{ "cells": [ { "cell_type": "markdown", "id": "religious-curve", "metadata": {}, "source": [ "# Consumption and Generation Reference System" ] }, { "cell_type": "markdown", "id": "furnished-anger", "metadata": {}, "source": [ "This tutorial is about the effect of the sign of active and reactive power in load and sgen in pandapower. In this tutorial, the load element is used to model power consumption and the static generator element is used to model power generation. In pandapower, the convention for consumption and generation is different. This difference between consumer frame convention and generator frame convention will be demonstrated here." ] }, { "cell_type": "markdown", "id": "lovely-manhattan", "metadata": {}, "source": [ "![reference_system](pics/reference_system.png)\n" ] }, { "cell_type": "markdown", "id": "considerable-holiday", "metadata": {}, "source": [ "![](l.png)" ] }, { "cell_type": "markdown", "id": "working-thumb", "metadata": {}, "source": [ "In regard to reactive power, there are 2 states for the 4 quadrants of each frame convention: under-excited and over-excited (see figure above).\n", "\n", "In the Consumer Frame Convention, which is used for load-like elements (load, shunt, ward, xward, storage), the term ‘under-excited’ is used to indicate that the load is in I and II quadrants and is absorbing reactive power (decreases voltage) and the term ‘over-excited’ is used to indicate that the load is in the III and IV quadrants and is injecting reactive power (increases voltage).\n", "\n", "In the Generator Frame Convention, which is used for generator-like elements (gen, sgen, ext_grid), the term ‘over-excited’ is used to indicate the generator is in the I and II quadrants and is injecting reactive power (increases voltage), and the term ‘under-excited’ is used to indicate the generator is in III and IV quadrants and is absorbing reactive power (decreases voltage)." ] }, { "cell_type": "markdown", "id": "immune-evans", "metadata": {}, "source": [ "We show the differences between the reference systems with the following example." ] }, { "cell_type": "code", "execution_count": 1, "id": "understood-fellowship", "metadata": {}, "outputs": [], "source": [ "import pandapower as pp\n", "import pandas as pd\n", "import numpy as np\n", "import seaborn as sn" ] }, { "cell_type": "code", "execution_count": 2, "id": "fatty-proposal", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "This pandapower network includes the following parameter tables:\n", " - bus (2 elements)\n", " - load (1 element)\n", " - sgen (1 element)\n", " - ext_grid (1 element)\n", " - line (1 element)" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "net=pp.create_empty_network()\n", "bus0 = pp.create_bus(net, name=\"Bus 0\", vn_kv=110, type=\"b\")\n", "bus1 = pp.create_bus(net, name=\"Bus 1\", vn_kv=110, type=\"b\")\n", "line0 = pp.create_line(net, bus0, bus1, length_km=50, std_type=\"70-AL1/11-ST1A 110.0\", name=\"Line 1\")\n", "pp.create_sgen(net, bus1, p_mw=0, q_mvar=0, name=\"static generator\")\n", "pp.create_ext_grid(net, bus0, vm_pu=1.02, va_degree=50)\n", "pp.create_load(net, bus1, p_mw=0, q_mvar=0, name=\"load i\")\n", "net" ] }, { "cell_type": "code", "execution_count": 3, "id": "honey-serbia", "metadata": {}, "outputs": [], "source": [ "df=pd.DataFrame(columns=['element', 'p_mw', 'q_mvar', 'vm_pu', 'p_from_mw', 'p_to_mw'])" ] }, { "cell_type": "markdown", "id": "suspended-coffee", "metadata": {}, "source": [ "We will take three variations of p_mw (0, 50, -50) and three variations of q_mvar (0, 25, -25) for both load and sgen to analyze the output of the voltages." ] }, { "cell_type": "code", "execution_count": 4, "id": "weird-argument", "metadata": {}, "outputs": [], "source": [ "i=0\n", "for element in ('load', 'sgen'):\n", " for x in [0, 50, -50]:\n", " for y in [0, 25, -25]:\n", " net[element].loc[0,['p_mw', 'q_mvar']] = x, y\n", " pp.runpp(net)\n", " df.loc[i, 'element'] = element\n", " df.loc[i, ['p_mw', 'q_mvar']] = x,y\n", " df.loc[i, 'vm_pu'] = net.res_bus.vm_pu.at[bus1]\n", " df.loc[i, 'p_from_mw'] = net.res_line.p_from_mw.at[line0]\n", " df.loc[i, 'p_to_mw'] = net.res_line.p_to_mw.at[line0]\n", " i += 1\n", " net[element].loc[0, ['p_mw', 'q_mvar']] = 0, 0" ] }, { "cell_type": "code", "execution_count": 5, "id": "acceptable-appointment", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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elementp_mwq_mvarvm_pup_from_mwp_to_mw
0load001.0215150.0011350.0
1load0250.9727671.060615-0.0
2load0-251.0644081.011292-0.0
3load5000.92386155.002097-50.0
4load50250.86758757.021399-50.0
5load50-250.97163855.720967-50.0
6load-5001.096104-46.44580750.0
7load-50251.050547-45.23231350.0
8load-50-251.136787-45.8015250.0
9sgen001.0215150.0011350.0
10sgen0251.0644081.011292-0.0
11sgen0-250.9727671.060615-0.0
12sgen5001.096104-46.44580750.0
13sgen50251.136787-45.8015250.0
14sgen50-251.050547-45.23231350.0
15sgen-5000.92386155.002097-50.0
16sgen-50250.97163855.720967-50.0
17sgen-50-250.86758757.021399-50.0
\n", "
" ], "text/plain": [ " element p_mw q_mvar vm_pu p_from_mw p_to_mw\n", "0 load 0 0 1.021515 0.001135 0.0\n", "1 load 0 25 0.972767 1.060615 -0.0\n", "2 load 0 -25 1.064408 1.011292 -0.0\n", "3 load 50 0 0.923861 55.002097 -50.0\n", "4 load 50 25 0.867587 57.021399 -50.0\n", "5 load 50 -25 0.971638 55.720967 -50.0\n", "6 load -50 0 1.096104 -46.445807 50.0\n", "7 load -50 25 1.050547 -45.232313 50.0\n", "8 load -50 -25 1.136787 -45.80152 50.0\n", "9 sgen 0 0 1.021515 0.001135 0.0\n", "10 sgen 0 25 1.064408 1.011292 -0.0\n", "11 sgen 0 -25 0.972767 1.060615 -0.0\n", "12 sgen 50 0 1.096104 -46.445807 50.0\n", "13 sgen 50 25 1.136787 -45.80152 50.0\n", "14 sgen 50 -25 1.050547 -45.232313 50.0\n", "15 sgen -50 0 0.923861 55.002097 -50.0\n", "16 sgen -50 25 0.971638 55.720967 -50.0\n", "17 sgen -50 -25 0.867587 57.021399 -50.0" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "markdown", "id": "empty-thursday", "metadata": {}, "source": [ "If you look at the 4th index, you will see both the active and reactive power of the load are positive and the voltage has been reduced. This is a result of consumption of P and Q in the under-excited state. In the 5th index the active power is positive but the reactive power is negative and as the result, the voltage does not drop as much as in the case of index 4." ] }, { "cell_type": "markdown", "id": "scheduled-gibson", "metadata": {}, "source": [ "Now we will see the plots for both the elements where the reference systems can be compared and the vm_pu values are shown for different combinations of active and reactive power." ] }, { "cell_type": "markdown", "id": "ruled-specific", "metadata": {}, "source": [ "Notice that, in the plot for the load element, when the sign of reactive power is negative, the reactive power is injected, which increases voltage. And when the reactive power is positive, the voltage drops because the reactive power is absorbed. The opposite effect can be seen for sgen elements." ] }, { "cell_type": "code", "execution_count": 6, "id": "potential-worker", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.patches as mpatches\n", "import matplotlib.pyplot as plt\n", "g=sn.relplot(x=\"p_mw\", \n", " y=\"q_mvar\",\n", " size=\"vm_pu\",\n", " col=\"element\",\n", " sizes=(500,500),\n", " palette=\"viridis\",\n", " hue=\"vm_pu\",\n", " data=df, alpha=1, zorder=10)\n", "g.set(xlim=(-60,60),ylim=(-60,60))\n", "\n", "texts =[['Under-excited (consumes reactive power, decreases voltage)', 'Over-excited (injects reactive power, increases voltage)'],\n", " ['Over-excited (injects reactive power, increases voltage)', 'Under-excited (consumes reactive power, decreases voltage)']]\n", " \n", "for i,(ax, text) in enumerate(zip(g.axes[0], texts)):\n", " # Move left y-axis and bottom x-axis to centre, passing through (0,0)\n", " ax.spines['left'].set_position('center')\n", " ax.spines['bottom'].set_position('center')\n", " \n", " ax.xaxis.labelpad = 160\n", " ax.yaxis.labelpad = 160\n", " ax.grid()\n", " ax.text(0,50, text[0], bbox={'facecolor': 'lightgrey', 'pad': 10}, horizontalalignment='center', zorder=10)\n", " ax.text(0,-50, text[1], bbox={'facecolor': 'lightgrey', 'pad': 10}, horizontalalignment='center', zorder=10)\n", " \n", " rect=mpatches.Rectangle((0,-25),50,50, alpha=0.1,facecolor=\"blue\")\n", " ax.add_patch(rect)\n", " \n", "\n", " # add text with text() function in matplotlib\n", " ax.text(10, 10,['P consumption','P generation'][i],fontsize=12)\n", "\n", "\n", " \n", " " ] }, { "cell_type": "code", "execution_count": null, "id": "greatest-impossible", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.9.13" } }, "nbformat": 4, "nbformat_minor": 5 }