__copyright__ = "Reiner Lemoine Institut gGmbH"
__license__ = "GNU Affero General Public License Version 3 (AGPL-3.0)"
__url__ = "https://github.com/openego/eDisGo/blob/master/LICENSE"
__author__ = "mltja"

eDisGo plot example with plotly

Setup

Import packages

import logging

logging.basicConfig(level=logging.CRITICAL)

import copy
import os
import time

import requests

from edisgo import EDisGo
from edisgo.tools.plots import plot_dash, plot_plotly

Download example grid

def download_ding0_example_grid():

    # create directories to save ding0 example grid into
    ding0_example_grid_path = os.path.join(
        os.path.expanduser("~"), ".edisgo", "ding0_test_network"
    )
    os.makedirs(ding0_example_grid_path, exist_ok=True)

    # download files
    filenames = [
        "buses",
        "generators",
        "lines",
        "loads",
        "network",
        "switches",
        "transformers",
        "transformers_hvmv",
    ]

    for file in filenames:
        req = requests.get(
            f"https://raw.githubusercontent.com/openego/eDisGo/dev/tests/data/ding0_test_network_1/{file}.csv"
        )
        filename = os.path.join(ding0_example_grid_path, f"{file}.csv")
        with open(filename, "wb") as fout:
            fout.write(req.content)


download_ding0_example_grid()

Create edisgo objects

ding0_grid = os.path.join(os.path.expanduser("~"), ".edisgo", "ding0_test_network")

edisgo_root = EDisGo(ding0_grid=ding0_grid)
edisgo_root.set_time_series_worst_case_analysis()

edisgo_analyzed = copy.deepcopy(edisgo_root)
edisgo_analyzed.analyze();

edisgo_reinforced = copy.deepcopy(edisgo_root)
edisgo_reinforced.reinforce();

Plots

plot_plotly function

In the following different plotting options are shown. For more information on different plotting options see API docstring.

Hovering over nodes and lines shows some information on them.

Plotting relative loading and voltage deviation, with map in the background.

Be aware that the used grid is a test grid with random geolocations. To see the plotting on a map with a ding0 grid with actual geolocations you can change the downloaded grid in the function download_ding0_example_grid above to ‘ding0_test_network_3’ and import the grid as follows:

edisgo_root = EDisGo(ding0_grid=ding0_grid, legacy_ding0_grids=False)

fig = plot_plotly(
    edisgo_obj=edisgo_analyzed,
    grid=None,
    line_color="relative_loading",
    node_color="voltage_deviation",
    line_result_selection="max",
    node_result_selection="max",
    selected_timesteps=None,
    pseudo_coordinates=False,
    plot_map=True,
    node_selection=False,
)

fig.show()

Plotting relative loading and voltage deviation, with time step selection

plot_plotly(
    edisgo_obj=edisgo_analyzed,
    grid=None,
    line_color="relative_loading",
    node_color="voltage_deviation",
    line_result_selection="max",
    node_result_selection="max",
    selected_timesteps=[
        "1970-01-01 00:00:00",
        "1970-01-01 01:00:00",
    ],
    pseudo_coordinates=False,
    node_selection=False,
)

Plotting loading and voltage deviation, with pseudo coordinates

plot_plotly(
    edisgo_obj=edisgo_analyzed,
    grid=None,
    line_color="loading",
    node_color="voltage_deviation",
    line_result_selection="max",
    node_result_selection="max",
    selected_timesteps="1970-01-01 03:00:00",
    pseudo_coordinates=True,
    node_selection=False,
)

Plotting reinforced lines, node adjacencies and a node selection

plot_plotly(
    edisgo_obj=edisgo_reinforced,
    grid=None,
    line_color="reinforce",
    node_color="adjacencies",
    line_result_selection="max",
    node_result_selection="max",
    selected_timesteps=None,
    pseudo_coordinates=False,
    node_selection=[
        "Bus_MVStation_1",
        "Bus_BranchTee_MVGrid_1_5",
        "Bus_BranchTee_MVGrid_1_10",
        "Bus_GeneratorFluctuating_4",
        "Bus_BranchTee_MVGrid_1_11",
        "Bus_GeneratorFluctuating_3",
        "BusBar_MVGrid_1_LVGrid_4_MV",
    ],
)

Dash plot app which calls plot_plotly

One edisgo object creates one large plot. Two or more edisgo objects create two adjacent plots, where the objects to be plotted are selected in the dropdown menu.

One interactive plot

plot_dash(edisgo_objects=edisgo_analyzed)
time.sleep(2)

Two interactives plots side by side

plot_dash(
    edisgo_objects={
        "edisgo_analyzed": edisgo_analyzed,
        "edisgo_reinforced": edisgo_reinforced,
    }
)
time.sleep(2)

Two interactives plots side by side with 3 EDisGo objects

Choose your edisgo objects in the drop down menu.

plot_dash(
    edisgo_objects={
        "edisgo_root": edisgo_root,
        "edisgo_analyzed": edisgo_analyzed,
        "edisgo_reinforced": edisgo_reinforced,
    },
    height=1000,
)