{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Plotting Pandapower Networks using Plotly\n", "This tutorial shows you how to make interactive plots of pandapower networks using plotly (https://plot.ly/python/).\n", "The best way to get started is to get familiar with 3 built-in plots that correspond to:\n", "* a simple plot of a network (respect switch statuses by default)\n", "* voltage-levels plot - colores and labels network according to voltage levels\n", "* Power Flow results - a colormap plot where buses are colored according to voltage magnitudes and branches according to line/transformer loading.\n", "\n", "The following sample plots are with mv_oberrhein network from the pandapower.networks package:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from pandapower.plotting.plotly import simple_plotly\n", "from pandapower.networks import mv_oberrhein\n", "from pandapower import runpp\n", "net = mv_oberrhein()\n", "runpp(net)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Simple plotting\n", "A simple network plot wich labels as separate trace all network buses, lines, transformers and external grid.\n", "Try some of the fancy plotly features from the upper-right corner:\n", "* zooming,\n", "* hoover tool (position cursor on the bus/line/trafo to get basic info),\n", "* selecting, \n", "* click on the legend to hide-show any of the legened elements," ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "simple_plotly(net)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Voltage levels\n", "Plots a network colored and layered according to voltage levels." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from pandapower.plotting.plotly import vlevel_plotly\n", "vlevel_plotly(net)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from pandapower.networks import create_cigre_network_hv\n", "net = create_cigre_network_hv()\n", "runpp(net)\n", "vlevel_plotly(net)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Power Flow Results\n", "Results from `res_bus`, `res_line` and `res_trafo` can be effectively displayed using `pf_res_plolty`.\n", "Buses colored according to resulting voltage magnitude using colormap in range $[0.9,1.1]$. \n", "Lines and trafos are colored according to resulting loading using colormap in range $[0,100]$. \n", "Positioning a cursor over a bus or line-breaks shows more details about each element." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from pandapower.plotting.plotly import pf_res_plotly\n", "pf_res_plotly(net)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## General Plotting features\n", "Interactive plots are built to share some general plotting features with static plots using [matplotlib](https://github.com/e2nIEE/pandapower/blob/master/tutorials/plotting_basic.ipynb). " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plots without geodata available" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "net = mv_oberrhein()\n", "runpp(net)\n", "\n", "# delete the geocoordinates\n", "net.bus_geodata.drop(net.bus_geodata.index, inplace=True)\n", "net.line_geodata.drop(net.line_geodata.index, inplace=True)\n", "\n", "simple_plotly(net)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Figure size and aspect ratio\n", "**Aspect ratio** (`aspectratio`) - default aspect ratio of a figure is set to `'auto'` which means keeping aspect ratio proportional to geodata. If `aspectratio=False` figure will be stretch according to window size." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "net.bus_geodata.drop(net.bus_geodata.index, inplace=True)\n", "net.line_geodata.drop(net.line_geodata.index, inplace=True)\n", "pf_res_plotly(net, aspectratio=(1.3,1))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Figure Size** (`figsize`) is by default set to 1 and it is used only to multiply total plot size, thus real figure size `figsize=aspectratio*figsize`" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "net = mv_oberrhein()\n", "simple_plotly(net, aspectratio=(2,1), figsize=0.5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "More tutorials about interactive plots using ploltly:\n", "\n", "* [custom interactive plots](http://nbviewer.jupyter.org/github/e2nIEE/pandapower/blob/develop/tutorials/plotly_traces.ipynb)\n", "* [interactive plots on maps](http://nbviewer.jupyter.org/github/e2nIEE/pandapower/blob/develop/tutorials/plotly_maps.ipynb)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.2" } }, "nbformat": 4, "nbformat_minor": 2 }