def plot_zones():
net = get_net_118_with_zones()
areas = get_subnets(net)
fig, axes = plt.subplots(1, len(areas.keys()))
keys = areas.keys()
keys = sorted(keys)
for i, zone in enumerate(keys):
net = areas[zone]
collections = list()
ax = axes[i]
sizes = pplt.get_collection_sizes(net)
collections.append(pplt.create_bus_collection(net, size=sizes["bus"]))
collections.append(pplt.create_line_collection(net))
collections.append(
pplt.create_trafo_collection(net, size=sizes["trafo"]))
if zone == 3:
collections.append(
pplt.create_bus_collection(net,
net.bus.loc[net.bus.toy_zone].index,
color="g",
size=2 * sizes["bus"],
zorder=11))
pplt.draw_collections(collections, ax=ax)
plt.show()
def plot_feeder():
net = nw.case118()
fig, ax = plt.subplots(1, 1)
mg = top.create_nxgraph(net, nogobuses=set(net.trafo.lv_bus.values))
colors = sns.color_palette()
collections = list()
sizes = pplt.get_collection_sizes(net)
voltage_levels = net.bus.vn_kv.unique()
voltage_level_colors = dict(zip(voltage_levels, colors))
legend_entries = dict()
gens = set(net.gen.loc[:, "bus"].values)
for area, color in zip(top.connected_components(mg), colors):
vn_area = net.bus.loc[list(area)[0], "vn_kv"]
color = voltage_level_colors[vn_area]
legend_entries[vn_area] = color
area_gens = gens - area
other = area - gens
collections.append(
pplt.create_bus_collection(net,
area_gens,
color=color,
size=sizes["bus"],
zorder=11,
patch_type="rect"))
collections.append(
pplt.create_bus_collection(net,
other,
color=color,
size=sizes["bus"],
zorder=11))
line_ind = net.line.loc[:, "from_bus"].isin(
area) | net.line.loc[:, "to_bus"].isin(area)
lines = net.line.loc[line_ind].index
collections.append(pplt.create_line_collection(net, lines,
color=color))
eg_vn = net.bus.at[net.ext_grid.bus.values[0], "vn_kv"]
collections.append(
pplt.create_ext_grid_collection(net,
size=sizes["ext_grid"],
color=voltage_level_colors[eg_vn]))
collections.append(
pplt.create_trafo_collection(net, size=sizes["trafo"], zorder=1))
pplt.draw_collections(collections, ax=ax)
custom_legend(fig, entries=legend_entries)
legend_entries = {"gen": "grey"}
custom_legend(fig, entries=legend_entries, loc='center right', marker="s")
print_info(net, fig)
plt.show()
def plot_network(net):
# función que recibe una red y la grafica.
colors = ["k", "b", "g", "r", "c", "y"]
buses = net.bus.index.tolist()
coords = zip(net.bus_geodata.x.loc[buses].values + 0.02,
net.bus_geodata.y.loc[buses].values + 0.02)
lc = plot.create_line_collection(net,
net.line.index,
color=colors[0],
use_bus_geodata=True,
zorder=1)
bc = plot.create_bus_collection(net,
net.bus.index,
size=0.02,
bus_geodata=None,
color=colors[0],
zorder=2)
bic = plot.create_annotation_collection(size=0.07,
texts=np.char.mod('%d', buses),
coords=coords,
zorder=3,
color=colors[0])
tf = plot.create_trafo_collection(net,
trafos=net.trafo.index,
color=colors[0],
size=0.04,
zorder=4)
sc = plot.create_bus_collection(net,
net.ext_grid.bus.values,
patch_type="rect",
size=0.03,
color=colors[2],
zorder=5)
ld = plot.create_load_collection(net, size=0.03)
sg = plot.create_sgen_collection(net,
sgens=net.sgen.index[1:],
size=0.05,
orientation=0)
sg1 = plot.create_sgen_collection(net,
sgens=[net.sgen.index[0]],
size=0.05,
orientation=np.pi / 2)
sw = plot.create_line_switch_collection(net,
size=0.04,
distance_to_bus=0.08)
return plot.draw_collections([lc, bc, bic, tf, sc, ld, sg, sg1, sw],
figsize=(7, 10))
def plot_network(net):
# create buses ID
buses = net.bus.index.tolist() # list of all bus indices
coords = zip(net.bus_geodata.x.loc[buses].values + 0.15,
net.bus_geodata.y.loc[buses].values +
0.07) # tuples of all bus coords
bic = plot.create_annotation_collection(size=0.2,
texts=np.char.mod('%d', buses),
coords=coords,
zorder=3,
color="black")
# creating a color function to get a linear a colormap with color centers green at 30%, yellow at 50% and red at 60%
# line loading
cmap_list_lines = [(20, "green"), (50, "yellow"), (60, "red")]
cmap_lines, norm_lines = plot.cmap_continuous(cmap_list_lines)
# create a collection for colouring each line according to a line color range.
lc = plot.create_line_collection(net,
net.line.index,
zorder=2,
cmap=cmap_lines,
norm=norm_lines,
linewidths=2)
# create discrete map for node pu magnitude
cmap_list_nodes = [(0.975, "blue"), (1.0, "green"), (1.03, "red")]
cmap_nodes, norm_nodes = plot.cmap_continuous(cmap_list_nodes)
bc = plot.create_bus_collection(
net,
net.bus.index,
size=0.07,
zorder=2,
cmap=cmap_nodes,
norm=norm_nodes) #80 of mv obherreim and 0.07 for ieee
tlc, tpc = plot.create_trafo_collection(net, net.trafo.index, color="g")
sc = plot.create_bus_collection(net,
net.ext_grid.bus.values,
patch_type="rect",
size=.08,
color="y",
zorder=11)
# draw the different collections
plot.draw_collections([lc, bc, tlc, tpc, sc, bic], figsize=(8, 6))
plt.show()
def updateBusCollection(self, redraw=False):
bc = plot.create_bus_collection(self.net,
size=self.scale * 0.01,
zorder=2,
picker=True,
color="black",
patch_type="rect",
infofunc=lambda x: ("bus", x))
self.collections["bus"] = bc
if redraw:
self.drawCollections()
def plot_net(net, ax=None):
if ax is None:
fig, ax = mpl.subplots(1, 1, figsize=(10, 7))
mean_distance_between_buses = sum(
(net['bus_geodata'].max() - net['bus_geodata'].min()).dropna() / 200)
bus_size = mean_distance_between_buses * 1.
ext_grid_size = mean_distance_between_buses * 1.
trafo_size = mean_distance_between_buses * .1
collections = list()
if ax is None:
fig, ax = plt.subplots(1, 1)
# create plot collection to visualize results
cmap, norm = plt.cmap_continuous([(0.9, "blue"), (1.0, "green"),
(1.1, "red")])
collections.append(
plt.create_bus_collection(net, size=bus_size, cmap=cmap, norm=norm))
cmap, norm = plt.cmap_continuous([(0., "green"), (50., "yellow"),
(100., "red")])
collections.append(
plt.create_line_collection(net,
use_bus_geodata=True,
linewidth=1.,
cmap=cmap,
norm=norm))
collections.append(
plt.create_trafo_collection(net,
size=trafo_size,
color="green",
alpha=.5))
collections.append(
plt.create_ext_grid_collection(net,
size=ext_grid_size,
orientation=1.5))
for idx in net.bus_geodata.index:
x = net.bus_geodata.loc[idx, "x"]
y = net.bus_geodata.loc[idx, "y"] + bus_size * 1.
ax.text(x + 0.01, y, str(idx), fontsize=8, color="k")
plt.draw_collections(collections, ax=ax)
mpl.tight_layout()
ax.axis('off')
mpl.show()
mpl.close()
def __init__(self, net):
super(SliderWidget, self).__init__()
self.setupUi(self)
self.net = net
self.net.line_geodata.drop(set(net.line_geodata.index) - set(net.line.index), inplace=True)
cmap, norm = plot.cmap_continous([(0.97, "blue"), (1.0, "green"), (1.03, "red")])
self.bc = plot.create_bus_collection(net, size=90, zorder=2, cmap=cmap, norm=norm, picker=True,
infofunc=lambda x: "This is bus %s"%net.bus.name.at[x])
cmap, norm = plot.cmap_continous([(20, "green"), (50, "yellow"), (60, "red")])
self.lc = plot.create_line_collection(net, zorder=1, cmap=cmap, norm=norm, linewidths=2,
infofunc=lambda x: "This is line %s"%net.line.name.at[x])
self.fig, self.ax = plt.subplots()
plot.draw_collections([self.bc, self.lc], ax=self.ax)
plt.close()
self.canvas = FigureCanvas(self.fig)
self.canvas.mpl_connect('pick_event', self.pick_event)
self.gridLayout.addWidget(self.canvas)
self.canvas.draw()
self.LoadSlider.valueChanged.connect(self.slider_changed)
self.SgenSlider.valueChanged.connect(self.slider_changed)
self.setWindowTitle("PyQt with pandapower Demo")
def network_plot(self, data: GridData, mode="topological_graph", pause=5):
"""
plot the network using matplotlib
* mode = topological_graph or color_map
"""
if mode == "topological_graph":
self.net.bus_geodata.drop(self.net.bus_geodata.index, inplace=True)
self.net.line_geodata.drop(self.net.line_geodata.index,
inplace=True)
pplot.create_generic_coordinates(self.net)
pplot.fuse_geodata(self.net)
buses = self.net.bus.index.tolist()
coords = zip(self.net.bus_geodata.x.loc[buses].values,
self.net.bus_geodata.y.loc[buses].values)
bus_layer = pplot.create_bus_collection(self.net,
self.net.bus.index,
size=.05,
color="black",
zorder=1)
sub_layer = pplot.create_bus_collection(
self.net,
self.net.ext_grid.bus.values,
patch_type="rect",
size=.2,
color="yellow",
zorder=2)
busid_layer = pplot.create_annotation_collection(size=0.2,
texts=np.char.mod(
'%d', buses),
coords=coords,
zorder=3,
color="blue")
line_layer = pplot.create_line_collection(self.net,
self.net.line.index,
color="grey",
linestyles="dashed",
linewidths=0.2,
use_bus_geodata=True,
zorder=4)
lines_ergized = self.net.line[self.net.line.in_service ==
True].index
line_ergized_layer = pplot.create_line_collection(self.net,
lines_ergized,
color="red",
zorder=5)
pplot.draw_collections([
line_layer, bus_layer, sub_layer, busid_layer,
line_ergized_layer
],
figsize=(8, 6))
pass
if mode == "color_map":
self.net.bus_geodata.drop(self.net.bus_geodata.index, inplace=True)
self.net.line_geodata.drop(self.net.line_geodata.index,
inplace=True)
voltage_map = [((0.00, 0.90), "lime"), ((0.90, 0.950), "g"),
((0.950, 1.05), "b"), ((1.05, 1.1), "m"),
((1.1, 1.5), "r")]
cmap, norm = pplot.cmap_discrete(voltage_map)
pplot.create_generic_coordinates(self.net)
pplot.fuse_geodata(self.net)
buses = self.net.bus.index.tolist()
coords = zip(self.net.bus_geodata.x.loc[buses].values,
self.net.bus_geodata.y.loc[buses].values)
bus_layer = pplot.create_bus_collection(self.net,
self.net.bus.index,
size=.05,
cmap=cmap,
norm=norm,
color="black",
zorder=1)
sub_layer = pplot.create_bus_collection(
self.net,
self.net.ext_grid.bus.values,
patch_type="rect",
size=.2,
color="yellow",
zorder=2)
busid_layer = pplot.create_annotation_collection(size=0.2,
texts=np.char.mod(
'%d', buses),
coords=coords,
zorder=3,
color="blue")
line_layer = pplot.create_line_collection(self.net,
self.net.line.index,
color="grey",
linestyles="dashed",
linewidths=0.2,
use_bus_geodata=True,
zorder=4)
lines_ergized = self.net.line[self.net.line.in_service ==
True].index
line_ergized_layer = pplot.create_line_collection(self.net,
lines_ergized,
color="red",
zorder=5)
pplot.draw_collections([
line_layer, bus_layer, sub_layer, busid_layer,
line_ergized_layer
],
figsize=(8, 6))
pass
plt.ion()
plt.plot()
# put the fault lines list in the figure
plt.annotate("fault lines: %s" % data.list_fault_line, (-2.3, -2.8))
if pause == 0:
plt.show()
else:
plt.pause(pause)
plt.close()
pass
# net = nw.mv_oberrhein() net=nw.case33bw() # net = nw.create_synthetic_voltage_control_lv_network(network_class='rural_1') # run pf pp.runpp(net) # creating a color function to get a linear a colormap with color centers green at 30%, yellow at 50% and red at 60% # line loading cmap_list_lines=[(20, "green"), (50, "yellow"), (60, "red")] cmap_lines, norm_lines = plot.cmap_continuous(cmap_list_lines) # create a collection for colouring each line according to a line color range. lc = plot.create_line_collection(net, net.line.index, zorder=2, cmap=cmap_lines, norm=norm_lines, linewidths=2) # create discrete map for node pu magnitude cmap_list_nodes=[(0.975, "blue"), (1.0, "green"), (1.03, "red")] cmap_nodes, norm_nodes = plot.cmap_continuous(cmap_list_nodes) bc = plot.create_bus_collection(net, net.bus.index, size=0.07, zorder=2, cmap=cmap_nodes, norm=norm_nodes) #80 of mv obherreim and 0.07 for ieee # tlc, tpc = plot.create_trafo_collection(net, net.trafo.index, color="g") sc = plot.create_bus_collection(net, net.ext_grid.bus.values, patch_type="rect", size=.08, color="y", zorder=11) # plot.draw_collections([lc, bc, sc], figsize=(8,6)) # plt.show() net_generic = nw.case33bw() net_generic.bus_geodata.drop(net_generic.bus_geodata.index, inplace=True) net_generic.line_geodata.drop(net_generic.line_geodata.index, inplace=True) plot.create_generic_coordinates(net_generic, respect_switches=True) #create artificial coordinates with the igraph package colors = ["b", "g", "r", "c", "y"] plot.fuse_geodata(net_generic) bc = plot.create_bus_collection(net_generic, net_generic.bus.index, size=.08, color=colors[0], zorder=10) lcd = plot.create_line_collection(net_generic, net_generic.line.index, color="grey", linewidths=0.5, use_bus_geodata=True) sc = plot.create_bus_collection(net_generic, net_generic.ext_grid.bus.values, patch_type="rect", size=.08, color="y", zorder=11) plot.draw_collections([lcd, bc, sc], figsize=(8,6))
import pandapower.networks as nw
import pandapower.plotting as plot
import matplotlib.pyplot as plt
import seaborn
colours = seaborn.color_palette()
net = nw.mv_oberrhein()
bc = plot.create_bus_collection(net,
buses=net.bus.index,
color=colours[0],
size=80,
zorder=1)
lc = plot.create_line_collection(net,
lines=net.line.index,
color='grey',
zorder=2)
long_lines = net.line.loc[net.line.length_km > 2.].index
lc1 = plot.create_line_collection(net,
lines=long_lines,
color=colours[2],
zorder=2)
plot.draw_collections([lc, bc, lc1])
plt.show()
net = nw.mv_oberrhein()
#net = nw.create_cigre_network_mv(with_der="pv_wind")
#lc = plot.create_line_collection(net, net.line.index, color="grey", zorder=1) #create lines
#bc = plot.create_bus_collection(net, net.bus.index, size=80, color=colors[0], zorder=2) #create buses
#plot.draw_collections([lc, bc], figsize=(8,6)) # plot lines and buses
long_lines = net.line[net.line.length_km > 2.].index
lc = plot.create_line_collection(net, net.line.index, color="grey", zorder=1)
lcl = plot.create_line_collection(net, long_lines, color=(.3, 1, .3), zorder=2)
pp.runpp(net)
low_voltage_buses = net.res_bus[net.res_bus.vm_pu < 0.98].index
bc = plot.create_bus_collection(net,
net.bus.index,
size=90,
color=(.2, .2, 1),
zorder=10)
bch = plot.create_bus_collection(net,
low_voltage_buses,
size=90,
color=(1, 0, 0),
zorder=11)
plot.draw_collections([lc, lcl, bc, bch], figsize=(8, 6))
im = plt.imread("")
plt.savefig('test', dpi=300)
###############################################################################
###############################################################################
# identify overvoltage
vm_max = 1.00
overvoltage_bus = net.res_bus[net.res_bus['vm_pu']>vm_max]
for i_overvoltage in overvoltage_bus.index:
overvoltage_bus_value = overvoltage_bus['vm_pu'][i_overvoltage]
overvoltage_bus_id = i_overvoltage
print(f"Bus with overvoltage:{overvoltage_bus_id}, load_percentage:{overvoltage_bus_value}")
# visualize network
colors = seaborn.color_palette()
if 1==0:
plot.simple_plot(net, show_plot=True)
if 1==0:
low_voltage_buses = net.res_bus[net.res_bus.vm_pu < 0.98].index
lc = plot.create_line_collection(net, net.line.index, color="grey", zorder=1)
bc = plot.create_bus_collection(net, net.bus.index, size=90, color=colors[0], zorder=10)
bch = plot.create_bus_collection(net, low_voltage_buses, size=90, color=colors[2], zorder=11)
plot.draw_collections([lc, bc, bch], figsize=(8, 6))
plt.show()
# OPF Part--------------------------------------------------------------
# creating virtual generators and virtual loads for OPF execution
print("OPF part. Creation of flexible sources")
# add virtual demands and generators to quantify the flexibility request
net_opf = pp.pandapowerNet(net)
flex_source_1_up = pp.create_gen(net_opf,bus4, name='Flex_1_UP', min_p_mw=0, p_mw=0, max_p_mw=100, min_q_mvar=0, max_q_mvar=200, controllable=True)
flex_source_1_down = pp.create_load(net_opf, bus4,name='Flex_1_DOWN', p_mw=0, min_p_mw=0, max_p_mw=100, min_q_mvar=0, max_q_mvar=200, controllable=True)
dummy = 1
# costs parameters for flexibility activation
# pp.create_poly_cost(net, 0, 'ext_grid', cp1_eur_per_mw=0)
import pandapower as pp
import pandapower.networks as nw
import pandapower.plotting as plot
import matplotlib.pyplot as plt
from matplotlib.pyplot import get_cmap
from matplotlib.colors import Normalize
# load the network - test case118 from MATPOWER and run power flow to retrieve results
net = nw.case118()
pp.runpp(net)
# create common colorbars and norms for the branches (lines) e.g. 20% line loading in green, 50% line loading in yellow
cmap = get_cmap('PuBu_r')
norm = Normalize(vmin=0, vmax=5)
# initialize the line and bus collections
lc = plot.create_line_collection(net, net.line.index, zorder=1, cmap=cmap, norm=norm) #, norm=norm, linewidths=2)
bc = plot.create_bus_collection(net, net.bus.index, size=0.1, zorder=2, cmap=cmap) #, norm=norm)
plot.draw_collections([lc, bc], figsize=(8,6), plot_colorbars=False)
plt.show()
# Youtube Tutorial: https://www.youtube.com/watch?v=QYDp_-TX7C4
import pandapower as pp
import pandapower.plotting as pplt
import pandapower.topology as top
import pandapower.networks as nw
import matplotlib.pyplot as plt
import seaborn as sns
net = nw.mv_oberrhein()
pplt.simple_plot(net)
mg = top.create_nxgraph(net, nogobuses=set(net.trafo.lv_bus.values) | set(net.trafo.hv_bus.values))
colors = sns.color_palette()
collections = list()
sizes = pplt.get_collection_sizes(net)
for area, color in zip(top.connected_components(mg), colors):
collections.append(pplt.create_bus_collection(net, area, color=color, size=sizes["bus"]))
line_ind = net.line.loc[:, "from_bus"].isin(area) | net.line.loc[:, "to_bus"].isin(area)
lines = net.line.loc[line_ind].index
collections.append(pplt.create_line_collection(net, lines, color=color))
collections.append(pplt.create_ext_grid_collection(net, size=sizes["ext_grid"]))
pplt.draw_collections(collections)
plt.show()