{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# IEEE European Low Voltage Test Feeder: \n", "\n", "http://sites.ieee.org/pes-testfeeders/resources/\n", "\n", "The current IEEE test cases are focused on North American style systems; however it is common outside of North America to see low-voltage distribution systems, both radial and meshed. It is important to make sure that tools support both dominant styles of distribution system configuration. This test case seeks to fill a benchmark gap by presenting a number of common low-voltage configurations. This circuit also introduces quasi-static time series simulations.\n", "\n", "IEEE European LV network is a generic 0.416 kV network serviced by one 0.8 MVA MV/LV transformer and a 11kV external grid. The network supplies 906 LV buses and 55 1-PH loads.\n", "\n", "\n", "# Time Series data from Benchmark dataset\n", "In this example the time series data from benchmark is used to perform a time series load flow analysis\n", "in pandapower\n", "\n", "The network data from csv is used to create Powerfactory and pandapower networks.\n", "\n", "The Sum total of power and maximum voltage is plotted with respect to 1440 time steps( 1 min interval) during the day:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import numpy as np\n", "import pandas as pd\n", "import tempfile\n", "import pandapower as pp\n", "from pandapower.control import ConstControl\n", "from pandapower.timeseries import DFData\n", "from pandapower.timeseries import OutputWriter\n", "from pandapower.timeseries.run_time_series import run_timeseries\n", "from pandapower.networks import ieee_european_lv_asymmetric\n", "from pandapower import pp_dir\n", "parent = os.path.join(pp_dir,'test','test_files')\n", "path = os.path.join(parent, \"European_LV_CSV\")\n", "load_path = os.path.join(path, \"Load_Profiles\")\n", "def remove_comments(f):\n", " '''Pass comments'''\n", " start=f.seek(0)\n", " for index in range(5):\n", " start=f.tell()\n", " if f.readline().startswith('#'):\n", " continue\n", " else:\n", " break \n", " f.seek(start)\n", " return f\n", "\n", "load_csv = os.path.join(path, \"Loads.csv\")\n", "\n", "with open (load_csv,'r') as f:\n", " f = remove_comments(f)\n", " loads = pd.read_csv(f)\n", " f.close()\n", "\n", "load_shapes = os.path.join(path, \"LoadShapes.csv\") \n", " \n", "with open (load_shapes,'r') as f:\n", " f = remove_comments(f)\n", " loadshapes = pd.read_csv(f)\n", " f.close()" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "hp.pandapower.plotting.plotting_toolbox - INFO: Interpreting color (0.12156862745098039, 0.4666666666666667, 0.7058823529411765) as rgb or rgba!\n", "hp.pandapower.plotting.plotting_toolbox - WARNING: The number of given colors (1) is smaller than the number of nodes (907) to draw! The colors will be repeated to fit.\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandapower.plotting as plot\n", "net =ieee_european_lv_asymmetric('on_peak_566')\n", "%matplotlib inline\n", "import numpy as np\n", "try:\n", " import seaborn\n", " colors = seaborn.color_palette()\n", "except:\n", " colors = [\"b\", \"g\", \"r\", \"c\", \"y\"]\n", "\n", "bc = plot.create_bus_collection(net, net.bus.index, size=.2, color=colors[0], zorder=10)\n", "tlc, tpc = plot.create_trafo_collection(net, net.trafo.index, color=\"c\",size =1.5 )\n", "lcd = plot.create_line_collection(net, net.line.index, color=\"grey\", linewidths=0.5, use_bus_geodata=True)\n", "sc = plot.create_bus_collection(net, net.ext_grid.bus.values, patch_type=\"rect\", size=.75, color=\"c\", zorder=11)\n", "ldA = plot.create_bus_collection(net, net.asymmetric_load.bus.values[np.where(net.asymmetric_load.p_a_mw >0)], patch_type=\"poly3\", size=.75, color=\"r\", zorder=11)\n", "ldB = plot.create_bus_collection(net, net.asymmetric_load.bus.values[np.where(net.asymmetric_load.p_b_mw >0)], patch_type=\"rect\", size=.75, color=\"y\", zorder=11)\n", "ldC = plot.create_bus_collection(net, net.asymmetric_load.bus.values[np.where(net.asymmetric_load.p_c_mw >0)], patch_type=\"circle\", size=.75, color=\"g\", zorder=11)\n", "plot.draw_collections([lcd, bc, tlc, tpc, sc,ldA,ldB,ldC], figsize=(10,7))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "- Cyan rectangle is External Grid and circle is the transformer\n", "- Red triangles, yellow rectangles and green dots represent A,B,C phase loads respectively\n", "- blue dots are buses\n", "- grey lines are power lines.\n", "\n", "\n", "# Time-series calculation\n", "\n", "Function to load time series data and perform time-series **three phase load flow**" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "def timeseries_example(output_dir):\n", " # 1. create test net\n", " net = ieee_european_lv_asymmetric('on_peak_566')\n", " pp.runpp_3ph(net)\n", " # 2. create data source for loads\n", " profiles, ds = create_data_source()\n", " # 3. create controllers (to control P values of the load and the sgen)\n", " net = create_controllers(net, ds)\n", "\n", " # time steps to be calculated. Could also be a list with non-consecutive time steps\n", " time_steps = range(0, 672)\n", " print(time_steps)\n", "\n", " # 4. the output writer with the desired results to be stored to files.\n", " ow = create_output_writer(net, time_steps, output_dir)\n", "\n", " # 5. the main time series function\n", " run_timeseries(net, time_steps, output_writer=ow, run=pp.runpp_3ph, continue_on_divergence=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Data source\n", "Data taken from csv data provided in IEEE benchmark grid" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "def create_data_source():\n", " profiles = pd.DataFrame()\n", " for loadprofile,file in (loadshapes[['Name','File']].values):\n", " file_path = os.path.join(load_path, file)\n", " profiles[loadprofile] = pd.read_csv(file_path).mult.values * 1e-3 \n", " profiles[loadprofile+'_Q'] = profiles[loadprofile] * np.tan(\n", " np.arccos(float(loads[loads.Yearly==loadprofile].PF.values))) \n", " ds = DFData(profiles)\n", " return profiles, ds" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Time series controller\n", "P, Q values entered using P and power factor(cos_phi) data" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "def create_controllers(net, ds):\n", " ConstControl(net, element='asymmetric_load', variable='p_a_mw', element_index=loads[loads['phases']=='A'].index,\n", " data_source=ds, profile_name=loads[loads['phases']=='A'].Yearly)\n", " ConstControl(net, element='asymmetric_load', variable='q_a_mvar', element_index=loads[loads['phases']=='A'].index,\n", " data_source=ds, profile_name=loads[loads['phases']=='A'].Yearly+'_Q')\n", " \n", " ConstControl(net, element='asymmetric_load', variable='p_b_mw', element_index=loads[loads['phases']=='B'].index,\n", " data_source=ds, profile_name=loads[loads['phases']=='B'].Yearly)\n", " ConstControl(net, element='asymmetric_load', variable='q_b_mvar', element_index=loads[loads['phases']=='B'].index,\n", " data_source=ds, profile_name=loads[loads['phases']=='B'].Yearly+'_Q')\n", " \n", " ConstControl(net, element='asymmetric_load', variable='p_c_mw', element_index=loads[loads['phases']=='C'].index,\n", " data_source=ds, profile_name=loads[loads['phases']=='C'].Yearly)\n", " ConstControl(net, element='asymmetric_load', variable='q_c_mvar', element_index=loads[loads['phases']=='C'].index,\n", " data_source=ds, profile_name=loads[loads['phases']=='C'].Yearly+'_Q') \n", " return net\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Format output\n", "- Maximum bus voltage magnitude for each time step\n", "- Aggregated Sum of P & Q values for each time step" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "def create_output_writer(net, time_steps, output_dir):\n", " ow = OutputWriter(net, time_steps, output_path=output_dir, output_file_type=\".json\")\n", " ow.log_variable('res_trafo_3ph', 'p_a_lv_mw', index=net.trafo.index)\n", " ow.log_variable('res_trafo_3ph', 'p_b_lv_mw', index=net.trafo.index)\n", " ow.log_variable('res_trafo_3ph', 'p_c_lv_mw', index=net.trafo.index)\n", " ow.log_variable('res_trafo_3ph', 'q_a_lv_mvar', index=net.trafo.index)\n", " ow.log_variable('res_trafo_3ph', 'q_b_lv_mvar', index=net.trafo.index)\n", " ow.log_variable('res_trafo_3ph', 'q_c_lv_mvar', index=net.trafo.index)\n", " ow.log_variable('res_bus_3ph', 'vm_a_pu', index=[34]) # Load 1 Phase A \n", " ow.log_variable('res_bus_3ph', 'vm_b_pu', index=[899]) # Load 53 Phase B\n", " ow.log_variable('res_bus_3ph', 'vm_c_pu', index=[614]) # Load 32 Phase C\n", " ow.log_variable('res_bus_3ph', 'va_a_degree', index=[34]) # Load 1 Phase A \n", " ow.log_variable('res_bus_3ph', 'va_b_degree', index=[899]) # Load 53 Phase B\n", " ow.log_variable('res_bus_3ph', 'va_c_degree', index=[614]) # Load 32 Phase C\n", " return ow" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Main Function" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Results can be found in your local temp folder: C:\\Users\\RBOLGA~1\\AppData\\Local\\Temp\\time_series_example\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\rbolgaryn\\AppData\\Local\\Temp\\ipykernel_27344\\1411155948.py:5: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " profiles[loadprofile] = pd.read_csv(file_path).mult.values*1e-3\n", "C:\\Users\\rbolgaryn\\AppData\\Local\\Temp\\ipykernel_27344\\1411155948.py:6: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " profiles[loadprofile+'_Q'] = profiles[loadprofile] * np.tan(\n", "C:\\Users\\rbolgaryn\\AppData\\Local\\Temp\\ipykernel_27344\\1411155948.py:5: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " profiles[loadprofile] = pd.read_csv(file_path).mult.values*1e-3\n", "C:\\Users\\rbolgaryn\\AppData\\Local\\Temp\\ipykernel_27344\\1411155948.py:6: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " profiles[loadprofile+'_Q'] = profiles[loadprofile] * np.tan(\n", "C:\\Users\\rbolgaryn\\AppData\\Local\\Temp\\ipykernel_27344\\1411155948.py:5: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " profiles[loadprofile] = pd.read_csv(file_path).mult.values*1e-3\n", "C:\\Users\\rbolgaryn\\AppData\\Local\\Temp\\ipykernel_27344\\1411155948.py:6: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " profiles[loadprofile+'_Q'] = profiles[loadprofile] * np.tan(\n", "C:\\Users\\rbolgaryn\\AppData\\Local\\Temp\\ipykernel_27344\\1411155948.py:5: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " profiles[loadprofile] = pd.read_csv(file_path).mult.values*1e-3\n", "C:\\Users\\rbolgaryn\\AppData\\Local\\Temp\\ipykernel_27344\\1411155948.py:6: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " profiles[loadprofile+'_Q'] = profiles[loadprofile] * np.tan(\n", "C:\\Users\\rbolgaryn\\AppData\\Local\\Temp\\ipykernel_27344\\1411155948.py:5: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " profiles[loadprofile] = pd.read_csv(file_path).mult.values*1e-3\n", "C:\\Users\\rbolgaryn\\AppData\\Local\\Temp\\ipykernel_27344\\1411155948.py:6: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " profiles[loadprofile+'_Q'] = profiles[loadprofile] * np.tan(\n", "hp.pandapower.timeseries.run_time_series - WARNING: deprecated: output_writer should not be given to run_timeseries(). This overwrites the stored one in net.output_writer.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "range(0, 672)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|████████████████████████████████████████████████████████████████████████████████| 672/672 [01:12<00:00, 9.30it/s]\n" ] } ], "source": [ "output_dir = os.path.join(tempfile.gettempdir(), \"time_series_example\")\n", "print(\"Results can be found in your local temp folder: {}\".format(output_dir))\n", "if not os.path.exists(output_dir):\n", " os.mkdir(output_dir)\n", "timeseries_example(output_dir)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Importing data for plotting\n", "A pandas dataframe is made from the output '.json' file\n", "This dataframe will be used for plotting results using matplotlib\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "output_dir = os.path.join(tempfile.gettempdir(), \"time_series_example\")\n", "# Power Values from secondary of the transformer\n", "PA = os.path.join(output_dir,'res_trafo_3ph','p_a_lv_mw.json')\n", "PB = os.path.join(output_dir,'res_trafo_3ph','p_b_lv_mw.json')\n", "PC = os.path.join(output_dir,'res_trafo_3ph','p_c_lv_mw.json')\n", "QA = os.path.join(output_dir,'res_trafo_3ph','q_a_lv_mvar.json')\n", "QB = os.path.join(output_dir,'res_trafo_3ph','q_b_lv_mvar.json')\n", "QC = os.path.join(output_dir,'res_trafo_3ph','q_c_lv_mvar.json')\n", "\n", "#pandapower Results\n", "df_pp = pd.read_json(PA)*-1e3\n", "df_pp['PB'] = pd.read_json(PB)*-1e3\n", "df_pp['PC'] = pd.read_json(PC)*-1e3\n", "df_pp['P_SUM'] = df_pp.sum(axis=1)\n", "df_pp = df_pp.rename(columns={0:'PA'}) \n", "\n", "df_pq = pd.read_json(QA)*-1e3\n", "df_pq['QB'] = pd.read_json(QB)*-1e3\n", "df_pq['QC'] = pd.read_json(QC)*-1e3\n", "df_pq = df_pq.rename(columns={0:'QA'})\n", "df_pp['Q_SUM'] = df_pq.sum(axis=1)\n", "\n", "\n", "#The magnitude of voltage at LOAD1 (phase A), LOAD32 (phase C), and LOAD53 (phase B) over the one-day period are shown \n", "pp_va = os.path.join(output_dir,'res_bus_3ph','vm_a_pu.json')\n", "pp_vb = os.path.join(output_dir,'res_bus_3ph','vm_b_pu.json')\n", "pp_vc = os.path.join(output_dir,'res_bus_3ph','vm_c_pu.json')\n", "\n", "#pandapower Results\n", "df_pp_v = pd.read_json(pp_va)*(416/np.sqrt(3))\n", "df_pp_v['VB'] = pd.read_json(pp_vb)*(416/np.sqrt(3))\n", "df_pp_v['VC'] = pd.read_json(pp_vc)*(416/np.sqrt(3))\n", "df_pp_v= df_pp_v.rename(columns={34: \"VA\"})\n", "\n", "# This is required since json makes keys as string type, the index order is like 1, 10, 100 ,...\n", "df_pp_v.index = df_pp_v.index.astype(np.int64)\n", "df_pp_v = df_pp_v.sort_index()\n", "\n", "df_pp.index = df_pp.index.astype(np.int64)\n", "df_pp = df_pp.sort_index()\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Plotting Results\n", "\n", "The following data is generated :\n", "- pandapower voltage and power (time-series values)\n", "- OpenDSS voltage and power (not executed here)\n", "- Difference between pandapower OpenDSS (time-series values)\n", "\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Load Voltages (pandapower) / V')" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "fig,ax1 = plt.subplots(1,1)\n", "df_pp_v.plot(kind='line', y=['VA','VB','VC'], ax=ax1, color=['blue','orange','green'],figsize=(10,5),legend = True)\n", "ax1.set_ylim((235,255))\n", "ax1.xaxis.set_label_text(\"time step\")\n", "ax1.yaxis.set_label_text(\"voltage mag. [Volts]\")\n", "ax1.set_title(\"Load Voltages (pandapower) / V\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# Comparison with OpenDSS Solutions\n", "\n", "**Voltage values are taken from three loads of each phase :**\n", "\n", "Load #1 Phase A\n", "\n", "Load #53 Phase B\n", "\n", "Load #32 Phase C\n", "\n", "\n", "\n", "\n", "\n", "" ] } ], "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": "3.10.6" } }, "nbformat": 4, "nbformat_minor": 2 }