.
	Examples
	--------
	.. math::
	PVA = (1 / p) - (1 / (p*(1 + p)^t))
	K_{ON} = K_a*PVA*((t/(period+1))
	"""
	# Based on eTraGo calculation in
	# https://github.com/openego/eTraGo/blob/dev/etrago/tools/utilities.py#L651
	# Calculate present value of an annuity (PVA)
	PVA = (1 / p) - (1 / (p * (1 + p) ** t))
	year = 8760
	# get period of calculation
	period = json_file["eTraGo"]["end_snapshot"] - json_file["eTraGo"]["start_snapshot"]
	# calculation of overnight_cost
	overnight_cost = annuity_cost * (PVA * (year / (period + 1)))
	return overnight_cost

-> should be moved to eTraGo and needs to be adjusted

eGo/ego/tools/plots.py

Lines 78 to 111 in d121771

	def carriers_colore():
	"""Return matplotlib colore set per carrier (technologies of
	generators) of eTraGo.
	Returns
	-------
	colors : :obj:`dict`
	List of carriers and matplotlib colores
	"""
	colors = {
	"biomass": "green",
	"coal": "k",
	"gas": "orange",
	"eeg_gas": "olive",
	"geothermal": "purple",
	"lignite": "brown",
	"oil": "darkgrey",
	"other_non_renewable": "pink",
	"reservoir": "navy",
	"run_of_river": "aqua",
	"pumped_storage": "steelblue",
	"solar": "yellow",
	"uranium": "lime",
	"waste": "sienna",
	"wind": "skyblue",
	"slack": "pink",
	"load shedding": "red",
	"nan": "m",
	"imports": "salmon",
	"": "m",
	}
	return colors

-> can be replaced by etrago.carrier_colors

eGo/ego/tools/plots.py

Lines 132 to 433 in d121771

	def plot_storage_expansion(
	ego, filename=None, dpi=300, column="overnight_costs", scaling=1
	):
	"""Plot line expantion
	Parameters
	----------
	ego : :class:`ego.tools.io.eGo`
	eGo ``eGo`` inclueds eTraGo and eDisGo results
	filename: str
	Filename and/or path of location to store graphic
	dpi: int
	dpi value of graphic
	column: str
	column name of eTraGo's line costs. Default: ``overnight_costs`` in EURO.
	Also available ``s_nom_expansion`` in MVA or
	annualized ``investment_costs`` in EURO
	scaling: numeric
	Factor to scale storage size of bus_sizes
	Returns
	-------
	plot :obj:`matplotlib.pyplot.show`
	https://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.show
	"""
	network = ego.etrago.network
	json_file = ego.json_file
	# get storage values
	if "storage" in ego.json_file["eTraGo"]["extendable"]:
	storage_inv = network.storage_units[network.storage_units.capital_cost > 0.0]
	storage_inv["investment_costs"] = (
	storage_inv.capital_cost * storage_inv.p_nom_opt
	)
	storage_inv["overnight_costs"] = etrago_convert_overnight_cost(
	storage_inv["investment_costs"], json_file
	)
	msd_max = storage_inv[column].max()
	msd_median = storage_inv[column].median()
	msd_min = storage_inv[column].min()
	if (msd_max - msd_min) > 1.0e5:
	if msd_max != 0:
	LabelVal = int(log10(msd_max))
	else:
	LabelVal = 0
	if LabelVal < 0:
	LabelUnit = "€"
	msd_max, msd_median, msd_min = (
	msd_max * 1000,
	msd_median * 1000,
	msd_min * 1000,
	)
	storage_inv[column] = storage_inv[column] * 1000
	elif LabelVal < 3:
	LabelUnit = "k €"
	else:
	LabelUnit = "M €"
	msd_max, msd_median, msd_min = (
	msd_max / 1000,
	msd_median / 1000,
	msd_min / 1000,
	)
	storage_inv[column] = storage_inv[column] / 1000
	else:
	LabelUnit = "€"
	# start plotting
	figsize = 6, 6
	fig, ax = plt.subplots(1, 1, figsize=(figsize))
	bus_sizes = storage_inv[column] * scaling
	if column == "investment_costs":
	title = "Annualized Storage costs per timestep"
	ltitel = "Storage costs"
	if column == "overnight_costs":
	title = "Total Expansion Costs Overnight"
	ltitel = "Storage costs"
	if column == "p_nom_opt":
	title = "Storage Expansion in MVA"
	ltitel = "Storage size"
	LabelUnit = "kW"
	if column not in ["investment_costs", "overnight_costs", "p_nom_opt"]:
	title = "unknown"
	ltitel = "unknown"
	LabelUnit = "unknown"
	if sum(storage_inv[column]) == 0:
	sc = network.plot(bus_sizes=0, ax=ax, title="No storage expantion")
	else:
	sc = network.plot(
	bus_sizes=bus_sizes,
	bus_colors="g",
	# bus_cmap=
	# line_colors='gray',
	title=title,
	line_widths=0.3,
	)
	ax.set_alpha(0.4)
	# add legend
	for area in [msd_max, msd_median, msd_min]:
	plt.scatter(
	[],
	[],
	c="white",
	s=area * scaling,
	label="= " + str(round(area, 0)) + LabelUnit + " ",
	)
	plt.legend(
	scatterpoints=1,
	labelspacing=1,
	title=ltitel,
	loc="upper left",
	shadow=True,
	fontsize="x-large",
	)
	ax.autoscale(tight=True)
	if filename is None:
	plt.show()
	else:
	fig = ax.get_figure()
	fig.set_size_inches(10, 8, forward=True)
	fig.savefig(filename, dpi=dpi)
	plt.close()
	def plot_line_expansion(ego, filename=None, dpi=300, column="overnight_costs"):
	"""Plot line expantion
	Parameters
	----------
	ego : :class:`ego.tools.io.eGo`
	eGo ``eGo`` inclueds eTraGo and eDisGo results
	filename: str
	Filename and or path of location to store graphic
	dpi: int
	dpi value of graphic
	column: str
	column name of eTraGo's line costs. Default: ``overnight_costs`` in EUR.
	Also available ``s_nom_expansion`` in MVA or
	annualized ``investment_costs`` in EUR
	Returns
	-------
	plot :obj:`matplotlib.pyplot.show`
	https://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.show
	"""
	network = ego.etrago.network
	json_file = ego.json_file
	# get values
	if "network" in ego.json_file["eTraGo"]["extendable"]:
	network.lines["s_nom_expansion"] = network.lines.s_nom_opt.subtract(
	network.lines.s_nom, axis="index"
	)
	network.lines["investment_costs"] = network.lines.s_nom_expansion.multiply(
	network.lines.capital_cost, axis="index"
	)
	network.lines["overnight_costs"] = etrago_convert_overnight_cost(
	network.lines["investment_costs"], json_file
	)
	else:
	network.lines["s_nom_expansion"] = None
	network.lines["investment_costs"] = None
	network.lines["overnight_costs"] = None
	# start plotting
	figsize = 10, 8
	fig, ax = plt.subplots(1, 1, figsize=(figsize))
	cmap = plt.cm.jet
	if column == "s_nom_expansion":
	line_value = network.lines[column]
	title = "Line expansion in MVA"
	if column == "overnight_costs":
	line_value = network.lines[column]
	title = "Total Expansion Costs in € per line"
	if column == "investment_costs":
	line_value = network.lines[column]
	title = "Annualized Expansion Costs in € per line and time step"
	line_widths = line_value / line_value.max()
	lc = network.plot(
	ax=ax,
	line_colors=line_value,
	line_cmap=cmap,
	title=title,
	line_widths=line_widths,
	)
	boundaries = [min(line_value), max(line_value)]
	v = np.linspace(boundaries[0], boundaries[1], 101)
	print(v.dtype.name)
	# colorbar
	cb = plt.colorbar(lc[1], boundaries=v, ticks=v[0:101:10], ax=ax)
	cb.set_clim(vmin=boundaries[0], vmax=boundaries[1])
	if column == "s_nom_expansion":
	cb.set_label("Expansion in MVA per line")
	if column == "overnight_costs":
	cb.set_label("Total Expansion Costs in € per line")
	if column == "investment_costs":
	cb.set_label("Annualized Expansion Costs in € per line")
	ax.autoscale(tight=True)
	if filename is None:
	plt.show()
	else:
	fig = ax.get_figure()
	fig.set_size_inches(10, 8, forward=True)
	fig.savefig(filename, dpi=dpi)
	plt.close()
	def plot_grid_storage_investment(costs_df, filename, display, var=None):
	"""Plot total grid and storage investment.
	Parameters
	----------
	costs_df: :pandas:`pandas.DataFrame<dataframe>`
	Dataframe containing total_investment_costs of ego
	filename: str
	Filename and or path of location to store graphic
	display: bool
	Display plot
	var: str
	Cost variable of ``overnight_cost`` by default displays annualized
	costs of timesteps
	Returns
	-------
	plot :obj:`matplotlib.pyplot.show`
	https://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.show
	"""
	colors = ego_colore()
	bar_width = 0.35
	opacity = 0.4
	if var == "overnight_cost":
	tic = costs_df[
	["component", "overnight_costs", "voltage_level", "differentiation"]
	]
	tic.set_index(["voltage_level", "component", "differentiation"], inplace=True)
	ax = tic.unstack().plot(
	kind="bar",
	stacked=False,
	rot=0,
	color=([colors.get(key) for key in ["egoblue1", "egoblue2", "egoblue4"]]),
	legend=False,
	)
	ax.set_ylabel("Overnight costs of simulation")
	ax.set_title(
	"Total costs of simulation, " "voltage level and component", y=1.08
	)
	else:
	tic = costs_df[
	["component", "capital_cost", "voltage_level", "differentiation"]
	]
	tic.set_index(["voltage_level", "component", "differentiation"], inplace=True)
	ax = tic.unstack().plot(
	kind="bar",
	rot=0,
	stacked=False,
	color=([colors.get(key) for key in ["egoblue1", "egoblue2", "egoblue3"]]),
	legend=False,
	)
	ax.set_ylabel("Annualized costs per simulation periods")
	ax.set_title(
	"Annualized costs per simulation periods, " "voltage level and component",
	y=1.08,
	)
	ax.set_xlabel("Voltage level and component")
	ax.set_yscale("symlog")
	ax.legend(("cross-border", "domestic", "foreign"))
	ax.autoscale()
	if display is True:
	plt.show()
	else:
	fig = ax.get_figure()
	fig.set_size_inches(10, 8, forward=True)
	fig.savefig(filename, dpi=100)
	plt.close()

-> in case these are only plotting results from eTraGo, they can be replaced by existing eTraGo plots

eGo/ego/tools/plots.py

Lines 436 to 527 in d121771

	def power_price_plot(ego, filename, display):
	"""
	Plot power price of calculated scenario of timesteps and carrier
	Parameters
	----------
	ego : :class:`ego.tools.io.eGo`
	eGo ``eGo`` inclueds eTraGo and eDisGo results
	filename: str
	Filename and or path of location to store graphic
	display: bool
	Display plot
	Returns
	-------
	plot :obj:`matplotlib.pyplot.show`
	https://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.show
	"""
	plt.rcdefaults()
	# colors = ego_colore()
	carrier_colors = coloring()
	fig, ax = plt.subplots()
	# plot power_price
	prc = ego.etrago.generator["power_price"]
	bar_width = 0.35
	opacity = 0.4
	ind = np.arange(len(prc.index)) # the x locations for the groups
	width = 0.35 # the width of the bars: can also be len(x) sequence
	plt_colors = [carrier_colors[carrier] for carrier in prc.index]
	# plt_colors = colors['egoblue1']
	ax.barh(ind, prc, align="center", color=plt_colors)
	ax.set_yticks(ind)
	ax.set_yticklabels(prc.index)
	ax.invert_yaxis()
	ax.set_xlabel("Power price in €/MWh")
	ax.set_title("Power Costs per Carrier")
	ax.autoscale(tight=True)
	if display is True:
	plt.show()
	else:
	fig = ax.get_figure()
	fig.set_size_inches(10, 8, forward=True)
	fig.savefig(filename, dpi=100)
	def plot_storage_use(ego, filename, display):
	"""Plot storage use by charge and discharge values
	Parameters
	----------
	ego : :class:`ego.tools.io.eGo`
	eGo ``eGo`` inclueds eTraGo and eDisGo results
	filename: str
	Filename and or path of location to store graphic
	display: bool
	Display plot
	Returns
	-------
	plot :obj:`matplotlib.pyplot.show`
	https://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.show
	"""
	colors = ego_colore()
	ax = ego.etrago.storage_charges[["charge", "discharge"]].plot(
	kind="bar",
	title="Storage usage",
	stacked=True,
	color=([colors.get(key) for key in ["egoblue1", "egoblue2"]]),
	figsize=(15, 10),
	legend=True,
	fontsize=12,
	)
	ax.set_xlabel("Kind of Storage", fontsize=12)
	ax.set_ylabel("Charge and Discharge in MWh", fontsize=12)
	ax.autoscale(tight=False)
	if display is True:
	plt.show()
	else:
	fig = ax.get_figure()
	fig.set_size_inches(10, 8, forward=True)
	fig.subplots_adjust(bottom=0.25)
	fig.savefig(filename, dpi=100)

-> sth like this is currently not part of eTraGo. If we need it, it needs to be adjusted and moved to eTraGo

eGo/ego/tools/plots.py

Lines 530 to 576 in d121771

	def get_country(session, region=None):
	"""Get Geometries of scenario Countries.
	Parameters
	----------
	session : :sqlalchemy:`sqlalchemy.orm.session.Session<orm/session_basics.html>`
	SQLAlchemy session to the OEDB
	region: list
	List of background countries e.g. ['DE', 'DK']
	Returns
	-------
	country: ``geopandas.GeoDataFrame``
	GeoDataFrame inclueds MultiPolygon of selected regions or countries
	"""
	if region is None:
	# Define regions 'FR',
	region = ["DE", "DK", "BE", "LU", "NO", "PL", "CH", "CZ", "SE", "NL"]
	else:
	region
	# get database tabel
	query = session.query(
	RenpassGisParameterRegion.gid,
	RenpassGisParameterRegion.stat_level,
	RenpassGisParameterRegion.u_region_id,
	RenpassGisParameterRegion.geom,
	RenpassGisParameterRegion.geom_point,
	)
	# get regions by query and filter
	Regions = [
	(gid, u_region_id, stat_level, shape.to_shape(geom), shape.to_shape(geom_point))
	for gid, u_region_id, stat_level, geom, geom_point in query.filter(
	RenpassGisParameterRegion.u_region_id.in_(region)
	).all()
	]
	# define SRID
	crs = {"init": "epsg:4326"}
	country = gpd.GeoDataFrame(
	Regions,
	columns=["gid", "stat_level", "u_region_id", "geometry", "point_geom"],
	crs=crs,
	)
	return country

-> not working anymore, no data from renpass gis, do we need it?