From cfbe952cc7be1baa29b907b1a94b47fe71397b1b Mon Sep 17 00:00:00 2001 From: lisrte Date: Mon, 16 Dec 2024 17:25:31 +0100 Subject: [PATCH 1/9] Add dynawo simulation nordic case Signed-off-by: lisrte --- dynawo/nordic case/Network.par | 38 + dynawo/nordic case/Nordic.par | 1023 ++++++++++ dynawo/nordic case/Nordic.xiidm | 2207 +++++++++++++++++++++ dynawo/nordic case/Solver.par | 56 + dynawo/nordic case/config.yml | 10 + dynawo/nordic case/pypowsybl_dynawo.ipynb | 326 +++ 6 files changed, 3660 insertions(+) create mode 100644 dynawo/nordic case/Network.par create mode 100644 dynawo/nordic case/Nordic.par create mode 100644 dynawo/nordic case/Nordic.xiidm create mode 100644 dynawo/nordic case/Solver.par create mode 100644 dynawo/nordic case/config.yml create mode 100644 dynawo/nordic case/pypowsybl_dynawo.ipynb diff --git a/dynawo/nordic case/Network.par b/dynawo/nordic case/Network.par new file mode 100644 index 0000000..fe37dfe --- /dev/null +++ b/dynawo/nordic case/Network.par @@ -0,0 +1,38 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/dynawo/nordic case/Nordic.par b/dynawo/nordic case/Nordic.par new file mode 100644 index 0000000..424ba18 --- /dev/null +++ b/dynawo/nordic case/Nordic.par @@ -0,0 +1,1023 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/dynawo/nordic case/Nordic.xiidm b/dynawo/nordic case/Nordic.xiidm new file mode 100644 index 0000000..753b35b --- /dev/null +++ b/dynawo/nordic case/Nordic.xiidm @@ -0,0 +1,2207 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/dynawo/nordic case/Solver.par b/dynawo/nordic case/Solver.par new file mode 100644 index 0000000..88201fd --- /dev/null +++ b/dynawo/nordic case/Solver.par @@ -0,0 +1,56 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/dynawo/nordic case/config.yml b/dynawo/nordic case/config.yml new file mode 100644 index 0000000..4627340 --- /dev/null +++ b/dynawo/nordic case/config.yml @@ -0,0 +1,10 @@ +dynawo: + homeDir: /home/dynawo + +dynawo-simulation-default-parameters: + parametersFile: Nordic.par + network.parametersFile: Network.par + network.parametersId: "Network" + solver.type: SIM + solver.parametersFile: Solvers.par + solver.parametersId: "Solver" diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb new file mode 100644 index 0000000..3650fe4 --- /dev/null +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -0,0 +1,326 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Dynawo simulation - Nordic case" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "TODO - description" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1 - Dynawo install" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!curl -L $(curl -s -L -X GET https://api.github.com/repos/dynawo/dynaflow-launcher/releases/latest | grep \"DynaFlowLauncher_Linux\" | grep url | cut -d '\"' -f 4) -o DynaflowLauncher_Linux_latest.zip\n", + "!unzip DynaflowLauncher_Linux_latest.zip > /dev/null 2>&1\n", + "!./dynaflow-launcher/dynaflow-launcher.sh help" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2 - Powsybl install" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pip install pypowsybl" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!mkdir /home/jovyan/.itools/\n", + "!cp /home/jovyan/dynaflow/config.yml /home/jovyan/.itools/\n", + "!cat /home/jovyan/.itools/config.yml" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3 - Base case" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pypowsybl as pp\n", + "import pypowsybl.dynamic as dyn\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import os.path" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# Load initial situation\n", + "network = pp.network.load('Nordic.xiidm')\n", + "network.get_network_area_diagram()\n", + "report_node = pp.report.Reporter()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Add generators dynamic models" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "model_mapping = dyn.ModelMapping()\n", + "generator_mapping_df = pd.DataFrame.from_records(\n", + " index='static_id',\n", + " columns=['static_id', 'parameter_set_id', 'model_name'],\n", + " data=[('g01', 'g01', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g02', 'g02', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g03', 'g03', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g04', 'g04', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g05', 'g05', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g06', 'g06', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g07', 'g07', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g08', 'g08', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g09', 'g09', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g10', 'g10', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g11', 'g11', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g12', 'g12', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g13', 'g13', 'GeneratorSynchronousThreeWindingsPmConstVRNordic'),\n", + " ('g14', 'g14', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g15', 'g15', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g16', 'g16', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g17', 'g17', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g18', 'g18', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g19', 'g19', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g20', 'g20', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic')])\n", + "model_mapping.add_synchronous_generator(generator_mapping_df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Add node fault and disconnect line event" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "event_mapping = dyn.EventMapping()\n", + "event_mapping.add_node_fault(static_id='4032_401', start_time=1, fault_time=0.1, r_pu=0.025, x_pu=0.025)\n", + "event_mapping.add_disconnection(static_id='L4032-4044', start_time=1.1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Request curves output" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "variables_mapping = dyn.OutputVariableMapping()\n", + "variables_mapping.add_standard_model_curves('1042_131', 'Upu_value')\n", + "# equipment_names = {'1011_131', '4011_401', 'B11___21', 'BG09__11', '1012_131', '4012_401', 'B12___21', 'BG01__11', 'BG10__11',\n", + "# '1013_131', 'B13___21', 'BG02__11', '1014_131', 'BG03__11', '1021_131', 'BG04__11', '1022_131', '4022_401',\n", + "# 'B22___21', 'BG05__11', '1041_131', 'B01___21', '1042_131', 'B02___21', 'BG06__11', '1043_131', 'B03___21',\n", + "# 'BG07__11', '1044_131', '4044_401', 'B04___21', '1045_131', '4045_401', 'B05___21', '2031_221', '4031_401',\n", + "# 'B31___21', 'BG12__11', '2032_221', 'B32___21', 'BG08__11', '4021_401', 'BG11__11', '4032_401', '4041_401',\n", + "# 'B41___21', 'BG13__11', '4042_401', 'B42___21', 'BG14__11', '4043_401', 'B43___21', '4046_401', 'B46___21',\n", + "# '4047_401', 'B47___21', 'BG15__11', '4051_401', 'B51___21', 'BG16__11', '4061_401', 'B61___21', '4062_401',\n", + "# 'B62___21', 'BG17__11', '4063_401', 'B63___21', 'BG18__11', '4071_401', 'B71___21', 'BG19__11', '4072_401',\n", + "# 'B72___21', 'BG20__11'}\n", + "# for eq in equipment_names:\n", + "# variables_mapping.add_standard_model_curves(eq, 'Upu_value')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "sim = dyn.Simulation()\n", + "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175, report_node)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Display curves" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "res.curves().plot()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4 - Second simulation with tap changer blocking automation system" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "tcb_df = pd.DataFrame.from_records(\n", + " index='dynamic_model_id',\n", + " columns=['dynamic_model_id', 'parameter_set_id'],\n", + " data=[('TCB', 'TCB')])\n", + "# Transformers\n", + "tfo_ids = ['Tr11-1011', 'Tr12-1012', 'Tr13-1013', 'Tr22-1022', 'Tr1-1041', 'Tr2-1042', 'Tr3-1043', 'Tr4-1044', 'Tr5-1045', 'Tr31-2031',\n", + " 'Tr32-2032', 'Tr41-4041', 'Tr42-4042', 'Tr43-4043', 'Tr46-4046', 'Tr47-4047', 'Tr51-4051', 'Tr61-4061', 'Tr62-4062', 'Tr63-4063'\n", + " 'Tr71-4071', 'Tr72-4072']\n", + "tfo_df = pd.DataFrame.from_records(\n", + " index='dynamic_model_id',\n", + " columns=['dynamic_model_id', 'transformer_id'],\n", + " data={'dynamic_model_id': ['TCB' for tfo in tfo_ids],\n", + " 'transformer_id': tfo_ids})\n", + "# Measurement point\n", + "measurement1_df = pd.DataFrame.from_records(\n", + " index='dynamic_model_id',\n", + " columns=['dynamic_model_id', 'measurement_point_id'],\n", + " data=[('TCB', '1042_131')])\n", + "model_mapping.add_tap_changer_blocking_automation_system(df=tcb_df,\n", + " tfo_df=tfo_df,\n", + " mp1_df=measurement1_df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run second simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "variables_mapping.add_standard_model_final_state_values('1042_131', 'Upu_value')\n", + "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175, report_node)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Display final state values " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " values\n", + "variables \n", + "NETWORK_1042_131_Upu_value 0.8069\n" + ] + } + ], + "source": [ + "print(res.final_state_values())" + ] + } + ], + "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": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From bcef593cd7ab34b91dd6d7433c005a64e147374f Mon Sep 17 00:00:00 2001 From: lisrte Date: Wed, 18 Dec 2024 11:23:17 +0100 Subject: [PATCH 2/9] Edit install Signed-off-by: lisrte --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index 3650fe4..d83d04f 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -27,9 +27,9 @@ "metadata": {}, "outputs": [], "source": [ - "!curl -L $(curl -s -L -X GET https://api.github.com/repos/dynawo/dynaflow-launcher/releases/latest | grep \"DynaFlowLauncher_Linux\" | grep url | cut -d '\"' -f 4) -o DynaflowLauncher_Linux_latest.zip\n", - "!unzip DynaflowLauncher_Linux_latest.zip > /dev/null 2>&1\n", - "!./dynaflow-launcher/dynaflow-launcher.sh help" + "!curl -L $(curl -s -L -X GET https://api.github.com/repos/dynawo/dynawo/releases/latest | grep \"Dynawo_Linux\" | grep url | cut -d '\"' -f 4) -o Dynawo_Linux_latest.zip\n", + "!unzip Dynawo_Linux_latest.zip > /dev/null 2>&1\n", + "!./dynawo/dynawo.sh help" ] }, { @@ -54,9 +54,9 @@ "metadata": {}, "outputs": [], "source": [ - "!mkdir /home/jovyan/.itools/\n", - "!cp /home/jovyan/dynaflow/config.yml /home/jovyan/.itools/\n", - "!cat /home/jovyan/.itools/config.yml" + "!mkdir /home/USER/.itools/\n", + "!cp /home/USER/dynaflow/config.yml /home/USER/.itools/\n", + "!cat /home/USER/.itools/config.yml" ] }, { From a49867255fb83364905fc53e77d264d96ba634e6 Mon Sep 17 00:00:00 2001 From: lisrte Date: Wed, 18 Dec 2024 15:51:03 +0100 Subject: [PATCH 3/9] Update installation instruction Use network variant Display TCB simulation curve Signed-off-by: lisrte --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 4308 ++++++++++++++++++++- 1 file changed, 4273 insertions(+), 35 deletions(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index d83d04f..d8d2f80 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -55,7 +55,7 @@ "outputs": [], "source": [ "!mkdir /home/USER/.itools/\n", - "!cp /home/USER/dynaflow/config.yml /home/USER/.itools/\n", + "!cp /home/USER/dynawo/nordic case/config.yml /home/USER/.itools/\n", "!cat /home/USER/.itools/config.yml" ] }, @@ -83,12 +83,4256 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " 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+ " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " -300\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " -2,138\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " 2,138\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " 2,000\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " -2,000\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
1011_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
138.0 kV / 57.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1012_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
138.2 kV / 61.1°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1013_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
137.1 kV / 65.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1014_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
137.9 kV / 68.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1021_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
134.0 kV / 66.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1022_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
136.7 kV / 45.2°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1041_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
131.6 kV / -17.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1042_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
131.9 kV / -3.2°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1043_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
133.6 kV / -12.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1044_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
130.9 kV / -3.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1045_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
131.4 kV / -7.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
2031_220
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
226.1 kV / 27.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
2032_220
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
235.3 kV / 40.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4011_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
409.0 kV / 56.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4012_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
409.4 kV / 58.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4021_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
419.5 kV / 28.1°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4022_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
397.9 kV / 43.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4031_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
414.7 kV / 24.8°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4032_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
419.5 kV / 19.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4041_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
420.2 kV / 9.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4042_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
417.2 kV / 6.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4043_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
414.8 kV / 0.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4044_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
415.8 kV / 0.0°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4045_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
421.4 kV / -4.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4046_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
414.3 kV / 0.1°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4047_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
423.6 kV / 4.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4051_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
426.4 kV / -6.8°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4061_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
415.5 kV / 6.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4062_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
422.4 kV / 9.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4063_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
421.4 kV / 13.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4071_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
419.4 kV / 59.2°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4072_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
423.6 kV / 60.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B01___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -20.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B02___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -6.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B03___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
19.9 kV / -15.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B04___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -6.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B05___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
19.9 kV / -10.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B11___20
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\n", + "
20.1 kV / 54.8°
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\n", + " \n", + " \n", + "
\n", + "
B12___20
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\n", + "
20.0 kV / 58.3°
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\n", + " \n", + " \n", + "
\n", + "
B13___20
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\n", + "
19.9 kV / 62.6°
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\n", + "
B22___20
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\n", + "
19.9 kV / 42.3°
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\n", + "
B31___20
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\n", + "
20.1 kV / 24.8°
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\n", + "
B32___20
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\n", + "
20.0 kV / 37.5°
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\n", + " \n", + " \n", + "
\n", + "
B41___20
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\n", + "
19.9 kV / 7.1°
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\n", + " \n", + " \n", + "
\n", + "
B42___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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\n", + "
19.9 kV / 4.0°
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\n", + " \n", + " \n", + "
\n", + "
B43___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -2.1°
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\n", + " \n", + " \n", + "
\n", + "
B46___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -2.7°
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\n", + " \n", + " \n", + "
\n", + "
B47___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
19.9 kV / 1.9°
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\n", + " \n", + " \n", + "
\n", + "
B51___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -9.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B61___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
19.9 kV / 3.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B62___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / 7.0°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B63___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / 10.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B71___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.1 kV / 56.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B72___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
19.9 kV / 57.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG01__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
16.0 kV / 66.8°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG02__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.8 kV / 69.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG03__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.9 kV / 74.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG04__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.5 kV / 72.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG05__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.4 kV / 51.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG06__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.1 kV / 4.8°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG07__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.2 kV / -4.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG08__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.7 kV / 47.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG09__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.0 kV / 62.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG10__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.2 kV / 65.2°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG11__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.3 kV / 35.2°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG12__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.3 kV / 32.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG13__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.3 kV / 9.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG14__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.7 kV / 14.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG15__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.7 kV / 12.0°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG16__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.8 kV / 0.1°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG17__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.1 kV / 17.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG18__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.5 kV / 20.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG19__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.5 kV / 64.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG20__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.3 kV / 64.2°
\n", + "
\n", + " \n", + " \n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Load initial situation\n", "network = pp.network.load('Nordic.xiidm')\n", - "network.get_network_area_diagram()\n", - "report_node = pp.report.Reporter()" + "network.clone_variant('InitialState', 'BaseCase')\n", + "network.set_working_variant('BaseCase')\n", + "network.get_network_area_diagram()" ] }, { @@ -163,18 +4407,7 @@ "outputs": [], "source": [ "variables_mapping = dyn.OutputVariableMapping()\n", - "variables_mapping.add_standard_model_curves('1042_131', 'Upu_value')\n", - "# equipment_names = {'1011_131', '4011_401', 'B11___21', 'BG09__11', '1012_131', '4012_401', 'B12___21', 'BG01__11', 'BG10__11',\n", - "# '1013_131', 'B13___21', 'BG02__11', '1014_131', 'BG03__11', '1021_131', 'BG04__11', '1022_131', '4022_401',\n", - "# 'B22___21', 'BG05__11', '1041_131', 'B01___21', '1042_131', 'B02___21', 'BG06__11', '1043_131', 'B03___21',\n", - "# 'BG07__11', '1044_131', '4044_401', 'B04___21', '1045_131', '4045_401', 'B05___21', '2031_221', '4031_401',\n", - "# 'B31___21', 'BG12__11', '2032_221', 'B32___21', 'BG08__11', '4021_401', 'BG11__11', '4032_401', '4041_401',\n", - "# 'B41___21', 'BG13__11', '4042_401', 'B42___21', 'BG14__11', '4043_401', 'B43___21', '4046_401', 'B46___21',\n", - "# '4047_401', 'B47___21', 'BG15__11', '4051_401', 'B51___21', 'BG16__11', '4061_401', 'B61___21', '4062_401',\n", - "# 'B62___21', 'BG17__11', '4063_401', 'B63___21', 'BG18__11', '4071_401', 'B71___21', 'BG19__11', '4072_401',\n", - "# 'B72___21', 'BG20__11'}\n", - "# for eq in equipment_names:\n", - "# variables_mapping.add_standard_model_curves(eq, 'Upu_value')" + "variables_mapping.add_standard_model_curves('1042_131', 'U_value')" ] }, { @@ -191,24 +4424,24 @@ "outputs": [], "source": [ "sim = dyn.Simulation()\n", - "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175, report_node)" + "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Display curves" + "Display curve" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -218,7 +4451,8 @@ } ], "source": [ - "res.curves().plot()\n", + "c = res.curves().plot()\n", + "c.set_xlabel('Time (ms)')\n", "plt.show()" ] }, @@ -231,7 +4465,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -267,38 +4501,42 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ - "variables_mapping.add_standard_model_final_state_values('1042_131', 'Upu_value')\n", - "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175, report_node)" + "network.clone_variant('InitialState', 'TCBCase')\n", + "network.set_working_variant('TCBCase')\n", + "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 300)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Display final state values " + "Display curve" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - " values\n", - "variables \n", - "NETWORK_1042_131_Upu_value 0.8069\n" - ] + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "print(res.final_state_values())" + "c = res.curves().plot()\n", + "c.set_xlabel('Time (ms)')\n", + "plt.show()" ] } ], From bff87a003e6f7b5ca53982c8692c9f7862989fc9 Mon Sep 17 00:00:00 2001 From: Joy El Feghali Date: Mon, 10 Feb 2025 16:04:55 +0100 Subject: [PATCH 4/9] Add description to Nordic test case Signed-off-by: Joy El Feghali --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 36 ++++++++++++++++++++--- 1 file changed, 32 insertions(+), 4 deletions(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index d8d2f80..55b38c0 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -11,7 +11,10 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "TODO - description" + "The Nordic test system is a variation of the so-called Nordic 32-bus system, which was created by the CIGRE Task Force 38-02-08 in 1995 to illustrate the voltage collapse in Sweden that happened in the year 1983. \n", + "The test case consists of four areas: an equivalent simplified network that has the biggest generators and therefore serves usually as the system reference, the northern region with few loads and more generation, a central area with more load than generation and a southern region loosely connected to the rest of the system.\n", + "One important characteristic of the system is the high power transfer from the North to the Central area. This characteristic is what ultimately results in long-term voltage collapse if the power transfer capability is affected, e.g. by losing one of the transmission lines that connect both areas.\n", + "The system comprises 20 generators (nineteen generators and one synchronous condenser) that are hydro and thermal generations. All loads are connected to 20 kV buses and controlled by Load Tap Changers (LTC)." ] }, { @@ -4339,7 +4342,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Add generators dynamic models" + "Add generators dynamic models : \n", + "Out of the total of twenty generators, the Equivalent and the North networks have twelve hydro generators that are modeled by salient-pole machines (GeneratorSynchronousThreeWindingsGoverNordicVRNordic). The two biggest generators belong to the Equivalent grid while the North area has ten generators. On the other hand, there are seven thermal generators modeled by round-rotor machines (GeneratorSynchronousFourWindingsPmConstVRNordic), two of them belong to the small South region, and the remaining five to the Central one that also has a synchronous condenser that is modeled as a salient-pole machine (GeneratorSynchronousThreeWindingsPmConstVRNordic)." ] }, { @@ -4379,7 +4383,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Add node fault and disconnect line event" + "Add node fault and disconnect line event:\n", + "The scenario consists of a three-phase fault at bus 4032 with a subsequent opening of the line 4032-4044 without further re-connection." ] }, { @@ -4431,7 +4436,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Display curve" + "Display curve " ] }, { @@ -4456,6 +4461,14 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Comment on the result:\n", + "The line 4032-4044 is tripped 0.1 s later. The system is short-term stable and it settles to a new equilibrium in 30 s. At around 35 s, the LTCs start acting attempting to restore the distribution voltage and hence the load consumption. The action of the LTC forces the generators to increase their reactive power injection and therefore their field current. Due to the actions of the LTCs, the OELs of some generators limit the field current. This leads to the voltage collapse depicted in the figure." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -4463,6 +4476,13 @@ "## 4 - Second simulation with tap changer blocking automation system" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Add a tap changer blocking automaton that will block the transformer when the monitored voltage is below a certain threshold" + ] + }, { "cell_type": "code", "execution_count": 10, @@ -4538,6 +4558,14 @@ "c.set_xlabel('Time (ms)')\n", "plt.show()" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Comment on the result :\n", + "When adding a Tap Changer Blocking Automaton, that blocks the LTCs when the voltage at bus 1042 is below 120kV, the voltage collapse is avoided, as shown in the figure." + ] } ], "metadata": { From 00fe62d9369bd1da2b7ef7fbf7991c9d5829abb5 Mon Sep 17 00:00:00 2001 From: Joy El Feghali Date: Tue, 11 Feb 2025 13:37:00 +0100 Subject: [PATCH 5/9] Add more detailed descriptions on the events Signed-off-by: Joy El Feghali --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index 55b38c0..3aa7835 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -4466,7 +4466,7 @@ "metadata": {}, "source": [ "Comment on the result:\n", - "The line 4032-4044 is tripped 0.1 s later. The system is short-term stable and it settles to a new equilibrium in 30 s. At around 35 s, the LTCs start acting attempting to restore the distribution voltage and hence the load consumption. The action of the LTC forces the generators to increase their reactive power injection and therefore their field current. Due to the actions of the LTCs, the OELs of some generators limit the field current. This leads to the voltage collapse depicted in the figure." + "The line 4032-4044 is tripped at 1.1s, 0.1 s after the fault occurred. The system tends to settle to a new equilibrium around 30 s, where the voltage rate of change is slow. At around 34 s, the LTCs start acting, by changing taps several times, attempting to restore the distribution voltage and hence the load consumption. It can be seen in the figure with the different spikes where the LTC action, leads to an increase in the voltage level. The action of the LTC forces the generators to increase their reactive power injection and therefore their field current. Due to the actions of the LTCs, the OELs of some generators limit the field current. This leads to the voltage collapse depicted in the figure." ] }, { From d2d045a406579f7cb5f682c004d9236875f04cd3 Mon Sep 17 00:00:00 2001 From: lisrte Date: Tue, 11 Feb 2025 16:56:49 +0100 Subject: [PATCH 6/9] Review fix Replace automaton with automation system Signed-off-by: lisrte --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 4287 +-------------------- 1 file changed, 32 insertions(+), 4255 deletions(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index 3aa7835..e3c4530 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -32,6 +32,7 @@ "source": [ "!curl -L $(curl -s -L -X GET https://api.github.com/repos/dynawo/dynawo/releases/latest | grep \"Dynawo_Linux\" | grep url | cut -d '\"' -f 4) -o Dynawo_Linux_latest.zip\n", "!unzip Dynawo_Linux_latest.zip > /dev/null 2>&1\n", + "!rm Dynawo_Linux_latest.zip \n", "!./dynawo/dynawo.sh help" ] }, @@ -48,7 +49,7 @@ "metadata": {}, "outputs": [], "source": [ - "pip install pypowsybl" + "pip install pypowsybl matplotlib pypowsybl-jupyter" ] }, { @@ -57,9 +58,9 @@ "metadata": {}, "outputs": [], "source": [ - "!mkdir /home/USER/.itools/\n", - "!cp /home/USER/dynawo/nordic case/config.yml /home/USER/.itools/\n", - "!cat /home/USER/.itools/config.yml" + "!mkdir /home/$USER/.itools/\n", + "!cp config.yml /home/$USER/.itools/\n", + "!cat /home/$USER/.itools/config.yml" ] }, { @@ -71,7 +72,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -79,4253 +80,27 @@ "import pypowsybl.dynamic as dyn\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "import os.path" + "import os.path\n", + "from pypowsybl_jupyter import display_nad" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { - "image/svg+xml": [ - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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" \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 591\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 700\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -700\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -1,080\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 1,080\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 100\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -100\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -600\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 600\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 800\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -800\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -346\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 348\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 500\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -500\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 235\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -233\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 235\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -233\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -530\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 530\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -1,060\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 1,060\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 590\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -590\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -69\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 69\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -69\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 69\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -2,138\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 2,138\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 2,000\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -2,000\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
1011_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
138.0 kV / 57.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1012_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
138.2 kV / 61.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1013_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
137.1 kV / 65.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1014_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
137.9 kV / 68.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1021_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
134.0 kV / 66.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1022_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
136.7 kV / 45.2°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1041_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
131.6 kV / -17.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1042_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
131.9 kV / -3.2°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1043_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
133.6 kV / -12.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1044_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
130.9 kV / -3.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1045_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
131.4 kV / -7.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
2031_220
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
226.1 kV / 27.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
2032_220
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
235.3 kV / 40.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4011_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
409.0 kV / 56.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4012_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
409.4 kV / 58.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4021_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
419.5 kV / 28.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4022_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
397.9 kV / 43.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4031_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
414.7 kV / 24.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4032_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
419.5 kV / 19.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4041_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
420.2 kV / 9.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4042_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
417.2 kV / 6.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4043_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
414.8 kV / 0.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4044_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
415.8 kV / 0.0°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4045_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
421.4 kV / -4.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4046_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
414.3 kV / 0.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4047_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
423.6 kV / 4.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4051_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
426.4 kV / -6.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4061_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
415.5 kV / 6.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4062_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
422.4 kV / 9.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4063_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
421.4 kV / 13.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4071_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
419.4 kV / 59.2°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4072_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
423.6 kV / 60.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B01___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -20.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B02___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -6.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B03___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / -15.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B04___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -6.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B05___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / -10.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B11___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.1 kV / 54.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B12___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / 58.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B13___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 62.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B22___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 42.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B31___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.1 kV / 24.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B32___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / 37.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B41___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 7.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B42___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 4.0°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B43___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -2.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B46___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -2.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B47___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 1.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B51___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -9.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B61___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 3.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B62___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / 7.0°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B63___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / 10.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B71___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.1 kV / 56.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B72___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 57.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG01__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
16.0 kV / 66.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG02__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.8 kV / 69.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG03__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.9 kV / 74.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG04__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.5 kV / 72.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG05__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.4 kV / 51.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG06__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.1 kV / 4.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG07__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.2 kV / -4.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG08__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.7 kV / 47.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG09__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.0 kV / 62.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG10__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.2 kV / 65.2°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG11__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.3 kV / 35.2°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG12__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.3 kV / 32.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG13__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.3 kV / 9.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG14__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.7 kV / 14.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG15__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.7 kV / 12.0°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG16__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.8 kV / 0.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG17__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.1 kV / 17.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG18__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.5 kV / 20.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG19__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.5 kV / 64.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG20__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.3 kV / 64.2°
\n", - "
\n", - " \n", - " \n", - "\n" - ], + "application/vnd.jupyter.widget-view+json": { + "model_id": "5553c204da48470c941f93591c6232d7", + "version_major": 2, + "version_minor": 1 + }, "text/plain": [ - "" + "NadWidget(diagram_data={'svg_data': '\\n" ] @@ -4457,7 +232,8 @@ ], "source": [ "c = res.curves().plot()\n", - "c.set_xlabel('Time (ms)')\n", + "plt.gca().xaxis.set_major_formatter(lambda x, pos: '{:.0f} s'.format(x/1000))\n", + "c.set_xlabel('Time')\n", "plt.show()" ] }, @@ -4485,7 +261,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 50, "metadata": {}, "outputs": [], "source": [ @@ -4521,7 +297,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 51, "metadata": {}, "outputs": [], "source": [ @@ -4539,12 +315,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 52, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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o0aP11vXp0we7d+9GcnIypkyZYvWldjP69u0LDw8P7N6927JMq9UiOzvb0lfom2++wfHjxy1flv/+978B1F4NmzdvnuVzn3/+OR577DF8/vnnuPfee9EWzGYzqqqqWmRbXbt2hUwmQ2pqqtXy8+fPQ6fTWQXSxowfPx4GgwE7duzAhg0bMH36dMu6M2fO4MqVK1i5ciXuvPNOxMTEoLCwsNHtBQcHIz8/3yrY/H5ofmhoKDQaDc6fP28V5KOjoxEVFdWkmm8Ubz8REbWQ2NhYTJ8+HW+//Xa9dYWFhTAYDFbLAgMDm3wbysvLC4MGDcI777yD22+/3dJ5Vy6XWy3//famTp2KjRs3YubMmXj99dcxYsQI6PV6rF69Glu3bsXGjRvr9Zf5vfDwcEycOBFLlizB9u3b662Pi4vDnj17MGLECEyZMgVfffXVdY+nuLgY2dnZyM3NBVAbWIDaKzRqtRoqlQqzZs3CggULEBAQAKVSiaeeegqDBw+2dBLu0qWL1TaLiooA1PYTquuLs2HDBsycORNvvfUWBg4caOmP4+Xl1aQrHGVlZUhPT7e8z8zMRFpaGgICAhAREYHy8nK8/PLLGDduHMLCwlBUVITVq1cjJyfHahh8dna25ZhNJpPlyz86Ovq6/VX8/Pzw+OOP47nnnoO7uztiY2Nx8eJFLFy4EIMGDcKQIUOuexxA7dWkCRMmYPHixTh9+jSmTZtmWRcREQG5XI533nkHc+fOxcmTJ/HSSy81ur2EhARcvnwZr732Gu6//37s2LED33//vdVzmZYvX46nn34aKpUKY8aMQVVVFY4cOYKrV69aHoTdKq47PspJtNaQ7j966KMUDukmaobGhnK2dzNnzhTjx4+3WpaZmSnkcnm9Id22Xn8cony94d9Lly4VAMTKlSutli9btkwAECtWrKj3GaPRKF5//XVx6623CrlcLpRKpRg9erQ4cOCAVbuGhhynpKQIAOLgwYNCiN+GdP/eL7/8IkJCQsT48eNFVVWVzdp/vx9b52Lp0qWWNpWVleIvf/mL6NChg/D29hYTJ060Gs7+R7bO27Bhw2zuZ+bMmY3W98dtNvT5yspKMXHiRKHRaIRcLhdhYWFi3Lhx4tChQ1bbmTlzps3t1A27v57KykqxdOlSERMTI7y8vERUVJSYM2eOuHz5cpM+X+e7774TAMTQoUPrrduwYYPo1KmTUCgUYvDgwWLr1q1Ww+1tnd/3339fhIeHCx8fHzFjxgzx8ssv1xvSvX79etGnTx8hl8tFhw4dxNChQ8WmTZsaPM6WGNLNp3S3sLoh3W9N7YPxfW6xWpd6oRgHzl2Bn6c7/L09EOirwMCoAHjeROdEIkfHp3QTUUs9pZu3n9qI0WTG458ewdUK6/vOGpUnnhvVHRPib4GbjMPDiYiIbhQ7CreRn89fwdUKI5Se7rivdxju7BqEED8FcnUGPLfxOO575wCSz16+/oaIiNqp/fv3w9fXt8FXe5Gdnd1onX983lVrmTt3boM1/PFZXw155ZVXGtxGYmJiKx9B+8MrNW3kh19rO6nd2zsMKybVzr5pMJrwyU9ZWL03Hafz9Jjx8SHcER2EvyXGoNctrTuWn4iopfXr18/mAyrbG41G02idGo2mTep48cUXG5zXqKndJObOndvghIJeXl43XJujYqhpA2azwH9/rX3C7Khb1Zblnh5umDusCx7sF47Ve9PxWcoFHEgvwn3vHMDE+Fvw3Khu6NjB215lExE1i5eXF6Kjo+1dxnW5u7u3izpDQkJuepK+gICAVnv0gyPi7ac2cOxiCQpLq+CncMeQLoH11nfwkeOF+3pi93PDML5P7b8QNh/LwV1v7MMr352GrqJl5n8gas/qZjElItfTUmOWeKWmDdTdehoeEwKFe8MjncIDvPHW1Hg8fkdnrPj+NH7KuIIPk8/jy8MX8eTwaDwyOJIjpcjpyOVyyGQy5ObmIjg4GHK5nM9UI3IhQghcvnwZkiQ1+/Ehf8RQ08qEENhxsjbUjOmlvk7rWrEdVVj/+EDsO3sZK78/gzP5pXj5u9P45Kcs/HV0N4yPuwUyjpQiJyGTyRAVFYW8vDzLhGxE5FokSULHjh3rPRG+uRhqWtmZ/FJkF1dA4S7DsG7BTf6cJElI6B6CO7sGY9PRS/jnf88ip6QS8788jg+TM/FEQhfc00sNdzfeQSTHJ5fLERERgZqaGphMJnuXQ0RtzMPD46YDDcBQ0+rqrtLc2TUYPormn243mYQH+oVjbJwGH/+Yiff3ZuB0nh5Pf34Mr/p74bHbO2FK/3AoPW/ukh2RvdVder7Zy89E5Lr4z/xWVtefpqm3nhri6eGGvyREI/l/hmPB3d0Q6CNHTkkl/vGf0xj48m48v/E4jmVfbbHOVkRERI6GV2pa0YUr5TiTXwo3mYSRPW5u2F6dDj5yPD2iK+YM7Ywtx3Lw8Y+ZOFtQho2pl7Ax9RK6h/phfLwG4+I0HA5OREQuhaGmFaVeuAoAiA/3h7+3vEW37enhhqkDIvBg/3CkXriKDYey8Z8TedAWlOK1HVq8tkOLfpEdMKaXGiN6hCIqqOEn8RIRETkDhppWlF1cAQDoEtx604NLkoR+nQLQr1MAlt53K74/mYetx3ORcv4Kjly4iiMXruIf/zmNLsE+uCsmBEOigzCgU8AN9e8hIiJqz/jN1orqQk1EYNvcBlJ5e2DqgAhMHRCBAr0B3/+Sh12nC/Hz+SvIuFyOjMuZ+Gh/JjzcJPQJ90ffyAD0jeyA2yL8EeiraJMaiYiIWgtDTSu6VFwJoHZSvbYWqvTEo7dH4dHbo6A3GLFPexk/phdh/7ki5JRU4nDWVRzOumppH6byRHe1H7qH+qG72g/dQv0QHeLLyf6IiMhhMNS0IsuVGjuEmt9TenpgbJwGY+M0EEIgu7gCB88X42j2VaReuIpzhWXI0xmQpzMgSfvbk8JlUu2ts5cm9MKgzvUf70BERNSeMNS0kiqjGfl6AwD7h5rfkyQJkYE+iAz0wZT+4QAAvcGIs/ml0BaUQpt/7VVQipIKI84VluFf/z2Lr+YOtnPlREREjWOoaSWXrtZepfFVuKODd/ueTEzp6WHpbFxHCIH0wjKMejMZh7KKcbG4wi630YiIiJqKk++1krpbT+EB3g75cD5JktA11A+3dwkCUPvUcCIiovaMoaaVXLx6rZNwBy87V3JzJsbfAgDYdPQSZysmIqJ2jaGmlbSXTsI3a0wvNbw83JB1pQLHLpbYuxwiIqIGMdS0ksulVQDabo6a1uKjcLc8t2rT0Ut2roaIiKhhDDWtzBk61066rfYW1LbjeaiqMdm5GiIiItsYalqZo99+AoAhXYIQqlRAV2nE3jOF9i6HiIjIJg7pbkWSBNzi79gdhQHATSZhQp9b8EHyeazZdx55OgM8PdzgLXdDoI8CQX5yBPkqoHD/LSMbTQKlBiP0lTWoqjEhtqMKCnfOTkxERK2HoaYVqZWeTvOYgUm3dcQHyeeRdrEEaTfQYXhq/3CsnNy75QsjIiK6ptm3n5KTkzF27FhoNBpIkoQtW7ZYrV+2bBliYmLg4+ODDh06YOTIkTh48KBVm+LiYkyfPh1KpRL+/v6YNWsWysrKGt2vwWDAvHnzEBgYCF9fX0yePBkFBQXNLb9NOUN/mjrd1X54ZWIsJt/WEff1DsPIHqEY0iUQ3UP9EOAjh62peHzkbghV1j4oc/OxHOgqjG1cNRERuZJmX6kpLy9HXFwc/vSnP2HSpEn11nfr1g3vvvsuOnfujMrKSqxatQqjRo1Ceno6goODAQDTp09HXl4edu7cCaPRiMceewxz5szBhg0bGtzv/Pnz8Z///AcbN26ESqXCk08+iUmTJuHHH39s7iG0mfAOzhNqAOChgRF4aGCEzXU1JjNqzLXz2EgS4CZJcHeTQQiBxLf240x+Kbak5WDmkE5tWDEREbkSSdzEjGqSJGHz5s2YMGFCg230ej1UKhV27dqFESNG4PTp0+jZsycOHz6Mfv36AQB27NiBe+65B5cuXYJGo6m3DZ1Oh+DgYGzYsAH3338/AODMmTPo0aMHUlJSMGjQoOvWWleHTqeDUqm8sQNugun//hk/pl8BAMwf2Q3PjOzaavtyFJ/8mIll204hRu2H75+50yFnWCYiIvtozvd3q45+qq6uxocffgiVSoW4uDgAQEpKCvz9/S2BBgBGjhwJmUxW7zZVndTUVBiNRowcOdKyLCYmBhEREUhJSbH5maqqKuj1eqtXW4sIdPxOwi1hQvwtkLvLcCa/FL/k6OxdDhEROalWCTXbt2+Hr68vPD09sWrVKuzcuRNBQbXPEMrPz0dISIhVe3d3dwQEBCA/P9/m9vLz8yGXy+Hv72+1PDQ0tMHPrFixAiqVyvIKDw+/+QNrJmcYzt0S/L3lSLw2gd8Xhy/auRoiInJWrRJqhg8fjrS0NPz0008YM2YMpkyZgsLCtp3fZNGiRdDpdJbXxYtt/2XqTB2Fb9bU/rV9cbam5aK8qua67WtMZugqjHzeFBERNVmrDOn28fFBdHQ0oqOjMWjQIHTt2hVr167FokWLoFar6wWcmpoaFBcXQ61W29yeWq1GdXU1SkpKrK7WFBQUNPgZhUIBhULRYsfUXJ4eMgT72m//7c2gzgHoFOiNrCsV+M8veZjSLxwGowmZReUo0BtwubQKhaVVyCgsw5n8UqRfLkN1jRn+3h6IDvZF11BfTB8YiV63qOx9KERE1E61yTw1ZrMZVVW1z0IaPHgwSkpKkJqair59+wIA9uzZA7PZjIEDB9r8fN++feHh4YHdu3dj8uTJAACtVovs7GwMHjy4LQ6h2SICvNkh9nckScKD/SPw6o4zeOMHLT5MPo/zl8tgvs6FmJIKI45cuIojF67i4Pli7FowDDIZzysREdXX7FBTVlaG9PR0y/vMzEykpaUhICAAgYGBePnllzFu3DiEhYWhqKgIq1evRk5ODh544AEAQI8ePTBmzBjMnj0ba9asgdFoxJNPPompU6daRj7l5ORgxIgR+OyzzzBgwACoVCrMmjULCxYsQEBAAJRKJZ566ikMHjy4SSOf7IH9aeqb3PcW/GunFoXXrsoAgMrLA2EqT4QoPRHip0BEgDdi1H6IUSsR7KdAZlE5zhWWYvGWkzhfVI7dZwpxd89QOx8JERG1R80ONUeOHMHw4cMt7xcsWAAAmDlzJtasWYMzZ87g008/RVFREQIDA9G/f3/s378ft956q+Uz69evx5NPPokRI0ZAJpNh8uTJePvtty3rjUYjtFotKioqLMtWrVplaVtVVYXRo0fjvffeu6GDbgsdnWyOmpYQ4ueJtTP743SeHt3UfugZpkSIn6LRK1o9NUr01ChxOq8Ua/Zl4KP95xlqiIjIppuap8aRtPU8NUvu64k/3RHVavtxNfk6A+54dQ9qzALfzrsdceH+9i6JiIjaQHO+v/nspxbWu6M/DmdexeAugfYuxamoVZ4Y10eDTUdz8NH+83j3odsabV+gN2DjkYs4cuEq/L08LLe3RvVUIyKQV9GIiJwRr9S0AoPR5DQPsmxPTuXqcc/b++Emk5D01wTLkHldpRGFegMKS6uQpzNgx8l87NUWwmSjF3J4gBd2L0iA3L1V550kIqIWwis1dsZA0zp6apS4IzoIB9KLsGrXWUSH+GLHyXycuGR7luL+nTrg3tgwVNWYUVhahc3HcnCxuBIbUy9i+sDINq6eiIhaG0MNOZTH74zCgfQibDqaY7Vc6eluucV0q0aJB/uHIzrEz6pNxw5eWL7tFN7dk47Jt3Vk+CQicjIMNeRQhnULxoBOATiaXdtvaUwvNUb1VCPY7/oTHU4bEIEPk88jT2fA54ey8djtzevIXVZVg9N5enQO8kEgJ1YkImp32KeGHI7JLGA0mW/oSsv6gxfwv5tPIshXgf3/MxxectvbMBhNSC8sw6lcPX7J0SH1wlWcydfDLIC4cH98O+/2mz0MIiJqAvapIafmJpPgJruxW0cP9A3Hmn0ZuFhciU9+ykLfyA747pc8JJ+7jMpqE8xCwCyA4vJqmx2NASDnaoXN5UREZF8MNeRS5O4yPH1XVzz/9Qm8uuNMo239vT1wq0aJnmFKxEd0gK/CHTM+PtToZ8xmgYJSAy5cqUBuSSUK9FUo0BugqzSiYwcvxKiV6K72Q1SQD9z4uAciohbFUEMuZ2L8Lfgw+TzOFZbBz9Mdo3qqMaaXGmqlJyQJkCQgwEd+7f1vwUObX9rgNi8WV2DWp4dxtqCsSTX07qjC/3t8IJSeHjd9PEREVIuhhlyOu5sMn88ZhPOXy9En3P+m56wRQmDmukM4f7kcQO3tsY4dvHCLvxfUSk+Eqjyh9PRAVlE5zhSU4kyeHicu6fDsF2n4aEY/XrEhImohDDXkkoJ8FQhqoRFM20/kWQLN/80agMGdA+Hu1nBQOnGpBA+sScGeM4X453+1+J8xMS1SBxGRq+O0qkQ3QW8w4qXtpwAA80d2w51dgxsNNEDtozRendwbAPBeUga2Hc9t9TqJiFwBQw1RE9V1r7laYcRbu86hstqEf/33LApLqxAV5IO5CZ2bvK0J8bfgz0Nr2z//9XEcPH+lNUomInIpDDVETRQZ6I0hXQJhMgus2nUWd/0zCZ+lZAEAXhrfCwr35g0z/58xMUjoHgyD0YxH1h7Ct2k51/8QERE1iKGGqIkU7m5Y//hAvDMtHrf4eyFPZ4BZAOPiNLija1Czt+cmk7Dm4b4Yc6sa1SYznvkiDav3psNF5sMkImpxnFGY6AYYjCasPZCJswWlWHJfz5t6bILJLPDKd6ex9kAmACChezAeGRSJYd2u3z+HiMjZNef7m6GGqJ345MdMvLj9FOomMg5VKnBXTCg83CSYr/0x7RTog54aJW7VqKDy4hw3ROT8GGpsYKghR5BeWIovDl3EpmM5KC6vbrTtoM4B+ODhflB5M9wQkfNiqLGBoYYcSXWNGbtOF+DXXB1kkgSZJMFkFjhXWIpfc/W4dLUSANC/Uwf836yBN/RwTyIiR8BQYwNDDTmTU7l6TP0wBXpDDUb2CMGah/uy/w0ROaXmfH/zb0EiB9RTo8TaR/tD4S7DrtOF+NumXzhqiohcHkMNkYPq3ykAqx+6DW4yCV+nXsJ97xzAd7/kwWRmuCEi18TbT0QObvOxS/j7ppOoNJoAAJ2DfDC+zy3oEuKDqCAfdA7yhZecfW6IyDGxT40NDDXkzIrLq/HJT1n49Kcs6CqNVuskCYgM8EZ3tR9i1ErEqP3QXe2HyEAfPiGciNo9hhobGGrIFZRV1WDT0Us4cUmH85fLcL6oHCUVRpttPT1kGBETin9OiePoKSJqt5rz/e3eRjURURvwVbhjxuBOVsuKyqqgzS/F6Tw9tPmlOJNfirMFpTAYzfjPL3noHOyD50Z1t0/BREQtiKGGyMkF+SoQFK3A7dG/PZ/KZBbYejwH8788jjX7MjAh/hZ0Cfa1Y5VERDePo5+IXJCbTMKEPrdgePdgGE0Ci7ec5JBwInJ4DDVELkqSJCwf1wsKdxl+yriCrcdz7V0SEdFNYaghcmERgd54cng0AOAf/zkNvcF2p2IiIkfAUEPk4uYM64zOQT64XFqFf2w/Ze9yiIhuGEMNkYtTuLvhlUmxkCTgqyOXsI23oYjIQTHUEBEGdQ603Ib6+6ZfcLG4ws4VERE1H0MNEQEAnhnRFf0iO6C0qgZPfn4MRpMZAFCoN+BY9lVkFZWjvKrGzlUSETWMMwoTkcWlqxW456390BtqEKP2Q1FZNYrKqqzaeMvdEOynQLCvAsF+CvSN7IBHh3SCuxv/jURELY8zChPRDenYwRuv3d8bc//fUZzJLwUAyCQgxM8TukojKo0mVFSbcOFKBS5cqb1F9f3JfJiFwJyhXexZOhERQw0RWRvTKwwfPtIXl8uq0DNMiRi1El5yNwghUF5tQlFpFS6XVeFyaRVSL1zF2gOZWLXzHBJ7hSE8wNve5RORC+PtJyK6YUIIPPjhzziUWYzh3YPx8aP9IUl88jcRtZzmfH/zJjgR3TBJkvDKxFh4uEnYq72M737Jt3dJROTCGGqI6KZEh/jiiYTa4eDLtv3KWYmJyG6aHWqSk5MxduxYaDQaSJKELVu2WNYZjUYsXLgQsbGx8PHxgUajwYwZM5Cb+9tkXklJSZAkyebr8OHDDe43ISGhXvu5c+c2t3wiagV/SeiCqGuzEr+8/bS9yyEiF9XsUFNeXo64uDisXr263rqKigocPXoUixcvxtGjR7Fp0yZotVqMGzfO0mbIkCHIy8uzej3++OOIiopCv379Gt337NmzrT732muvNbd8ImoFnh5ueGVi7azEXx65iO9+ybN3SUTkgpo9+ikxMRGJiYk216lUKuzcudNq2bvvvosBAwYgOzsbERERkMvlUKvVlvVGoxHffvstnnrqqet2MPT29rb6LBG1H4O7BGLusC54PykDf/vmBHp3VKFjB46GIqK20+p9anQ6HSRJgr+/v831W7duxZUrV/DYY49dd1vr169HUFAQevXqhUWLFqGiouGp3KuqqqDX661eRNS6FtzdDXHh/tAbavDsF2mouTYrcanBiF9zdTAYTXaukIicWavOU2MwGLBw4UJMmzatwWFYa9euxejRo9GxY8dGt/XQQw8hMjISGo0GJ06cwMKFC6HVarFp0yab7VesWIHly5ff9DEQUdN5uMnwztR43Pv2fhy5cBUz1x1CcbkR2nw9zAKQu8nQJ9wfAzsHoHOwD/wUHvDzdIfG34tz3BDRTbupeWokScLmzZsxYcKEeuuMRiMmT56MS5cuISkpyWaouXTpEiIjI/HVV19h8uTJzdr3nj17MGLECKSnp6NLl/ozmVZVVaGq6rfp3fV6PcLDwzlPDVEb+DYtB898kWa1zFfhjrIGnh0lScAnjw3AsG7BbVAdETkSuz8mwWg0YsqUKbhw4QL27NnTYBHr1q1DYGCgVUfipho4cCAANBhqFAoFFApFs7dLRDdvfJ9boDfU4EJROW6L7IB+kR0Q7KdA1pUKHDx/BYeyilGor0KpwYjC0irk6Qz4+6Zf8MP8ofBVcKJzIroxLf63R12gOXfuHPbu3YvAwECb7YQQWLduHWbMmAEPD49m7yctLQ0AEBYWdjPlElEreWRQZL1lUUE+iArywdQBEZZlFdU1GP1mMi4WV+L1HWewfHyvtiyTiJxIszsKl5WVIS0tzRIqMjMzkZaWhuzsbBiNRtx///04cuQI1q9fD5PJhPz8fOTn56O6utpqO3v27EFmZiYef/zxevvIyclBTEwMDh06BADIyMjASy+9hNTUVGRlZWHr1q2YMWMGhg4dit69e9/AYRNRe+Etd8eKibV/jj/7+QIOZxXbuSIiclTNDjVHjhxBfHw84uPjAQALFixAfHw8lixZgpycHGzduhWXLl1Cnz59EBYWZnn99NNPVttZu3YthgwZgpiYmHr7MBqN0Gq1ltFNcrkcu3btwqhRoxATE4PnnnsOkydPxrZt227kmImonbmjaxCm9OsIIYCF35zgKCkiuiF8oCURtQu6CiNGrtqHy6VVeCKhCxaOqf8PHiJyPXygJRE5HJW3B1661p9mzb4M/JheZOeKiMjRMNQQUbsxppca0waEQwjg2S/TUFRWdf0PERFdw1BDRO3KkvtuRdcQX1wurcJzXx2H2Vx7h9xgNOHClXLLeyKiP2KfGiJqd7T5pRj37gFU1ZgxKf4WXK2oRvK5IpjMAq9MjMVDAyOuvxEicgrsU0NEDq272g9LxvYEAGw6loO92sswXbtCcypPZ8/SiKgd49SdRNQuPTQgAheLK/Frrg63RwchvbAMX6degr7S9qMWiIgYaoioXZIkCX9L/G1Y91dHLuLr1EvQVRrtWBURtWe8/UREDkHlVfs4FYYaImoIQw0ROYS6UKNnqCGiBjDUEJFD4JUaIroehhoicgi/DzUuMhMFETUTQw0ROQTltVBTYxaoqOYDL4moPoYaInIIPnI3uMkkAIDewFtQRFQfQw0ROQRJktivhogaxVBDRA7DEmoqGGqIqD6GGiJyGEpeqSGiRjDUEJHD4O0nImoMQw0ROQyGGiJqDEMNETkMlVft4+o4qzAR2cJQQ0QOg1dqiKgxDDVE5DAYaoioMQw1ROQwGGqIqDEMNUTkMBhqiKgxDDVE5DA4Tw0RNYahhogcRt2VGr2hxs6VEFF7xFBDRA5D6ckrNUTUMIYaInIYKu/aUFNdY4bBaLJzNUTU3jDUEJHD8JW7QybV/syrNUT0Rww1ROQwZDKJnYWJqEEMNUTkUDism4gawlBDRA7FEmoqGGqIyBpDDRE5FF6pIaKGMNQQkUNhnxoiaghDDRE5FF6pIaKGMNQQkUNhqCGihjDUEJFDsTwqgaGGiP6AoYaIHAqv1BBRQxhqiMih/PZQS4YaIrLGUENEDoUPtSSihjDUEJFD4e0nImpIs0NNcnIyxo4dC41GA0mSsGXLFss6o9GIhQsXIjY2Fj4+PtBoNJgxYwZyc3OtttGpUydIkmT1WrlyZaP7NRgMmDdvHgIDA+Hr64vJkyejoKCgueUTkYNjqCGihjQ71JSXlyMuLg6rV6+ut66iogJHjx7F4sWLcfToUWzatAlarRbjxo2r1/bFF19EXl6e5fXUU081ut/58+dj27Zt2LhxI/bt24fc3FxMmjSpueUTkYOrCzUGoxlVNSY7V0NE7Yl7cz+QmJiIxMREm+tUKhV27txptezdd9/FgAEDkJ2djYiICMtyPz8/qNXqJu1Tp9Nh7dq12LBhA+666y4AwLp169CjRw/8/PPPGDRoUHMPg4gclJ+nOyQJEKL2ak2In5u9SyKidqLV+9TodDpIkgR/f3+r5StXrkRgYCDi4+Px+uuvo6ampsFtpKamwmg0YuTIkZZlMTExiIiIQEpKis3PVFVVQa/XW72IyPHJZBL8FLX/HuNcNUT0e82+UtMcBoMBCxcuxLRp06BUKi3Ln376adx2220ICAjATz/9hEWLFiEvLw//+te/bG4nPz8fcrm8XjAKDQ1Ffn6+zc+sWLECy5cvb7FjIaL2Q+XtAb2hhv1qiMhKq4Uao9GIKVOmQAiB999/32rdggULLD/37t0bcrkcf/7zn7FixQooFIoW2f+iRYus9qPX6xEeHt4i2yYi+1J5eeAiKhlqiMhKq9x+qgs0Fy5cwM6dO62u0tgycOBA1NTUICsry+Z6tVqN6upqlJSUWC0vKChosF+OQqGAUqm0ehGRc+AIKCKypcVDTV2gOXfuHHbt2oXAwMDrfiYtLQ0ymQwhISE21/ft2xceHh7YvXu3ZZlWq0V2djYGDx7cYrUTkWOwhJoKhhoi+k2zbz+VlZUhPT3d8j4zMxNpaWkICAhAWFgY7r//fhw9ehTbt2+HyWSy9HkJCAiAXC5HSkoKDh48iOHDh8PPzw8pKSmYP38+Hn74YXTo0AEAkJOTgxEjRuCzzz7DgAEDoFKpMGvWLCxYsAABAQFQKpV46qmnMHjwYI58InJBv12paXiAARG5nmaHmiNHjmD48OGW93X9VmbOnIlly5Zh69atAIA+ffpYfW7v3r1ISEiAQqHAF198gWXLlqGqqgpRUVGYP3++Vf8Xo9EIrVaLiooKy7JVq1ZBJpNh8uTJqKqqwujRo/Hee+81t3wicgJKPv+JiGyQhBDC3kW0Bb1eD5VKBZ1Ox/41RA7uvaR0vLZDi/v7dsQbD8TZuxwiakXN+f7ms5+IyOGwozAR2cJQQ0QOh0/qJiJbGGqIyOHUXanhjMJE9HsMNUTkcHj7iYhsYaghIodTF2quVlTDRcY6EFETMNQQkcPR+HvB00MGg9GMjMvl9i6HiNoJhhoicjhydxn6hPsDAA5nFdu3GCJqNxhqiMgh9e8UAIChhoh+w1BDRA6p37VQcyTrqp0rIaL2gqGGiBzSbRH+kElAdnEFCvQGe5dDRO0AQw0ROSQ/Tw/0CKudMp23oIgIYKghIgfWn7egiOh3GGqIyGHVhZpDmbxSQ0QMNUTkwPp16gAAOJOvh97A2YWJXB1DDRE5rFClJyICvGEWwLHsEnuXQ0R2xlBDRA7NMl8Nb0ERuTyGGiJyaP2v3YLiCCgiYqghIodWNwlf2sUSVNeY7VwNEdkTQw0RObQuwT4I8JGjqsaMX3J09i6HiOyIoYaIHJokSegXWXsLikO7iVwbQw0RObyBnQMBAAczr9i5EiKyJ4YaInJ4gzr/NrNwjYn9aohcFUMNETm8GLUSSk93lFXV4Ndcvb3LISI7YaghIofnJpMwIKr2ag1vQRG5LoYaInIKg671q/n5PDsLE7kqhhoicgoDo2pDzeHMYpjMws7VEJE9MNQQkVPoqVHCT+GO0qoanGK/GiKXxFBDRE7BTSahP/vVELk0hhoichoDr4Wan88z1BC5IoYaInIadZ2FD7FfDZFLYqghIqdxq0YJX4U79IYanM5jvxoiV8NQQ0ROw91Nhn6dap8DdZDPgSJyOQw1RORU6oZ2s18NkethqCEip1J3peZkjs7OlRBRW2OoISKn0i3UDwCQpzNAV2m0czVE1JYYaojIqai8PKBReQIAzhaU2rkaImpLDDVE5HS6qWuv1mjzGWqIXAlDDRE5ne7XbkHxSg2Ra2GoISKnU9evhldqiFwLQw0ROZ3u6t+u1AjBmYWJXEWzQ01ycjLGjh0LjUYDSZKwZcsWyzqj0YiFCxciNjYWPj4+0Gg0mDFjBnJzcy1tsrKyMGvWLERFRcHLywtdunTB0qVLUV1d3eh+ExISIEmS1Wvu3LnNLZ+IXEB0iC9kEnC1wojLZVX2LoeI2kizQ015eTni4uKwevXqeusqKipw9OhRLF68GEePHsWmTZug1Woxbtw4S5szZ87AbDbjgw8+wK+//opVq1ZhzZo1+Pvf/37dfc+ePRt5eXmW12uvvdbc8onIBXh6uKFToA8A4Gx+mZ2rIaK24t7cDyQmJiIxMdHmOpVKhZ07d1ote/fddzFgwABkZ2cjIiICY8aMwZgxYyzrO3fuDK1Wi/fffx9vvPFGo/v29vaGWq1ubslE5IK6hfrhfFE5tAWluKNrkL3LIaI20Op9anQ6HSRJgr+/f6NtAgICrrut9evXIygoCL169cKiRYtQUVHRYNuqqiro9XqrFxG5jt+GdfPPPpGraPaVmuYwGAxYuHAhpk2bBqVSabNNeno63nnnnetepXnooYcQGRkJjUaDEydOYOHChdBqtdi0aZPN9itWrMDy5ctv+hiIyDHVDevWFvD2E5GraLVQYzQaMWXKFAgh8P7779tsk5OTgzFjxuCBBx7A7NmzG93enDlzLD/HxsYiLCwMI0aMQEZGBrp06VKv/aJFi7BgwQLLe71ej/Dw8Bs8GiJyNN3VvgCAcwWlMJsFZDLJzhURUWtrldtPdYHmwoUL2Llzp82rNLm5uRg+fDiGDBmCDz/8sNn7GDhwIIDaKz22KBQKKJVKqxcRuY7IQB/I3WSoqDYhp6TS3uUQURto8VBTF2jOnTuHXbt2ITAwsF6bnJwcJCQkoG/fvli3bh1ksuaXkZaWBgAICwu72ZKJyAl5uMnQJaT2ag0n4SNyDc1OE2VlZUhLS7OEiszMTKSlpSE7OxtGoxH3338/jhw5gvXr18NkMiE/Px/5+fmWeWjqAk1ERATeeOMNXL582dKmTk5ODmJiYnDo0CEAQEZGBl566SWkpqYiKysLW7duxYwZMzB06FD07t27BU4DETmj7qHXQg0fl0DkEprdp+bIkSMYPny45X1dv5WZM2di2bJl2Lp1KwCgT58+Vp/bu3cvEhISsHPnTqSnpyM9PR0dO3a0alM386fRaIRWq7WMbpLL5di1axfefPNNlJeXIzw8HJMnT8YLL7zQ3PKJyIV0U/MZUESuRBIuMoe4Xq+HSqWCTqdj/xoiF7H7dAFmfXoEMWo/7Hh2qL3LIaIb0Jzvbz77iYicVt2DLTMul8FoMtu5GiJqba06Tw0RkT117OAFH7kbyqtNSHxrP27vEojBXYIwPCYYCnc3e5dHRC2MV2qIyGlJkoSpAyIAAOmFZfg05QLm/r9UJL65HykZV+xcHRG1NPapISKnV1xejYPnryDl/BV890s+iq49ufuBvh3x93t6oIOP3M4VElFDmvP9zVBDRC5FV2nEazvOYP3BbAC1t6j+O38ovOW8G0/UHrGjMBFRA1ReHnh5Yiy+njsYaqUnLl2txGcpF+xdFhG1AIYaInJJ/ToF4PnR3QEAH+zLQFlVjZ0rIqKbxVBDRC5rfB8NOgf54GqFEZ/+lGXvcojoJjHUEJHLcneT4ZmRXQEAHyafh95gtHNFRHQzGGqIyKXd11uD6BBf6CqNWHcgy97lENFNYKghIpfmJpPwzIjaqzX/PnAeugperSFyVAw1ROTy7o0NQ7dQX5QaarAx9aK9yyGiG8RQQ0QuTyaTMOm2jgCAI1lX7VwNEd0ohhoiIgDx4f4AgKPZV+Eic5ISOR2GGiIiALEdVXCTSSgsrUKezmDvcojoBjDUEBEB8Ja7o0eYHwDgWHaJfYshohvCUENEdE18eAcAwLFs9qshckQMNURE18RH+AMAjl0ssWsdRHRjGGqIiK6Jj6i9UvNLjg7VNWY7V0NEzcVQQ0R0TadAb/h7e6C6xozTeXp7l0NEzcRQQ0R0jSRJlqHd7FdD5HgYaoiIfqfuFhT71RA5HoYaIqLfsXQW5rBuIofDUENE9Dtx4f6QJCC7uAJFZVX2LoeImoGhhojod5SeHuga4guAV2uIHA1DDRHRH3ASPiLHxFBDRPQH7FdD5JgYaoiI/iDu2rDuk7k6PrGbyIEw1BAR/UHnYB/IJKDUUIPL7CxM5DAYaoiI/kDh7oaIAG8AQHphmZ2rIaKmYqghIrKhS3DtCKgMhhoih8FQQ0RkQ/S1Yd28UkPkOBhqiIhs6HIt1GRcLrdzJUTUVAw1REQ28EoNkeNhqCEisqGuT02+3oBSg9HO1RBRUzDUEBHZoPLyQLCfAgBvQRE5CoYaIqIGRAfzFhSRI2GoISJqQLSlszBDDZEjYKghImpAl2AfALxSQ+QoGGqIiBoQHeIHgBPwETmKZoea5ORkjB07FhqNBpIkYcuWLZZ1RqMRCxcuRGxsLHx8fKDRaDBjxgzk5uZabaO4uBjTp0+HUqmEv78/Zs2ahbKyxv/SMBgMmDdvHgIDA+Hr64vJkyejoKCgueUTETVZ3e2nC8UVqK4x27kaIrqeZoea8vJyxMXFYfXq1fXWVVRU4OjRo1i8eDGOHj2KTZs2QavVYty4cVbtpk+fjl9//RU7d+7E9u3bkZycjDlz5jS63/nz52Pbtm3YuHEj9u3bh9zcXEyaNKm55RMRNVmoUgFfhTtMZoELVzgCiqi9k4QQ4oY/LEnYvHkzJkyY0GCbw4cPY8CAAbhw4QIiIiJw+vRp9OzZE4cPH0a/fv0AADt27MA999yDS5cuQaPR1NuGTqdDcHAwNmzYgPvvvx8AcObMGfTo0QMpKSkYNGjQdWvV6/VQqVTQ6XRQKpU3dsBE5HLGv3sAxy/p8P7025AYG2bvcohcTnO+v1u9T41Op4MkSfD39wcApKSkwN/f3xJoAGDkyJGQyWQ4ePCgzW2kpqbCaDRi5MiRlmUxMTGIiIhASkqKzc9UVVVBr9dbvYiImqsLZxYmchitGmoMBgMWLlyIadOmWdJVfn4+QkJCrNq5u7sjICAA+fn5NreTn58PuVxuCUZ1QkNDG/zMihUroFKpLK/w8PCbPyAicjmWxyVwWDdRu9dqocZoNGLKlCkQQuD9999vrd00aNGiRdDpdJbXxYsX27wGInJ8dRPwca4aovbPvTU2WhdoLly4gD179ljdA1Or1SgsLLRqX1NTg+LiYqjVapvbU6vVqK6uRklJidXVmoKCggY/o1AooFAobv5giMilWZ7WXVgOs1lAJpPsXBERNaTFr9TUBZpz585h165dCAwMtFo/ePBglJSUIDU11bJsz549MJvNGDhwoM1t9u3bFx4eHti9e7dlmVarRXZ2NgYPHtzSh0BEZBEZ4A0PNwmVRhMuXa20dzlE1IhmX6kpKytDenq65X1mZibS0tIQEBCAsLAw3H///Th69Ci2b98Ok8lk6fMSEBAAuVyOHj16YMyYMZg9ezbWrFkDo9GIJ598ElOnTrWMfMrJycGIESPw2WefYcCAAVCpVJg1axYWLFiAgIAAKJVKPPXUUxg8eHCTRj4REd0odzcZooJ8cLagDGPeSsbwmBAk9lIjvIM33GQS3N0khCm9oPL2sHepRC6v2UO6k5KSMHz48HrLZ86ciWXLliEqKsrm5/bu3YuEhAQAtZPvPfnkk9i2bRtkMhkmT56Mt99+G76+tZd5s7KyEBUVZfUZg8GA5557Dp9//jmqqqowevRovPfeew3efvojDukmohu1/UQuVnx3Bjkltq/UKD3dsXPBMIQqPdu4MiLn15zv75uap8aRMNQQ0c0QQuDEJR2+O5mHfdrLKDXUoMZshr6yBpVGEx67vROWjr3V3mUSOR2GGhsYaoioNew/dxmPrD0EhbsM+/9nOEJ4tYaoRbWryfeIiJzZHdFBuC3CH1U1ZnyQfN7e5RC5NIYaIqKbIEkSnhnZDQCw/uAFXC6tsnNFRK6LoYaI6CYN7RqEPuH+MBjN+DA5w97lELkshhoioptUe7WmKwDg/36+gKIyXq0hsgeGGiKiFpDQLRhxHVUwGM344lC2vcshckkMNURELUCSJIzpFQYAOF9UbudqiFwTQw0RUQtRq2qfN1egN9i5EiLXxFBDRNRCQv1q56jJ1zHUENkDQw0RUQsJVdWGmgI9OwoT2QNDDRFRC1Ffm024rKoGZVU1dq6GyPUw1BARtRAfhTv8FO4A2K+GyB4YaoiIWlCI8lpnYfarIWpzDDVERC1Ifa1fTT6v1BC1OYYaIqIWFKpkqCGyF4YaIqIWVNdZuJAjoIjaHEMNEVELslypYZ8aojbHUENE1IJ4+4nIfhhqiIhakNoyAR9DDVFbY6ghImpBlj41pVUwm4WdqyFyLQw1REQtKMhXDpkEmMwCReXsLEzUlhhqiIhakLubDEG+dRPwMdQQtSWGGiKiFsYJ+Ijsg6GGiKiF1Y2AYmdhorbFUENE1MJC657/xFBD1KYYaoiIWpiaE/AR2QVDDRFRC+MEfET2wVBDRNTC6joK8/lPRG2LoYaIqIXxSg2RfTDUEBG1sLpQo6s0wmA02bkaItfBUENE1MKUnu7w8nADwM7CRG2JoYaIqIVJksQHWxLZAUMNEVErCPGrnauG/WqI2g5DDRFRK+CVGqK2x1BDRNQKfpuAj8O6idqKu70LICJyRpbnP5UaYDSZ8WHyeWxNy0VZVQ0qjSZUGU0Y3CUIf0vsjugQPztXS+QcGGqIiFpBXaj5NUeHse8cwJn80nptdp0uwF5tIaYPjMCzI7shwEfe1mUSORWGGiKiVqBW1XYUzrpSAQDo4O2BhWNiEBOmhLfcDQajCe/sScfOUwX4LOUCvk3LxTvT4jG0W7A9yyZyaAw1REStIDzAG5IECAGMjdNg6dieCPJVWLX5aEY//JRRhJe2n8bpPD0e++QwFt/bAzOHdIIkSXaqnMhxSUIIYe8i2oJer4dKpYJOp4NSqbR3OUTkAnafLoCXhxuGRAc12q6qxoS/bzqJb45eAgBMGxCB5eNuhdydYzmImvP93ew/McnJyRg7diw0Gg0kScKWLVus1m/atAmjRo1CYGAgJElCWlqa1fqsrCxIkmTztXHjxgb3++ijj9ZrP2bMmOaWT0TUZkb0CL1uoAEAhbsb3nigN/73nh6QJODzQ9l4e/e5NqiQyLk0O9SUl5cjLi4Oq1evbnD9HXfcgVdffdXm+vDwcOTl5Vm9li9fDl9fXyQmJja67zFjxlh97vPPP29u+URE7ZIkSZg9tDP+MaEXgNpOxETUPM3uU5OYmNho+HjkkUcA1F6RscXNzQ1qtdpq2ebNmzFlyhT4+vo2um+FQlHvs0REzmT0rWr87+aT0BaUoqSiGv7eHBFF1FR2v2GbmpqKtLQ0zJo167ptk5KSEBISgu7du+OJJ57AlStXGmxbVVUFvV5v9SIiau+CfBXoHOwDIYAjWVftXQ6RQ7F7qFm7di169OiBIUOGNNpuzJgx+Oyzz7B79268+uqr2LdvHxITE2EymWy2X7FiBVQqleUVHh7eGuUTEbW4gVEBAIDDWcV2roTIsdg11FRWVmLDhg1NukozdepUjBs3DrGxsZgwYQK2b9+Ow4cPIykpyWb7RYsWQafTWV4XL15s4eqJiFpH/061oeZgJkMNUXPYNdR8/fXXqKiowIwZM5r92c6dOyMoKAjp6ek21ysUCiiVSqsXEZEjGHDtSs3JHB0qqmvsXA2R47BrqFm7di3GjRuH4ODmz6B56dIlXLlyBWFhYa1QGRGR/XTs4I1b/L1QYxY4ll1i73KIHEazQ01ZWRnS0tIs889kZmYiLS0N2dnZAIDi4mKkpaXh1KlTAACtVou0tDTk5+dbbSc9PR3Jycl4/PHHbe4nJiYGmzdvtuzz+eefx88//4ysrCzs3r0b48ePR3R0NEaPHt3cQyAiavf6d+oAgLegiJqj2aHmyJEjiI+PR3x8PABgwYIFiI+Px5IlSwAAW7duRXx8PO69914AtX1h4uPjsWbNGqvtfPzxx+jYsSNGjRplcz9arRY6nQ5A7TDwEydOYNy4cejWrRtmzZqFvn37Yv/+/VAoFDY/T0TkyAZEBQIADmU2PMqTiKzxMQlERO1QemEpRv4rGQp3GX5ZNpqPTCCX1aqPSSAiotbXJdgXAT5yVNWY8UtOib3LIXIIDDVERO2QJEkYwKHdRM3CUENE1E71r5uEj6GGqEkYaoiI2qm6mYV/TL+Cpz4/hq9TL6Gw1GDnqojar2Y/0JKIiNpGjzAlYtR+OJNfim3Hc7HteC7cZBIWJcbg8Ts727s8onaHoYaIqJ1yk0nY/tQdSLtYgiTtZezVFuLXXD3+8Z/TKCqrxsIx3SFJkr3LJGo3OKSbiMiBrNmXgZXfnwEATOnXEa9MjIW7G3sSkPPikG4iIic1d1gXvDa5N2QS8NWRS3hywzEYTWZ7l0XULjDUEBE5mCn9w7Hm4b6Qu8uw49d8PPfVcZjMLnHRnahRDDVERA5o1K1qrHn4Nni4Sdh6PBeLNp2AmcGGXBxDDRGRg7orJhRvTY233Ipavu1XuEg3SSKbGGqIiBzYPbFh+OeUOEgS8GnKBaz8/gyDDbkshhoiIgc3Mb4jXp4QCwD4IPk83tp9zs4VEdkHQw0RkRN4aGAEFt/XEwDw5q5z+GBfhp0rImp7DDVERE5i1h1ReH50dwDAiu/P4OMDmXauiKhtMdQQETmRecOj8eTwaADAi9tPYfXedPaxIZfBUENE5GSeG9UNz4zoCgB4/QctVu5g52FyDQw1RERORpIkzL+7G/73nh4AgA/2nccLW05ygj5yegw1REROavbQznhlYiwkCVh/MBuzPzuCsqoae5dF1GoYaoiInNhDAyOw+qHboHCXYc+ZQtz//k+4dLXC3mURtQqGGiIiJ3dPbBi+/PNgBPspcCa/FBNW/4jDWcX2LouoxTHUEBG5gD7h/vh23u3oEaZEUVk1pn74M97dc479bMipMNQQEbkIjb8Xvp47GBPjb4HJLPDGf89i5seHUFhqsHdpRC2CoYaIyIX4KNzxrylxeP3+3vDycMOB9CKMXpWMLcdyOOybHB5DDRGRi5EkCQ/0C8e2p25HjNoPVyuMePbLNDz2yWF2IiaHxlBDROSiokP8sPXJO/DXUd0gd5MhSXsZo1Yl4+3d51BRzaHf5Hgk4SLXG/V6PVQqFXQ6HZRKpb3LISJqV9ILy7Bo0wkczroKAAjxU2DB3d3wQL9wuMkkO1dHrqw5398MNUREBAAwmwW2/5KH1384g4vFlQCAToHemDO0Cybddgs8PdzsXCG5IoYaGxhqiIiapqrGhP9LuYB396ajpMIIAAj2U+DRIZ0wpV84gv0Udq6QXAlDjQ0MNUREzVNeVYMvDl/Ev/efR56udti3u0zCXTEhmDogHHd2DYaHG7tmOjMhBMwCMJkFzKL2ZTILmM2Aqe7n3y13k0kIU3m1aA0MNTYw1BAR3ZjqGjO2Hs/F+oMXcCy7xLJc5eWBkT1CMfrWUNzZNRhect6euhkms0BFdQ0qjSZUGc2oNJpgMJpQWW269rMZhrplRutl1TVmGE1m1JgEjCYzqk21741172vMqDH/9vPv19X9bDJfewkBsyWsNO8YugT7YPdzCS16XhhqbGCoISK6eWcLSvHl4YvYciwHV8qrLcvlbjL07qhC/6gADOgUgLhwfwT4yO1YadsymQXKqmpQajBCX1n731JDDUqrrv3XUAP9tWX6yrplv60rNRhRXm2y92HcEJkEyCQJMpmEzkE+2PHs0BbdPkONDQw1REQtx2QWOJJVjB2/5uO/vxYgp6SyXpuOHbzQu6MKPdRKRIf4okuILzoF+kDu3r5uWZnNAmXVNX8IGr+FE73Bxro/hJKWfvq5l4cbvORu8HSXwVPuBk/32vdeHm7w9JDB08MNnh6/vZe7y+DhVvuSu8ng7iZZfvZwr/3ZXSaD/NrPv70ky3/dZDK4SRJkMsBNJtUGFUmCm0xqcLlMqp33qDUx1NjAUENE1DqEEMgursDBzGIcyixG6oWryCwqt9lWkmqHi4epvKDx90SAjxxKTw+ovDyg9Lr2X08P+Hm6w91NsvnlKkn47fZKjUD1726pGIwmlFfXoKzKhPKqGpRX1YaO8qoam8v1lUaUVdegpb4J5e4yKD3d4XftGOqOxe93y36/Tmm13B0+Cnco3GWtHhQcCUONDQw1RERtR1dpxK85OpzI0eFsQSkyLpcjo7Csxa9otCQPN+l3IaR+GFHWCyq/tVF61f6scGe/opbWnO9v9zaqiYiIXIjKywNDooMwJDrIskwIgSvl1cgrMSCnpBJ5ukqUVBihqzRCbzBCX1l7y0dXaUSpwYga82+jampH2dTe9hIQkLv94ZbLtZ8V7jL4Ktzho3CDj8L92s/X/iv/bZnvH0OJpwevkDgBhhoiImoTkiQhyFeBIF8FYjuq7F0OOaH21VuLiIiI6AYx1BAREZFTYKghIiIip9DsUJOcnIyxY8dCo9FAkiRs2bLFav2mTZswatQoBAYGQpIkpKWl1dtGQkICJEmyes2dO7fR/QohsGTJEoSFhcHLywsjR47EuXPnmls+EREROalmh5ry8nLExcVh9erVDa6/44478Oqrrza6ndmzZyMvL8/yeu211xpt/9prr+Htt9/GmjVrcPDgQfj4+GD06NEwGAzNPQQiIiJyQs0e/ZSYmIjExMQG1z/yyCMAgKysrEa34+3tDbVa3aR9CiHw5ptv4oUXXsD48eMBAJ999hlCQ0OxZcsWTJ06tWnFExERkdOyW5+a9evXIygoCL169cKiRYtQUVHRYNvMzEzk5+dj5MiRlmUqlQoDBw5ESkqKzc9UVVVBr9dbvYiIiMh52WWemoceegiRkZHQaDQ4ceIEFi5cCK1Wi02bNtlsn5+fDwAIDQ21Wh4aGmpZ90crVqzA8uXLW7ZwIiIiarfsEmrmzJlj+Tk2NhZhYWEYMWIEMjIy0KVLlxbZx6JFi7BgwQLLe71ej/Dw8BbZNhEREbU/7WJI98CBAwEA6enpNtfX9b0pKCiwWl5QUNBgvxyFQgGlUmn1IiIiIufVLkJN3bDvsLAwm+ujoqKgVquxe/duyzK9Xo+DBw9i8ODBbVEiERERtXPNvv1UVlZmdUUlMzMTaWlpCAgIQEREBIqLi5GdnY3c3FwAgFarBVB7tUWtViMjIwMbNmzAPffcg8DAQJw4cQLz58/H0KFD0bt3b8t2Y2JisGLFCkycOBGSJOHZZ5/FP/7xD3Tt2hVRUVFYvHgxNBoNJkyYcJOngIiIiJyCaKa9e/cKAPVeM2fOFEIIsW7dOpvrly5dKoQQIjs7WwwdOlQEBAQIhUIhoqOjxfPPPy90Op3VfgCIdevWWd6bzWaxePFiERoaKhQKhRgxYoTQarVNrlun0wkA9fZDRERE7Vdzvr8lIYSwS5pqY3q9HiqVCjqdjv1riIiIHERzvr/tMvrJHuqyG+erISIichx139tNuQbjMqGmtLQUADism4iIyAGVlpZCpVI12sZlbj+ZzWbk5ubCz88PkiS16Lbr5sC5ePEib221EJ7T1sHz2vJ4Tlsez2nrcNTzKoRAaWkpNBoNZLLGB227zJUamUyGjh07tuo+OB9Oy+M5bR08ry2P57Tl8Zy2Dkc8r9e7QlOnXcxTQ0RERHSzGGqIiIjIKTDUtACFQoGlS5dCoVDYuxSnwXPaOnheWx7PacvjOW0drnBeXaajMBERETk3XqkhIiIip8BQQ0RERE6BoYaIiIicAkMNEREROQWGmiZavXo1OnXqBE9PTwwcOBCHDh2yd0kOZdmyZZAkyeoVExNj1cZgMGDevHkIDAyEr68vJk+ejIKCAjtV3P4kJydj7Nix0Gg0kCQJW7ZsqddGCIElS5YgLCwMXl5eGDlyJM6dO2fVpri4GNOnT4dSqYS/vz9mzZqFsrKyNjqK9qUp5/TRRx+t97s7ZswYqzY8p9ZWrFiB/v37w8/PDyEhIZgwYQK0Wq1Vm6b8ec/Ozsa9994Lb29vhISE4Pnnn0dNTU1bHkq70ZRzmpCQUO93de7cuVZtnP2cMtQ0wZdffokFCxZg6dKlOHr0KOLi4jB69GgUFhbauzSHcuuttyIvL8/yOnDggNX6+fPnY9u2bdi4cSP27duH3NxcTJo0yU7Vtj/l5eWIi4vD6tWrG2zz2muv4e2338aaNWtw8OBB+Pj4YPTo0TAYDJY206dPx6+//oqdO3di+/btSE5Oxpw5c9riENqdppxTABgzZozV7+7nn39utZ7n1Nq+ffswb948/Pzzz9i5cyeMRiNGjRqF8vJyS5vr/Xk3mUy49957UV1djZ9++gmffvopPvnkEyxZssQeh2R3TTmnADB79myr39XXXnvNss4lzqmg6xowYICYN2+e5b3JZBIajUasWLGiwc/s3btX9O/fX3h7ewuVSiWGDBkisrKy2qLcdmnp0qUiLi6uwfUlJSXCw8NDbNy40bLs9OnTAoBISUlp8HOrV68W0dHRQqFQiJCQEDF58uSWLLvdAiA2b95stcxsNgu1Wi1ef/11y7KSkhKhUCjE559/LoQQ4tSpUwKAOHz4sKXN999/LyRJEjk5OTb3ZTabxdKlS0V4eLiQy+UiLCxMPPXUUy1/UHZm65wKIcTMmTPF+PHjG/wcz+n1FRYWCgBi3759Qoim/Xn/7rvvhEwmE/n5+ZY277//vlAqlaKqqsrmfqqqqsS8efOEWq0WCoVCREREiFdeeaUVj8x+/nhOhRBi2LBh4plnnmnwM65wTnml5jqqq6uRmpqKkSNHWpbJZDKMHDkSKSkpNj9TU1ODCRMmYNiwYThx4gRSUlIwZ86cFn+QpqM5d+4cNBoNOnfujOnTpyM7O9uyLjU1FUaj0eo8x8TEICIiosHzfOTIETz99NN48cUXodVqsWPHDgwdOrTVj6O9yszMRH5+vtU5VKlUGDhwoOUcpqSkwN/fH/369bO0GTlyJGQyGQ4ePGhzu9988w1WrVqFDz74AOfOncOWLVsQGxvbugfTziQlJSEkJATdu3fHE088gStXrljW8Zxen06nAwAEBAQAaNqf95SUFMTGxiI0NNTSZvTo0dDr9fj1119t7uftt9/G1q1b8dVXX0Gr1WL9+vXo1KlTKx2Vff3xnNZZv349goKC0KtXLyxatAgVFRWWda5wTl3mgZY3qqioCCaTyeqXAABCQ0Nx5swZm5/R6/XQ6XS477770KVLFwBAjx49Wr3W9mzgwIH45JNP0L17d+Tl5WH58uW48847cfLkSfj5+SE/Px9yuRz+/v5WnwsNDUV+fr7NbWZnZ8PHxwf33Xcf/Pz8EBkZifj4+DY4mvap7jzZ+l2tW5efn4+QkBCr9e7u7ggICGj0PKvVaowcORIeHh6IiIjAgAEDWuEI2qcxY8Zg0qRJiIqKQkZGBv7+978jMTERKSkpcHNz4zm9DrPZjGeffRa33347evXqBQBN+vOen59v83e5bp0t2dnZ6Nq1K+644w5IkoTIyMgWPpr2wdY5BYCHHnoIkZGR0Gg0OHHiBBYuXAitVotNmzYBcI1zyis1rSAgIACPPvooRo8ejbFjx+Ktt95CXl6evcuyq8TERDzwwAPo3bs3Ro8eje+++w4lJSX46quvbnibd999NyIjI9G5c2c88sgjWL9+vdW/SqhlPPDAA6isrETnzp0xe/ZsbN682ak6Fl7P1KlTMW7cOMTGxmLChAnYvn07Dh8+jKSkpBvepiud03nz5uHkyZP44osvWn1fjz76KNLS0tC9e3c8/fTT+O9//9vq+7SHhs7pnDlzMHr0aMTGxmL69On47LPPsHnzZmRkZNzwvhztnDLUXEdQUBDc3Nzq9covKCiAWq1u8HPr1q1DSkoKhgwZgi+//BLdunXDzz//3NrlOgx/f39069YN6enpAAC1Wo3q6mqUlJRYtWvsPPv5+eHo0aP4/PPPERYWhiVLliAuLq7eNlxF3Xlq7HdVrVbX6+BeU1OD4uLiBs9zeHg4tFot3nvvPXh5eeEvf/kLhg4dCqPR2ApH0f517twZQUFBVr+7PKe2Pfnkk9i+fTv27t2Ljh07WpY35c+7Wq22+btct86W2267DZmZmXjppZdQWVmJKVOm4P7772/BI7K/hs6pLQMHDgQAq99Vpz+n9u7U4wgGDBggnnzySct7k8kkbrnllkY7Cv/RoEGDnLojYHOVlpaKDh06iLfeeksI8VvHwa+//trS5syZM9ftKPx7ZWVlwt3dXXzzzTetUnN7gkY6Cr/xxhuWZTqdzmZH4SNHjlja/PDDD412av2juv8vqampN38g7Yitc2rLxYsXhSRJ4ttvvxVC8JzaYjabxbx584RGoxFnz56tt74pf97rOrUWFBRY2nzwwQdCqVQKg8HQpDp27NghAIgrV67c5BHZ3/XOqS0HDhwQAMTx48eFEK5xThlqmuCLL74QCoVCfPLJJ+LUqVNizpw5wt/f36oH+e+dP39e/O1vfxM//fSTyMrKEj/88IMIDAwU7733XhtX3n4899xzIikpSWRmZooff/xRjBw5UgQFBYnCwkJLm7lz54qIiAixZ88eceTIETF48GAxePDgBre5bds28dZbb4ljx46JrKws8d577wmZTCZOnjzZFofU5kpLS8WxY8fEsWPHBADxr3/9Sxw7dkxcuHDB0mblypXC399ffPvtt+LEiRNi/PjxIioqSlRWVlrajBkzRsTHx4uDBw+KAwcOiK5du4pp06Y1uN9169aJf//73+KXX34RGRkZ4oUXXhBeXl6iqKioVY+3LVzvnJaWloq//vWvIiUlRWRmZopdu3aJ2267TXTt2tXqS4Dn1NoTTzwhVCqVSEpKEnl5eZZXRUWFpc31/rzX1NSIXr16iVGjRom0tDSxY8cOERwcLBYtWtTgfv/5z3+KDRs2iNOnTwutVitmzZol1Gq1MJlMrXq8beF65zQ9PV28+OKL4siRIyIzM1N8++23onPnzmLo0KGWbbjCOWWoaaJ33nlHRERECLlcLgYMGCB+/vnnBtvm5+eLCRMmiLCwMCGXy0VkZKRYsmRJu/0laAsPPvig5Xzccsst4sEHHxTp6elWbSorK8Vf/vIX0aFDB+Ht7S0mTpwo8vLyGtzm/v37xbBhw0SHDh2El5eX6N27t/jyyy9b+1DsZu/evQJAvdfMmTMtbcxms1i8eLEIDQ0VCoVCjBgxQmi1WqvtXLlyRUybNk34+voKpVIpHnvsMVFaWtrgfjdv3iwGDhwolEql8PHxEYMGDRK7du1qrcNsU9c7pxUVFWLUqFEiODhYeHh4iMjISDF79ux6/6DhObVm65wCEOvWrbO0acqf96ysLJGYmCi8vLxEUFCQeO6554TRaGxwvx9++KHo06eP8PHxEUqlUowYMUIcPXq0tQ6zTV3vnGZnZ4uhQ4eKgIAAoVAoRHR0tHj++eeFTqez2o6zn1NJCCFa+Q4XERERUatjR2EiIiJyCgw1RERE5BQYaoiIiMgpMNQQERGRU2CoISIiIqfAUENEREROgaGGiIiInAJDDRERETkFhhoicgiPPvooJkyYYO8yiKgdc7d3AUREkiQ1un7p0qV46623wAnQiagxDDVEZHd5eXmWn7/88kssWbIEWq3WsszX1xe+vr72KI2IHAhvPxGR3anVastLpVJBkiSrZb6+vvVuPyUkJOCpp57Cs88+iw4dOiA0NBQfffQRysvL8dhjj8HPzw/R0dH4/vvvrfZ18uRJJCYmwtfXF6GhoXjkkUdQVFTUxkdMRK2BoYaIHNann36KoKAgHDp0CE899RSeeOIJPPDAAxgyZAiOHj2KUaNG4ZFHHkFFRQUAoKSkBHfddRfi4+Nx5MgR7NixAwUFBZgyZYqdj4SIWgJDDRE5rLi4OLzwwgvo2rUrFi1aBE9PTwQFBWH27Nno2rUrlixZgitXruDEiRMAgHfffRfx8fF45ZVXEBMTg/j4eHz88cfYu3cvzp49a+ejIaKbxT41ROSwevfubfnZzc0NgYGBiI2NtSwLDQ0FABQWFgIAjh8/jr1799rsn5ORkYFu3bq1csVE1JoYaojIYXl4eFi9lyTJalndqCqz2QwAKCsrw9ixY/Hqq6/W21ZYWFgrVkpEbYGhhohcxm233YZvvvkGnTp1grs7//ojcjbsU0NELmPevHkoLi7GtGnTcPjwYWRkZOCHH37AY489BpPJZO/yiOgmMdQQkcvQaDT48ccfYTKZMGrUKMTGxuLZZ5+Fv78/ZDL+dUjk6CTBKTqJiIjICfCfJkREROQUGGqIiIjIKTDUEBERkVNgqCEiIiKnwFBDREREToGhhoiIiJwCQw0RERE5BYYaIiIicgoMNUREROQUGGqIiIjIKTDUEBERkVP4/xuw8cvSJq3sAAAAAElFTkSuQmCC", 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" ] @@ -4555,7 +331,8 @@ ], "source": [ "c = res.curves().plot()\n", - "c.set_xlabel('Time (ms)')\n", + "plt.gca().xaxis.set_major_formatter(lambda x, pos: '{:.0f} s'.format(x/1000))\n", + "c.set_xlabel('Time')\n", "plt.show()" ] }, @@ -4564,7 +341,7 @@ "metadata": {}, "source": [ "Comment on the result :\n", - "When adding a Tap Changer Blocking Automaton, that blocks the LTCs when the voltage at bus 1042 is below 120kV, the voltage collapse is avoided, as shown in the figure." + "When adding a Tap Changer Blocking automation system, that blocks the LTCs when the voltage at bus 1042 is below 120kV, the voltage collapse is avoided, as shown in the figure." ] } ], From 1f760a337304ae9e8fe726b3b5d77d76a7595dee Mon Sep 17 00:00:00 2001 From: lisrte Date: Wed, 12 Feb 2025 11:27:35 +0100 Subject: [PATCH 7/9] Use axes directly instead of pyplot Mutualize plot configuration in plot function Signed-off-by: lisrte --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 50 ++++++++++++----------- 1 file changed, 26 insertions(+), 24 deletions(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index e3c4530..64ac43d 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -72,27 +72,36 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pypowsybl as pp\n", "import pypowsybl.dynamic as dyn\n", "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", "import os.path\n", - "from pypowsybl_jupyter import display_nad" + "from pypowsybl_jupyter import display_nad\n", + "\n", + "def plot(df):\n", + " df.plot(xlabel='Time').xaxis.set_major_formatter(lambda x, pos: '{:.0f} s'.format(x/1000))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Load initial situation" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5553c204da48470c941f93591c6232d7", + "model_id": "c70975f73f56400dbdb07d2941360af0", "version_major": 2, "version_minor": 1 }, @@ -100,13 +109,12 @@ "NadWidget(diagram_data={'svg_data': '\\n" ] @@ -231,10 +239,7 @@ } ], "source": [ - "c = res.curves().plot()\n", - "plt.gca().xaxis.set_major_formatter(lambda x, pos: '{:.0f} s'.format(x/1000))\n", - "c.set_xlabel('Time')\n", - "plt.show()" + "plot(res.curves())" ] }, { @@ -261,7 +266,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -297,7 +302,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -315,7 +320,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -330,10 +335,7 @@ } ], "source": [ - "c = res.curves().plot()\n", - "plt.gca().xaxis.set_major_formatter(lambda x, pos: '{:.0f} s'.format(x/1000))\n", - "c.set_xlabel('Time')\n", - "plt.show()" + "plot(res.curves())" ] }, { From bb187a690026394c98008b4abc806c3b8e3a61bc Mon Sep 17 00:00:00 2001 From: Florian Dupuy Date: Fri, 14 Feb 2025 16:11:50 +0100 Subject: [PATCH 8/9] Add mybinder link Signed-off-by: Florian Dupuy --- README.md | 1 + dynawo/{nordic case => nordic_case}/Network.par | 0 dynawo/{nordic case => nordic_case}/Nordic.par | 0 dynawo/{nordic case => nordic_case}/Nordic.xiidm | 0 dynawo/{nordic case => nordic_case}/Solver.par | 0 dynawo/{nordic case => nordic_case}/config.yml | 0 dynawo/{nordic case => nordic_case}/pypowsybl_dynawo.ipynb | 0 7 files changed, 1 insertion(+) rename dynawo/{nordic case => nordic_case}/Network.par (100%) rename dynawo/{nordic case => nordic_case}/Nordic.par (100%) rename dynawo/{nordic case => nordic_case}/Nordic.xiidm (100%) rename dynawo/{nordic case => nordic_case}/Solver.par (100%) rename dynawo/{nordic case => nordic_case}/config.yml (100%) rename dynawo/{nordic case => nordic_case}/pypowsybl_dynawo.ipynb (100%) diff --git a/README.md b/README.md index bd8e82b..ebb95c5 100644 --- a/README.md +++ b/README.md @@ -7,6 +7,7 @@ - Network, load flow calculation, security analysis and sensitivity analysis [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=pypowsybl_lf_security_sensitivity_analysis.ipynb) - Operator strategy notebook: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=operator_strategy.ipynb) - Computation using Dynaflow : [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=dynaflow/pypowsybl_dynaflow.ipynb) +- Dynamic simulation using dynawo: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/dynawo_simulation_nordic_case?labpath=dynawo/nordic_case/pypowsybl_dynawo.ipynb) - Sensitivity analysis and PTDF calculation [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=sensitivity_analysis.ipynb) - Pypowsybl-Jupyter widgets notebook : [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=pypowsybl_jupyter_widgets_demo.ipynb) diff --git a/dynawo/nordic case/Network.par b/dynawo/nordic_case/Network.par similarity index 100% rename from dynawo/nordic case/Network.par rename to dynawo/nordic_case/Network.par diff --git a/dynawo/nordic case/Nordic.par b/dynawo/nordic_case/Nordic.par similarity index 100% rename from dynawo/nordic case/Nordic.par rename to dynawo/nordic_case/Nordic.par diff --git a/dynawo/nordic case/Nordic.xiidm b/dynawo/nordic_case/Nordic.xiidm similarity index 100% rename from dynawo/nordic case/Nordic.xiidm rename to dynawo/nordic_case/Nordic.xiidm diff --git a/dynawo/nordic case/Solver.par b/dynawo/nordic_case/Solver.par similarity index 100% rename from dynawo/nordic case/Solver.par rename to dynawo/nordic_case/Solver.par diff --git a/dynawo/nordic case/config.yml b/dynawo/nordic_case/config.yml similarity index 100% rename from dynawo/nordic case/config.yml rename to dynawo/nordic_case/config.yml diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic_case/pypowsybl_dynawo.ipynb similarity index 100% rename from dynawo/nordic case/pypowsybl_dynawo.ipynb rename to dynawo/nordic_case/pypowsybl_dynawo.ipynb From e23113ba2a9c437cdac6b1e260f96b0f898947cf Mon Sep 17 00:00:00 2001 From: lisrte Date: Tue, 25 Feb 2025 16:18:59 +0100 Subject: [PATCH 9/9] Review fix Signed-off-by: lisrte --- dynawo/nordic_case/config.yml | 8 +++--- dynawo/nordic_case/pypowsybl_dynawo.ipynb | 30 ++++++++++++++++++++--- 2 files changed, 30 insertions(+), 8 deletions(-) diff --git a/dynawo/nordic_case/config.yml b/dynawo/nordic_case/config.yml index 4627340..35df1ce 100644 --- a/dynawo/nordic_case/config.yml +++ b/dynawo/nordic_case/config.yml @@ -1,10 +1,10 @@ dynawo: - homeDir: /home/dynawo + homeDir: "WORKING_DIR/dynawo" dynawo-simulation-default-parameters: - parametersFile: Nordic.par - network.parametersFile: Network.par + parametersFile: "WORKING_DIR/Nordic.par" + network.parametersFile: "WORKING_DIR/Network.par" network.parametersId: "Network" solver.type: SIM - solver.parametersFile: Solvers.par + solver.parametersFile: "WORKING_DIR/Solver.par" solver.parametersId: "Solver" diff --git a/dynawo/nordic_case/pypowsybl_dynawo.ipynb b/dynawo/nordic_case/pypowsybl_dynawo.ipynb index 64ac43d..9b3c003 100644 --- a/dynawo/nordic_case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic_case/pypowsybl_dynawo.ipynb @@ -24,6 +24,16 @@ "## 1 - Dynawo install" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**For Windows**\n", + "Follow [this link](https://github.com/dynawo/dynawo?tab=readme-ov-file#installation) to install Dynawo.\n", + "**For Linux**\n", + "You can launch the following commands to download the latest distribution:" + ] + }, { "cell_type": "code", "execution_count": null, @@ -52,6 +62,20 @@ "pip install pypowsybl matplotlib pypowsybl-jupyter" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `config.yml` file provided with the notebook has to be edited for some properties:\n", + "- `dynawo/homeDir` with the Dynawo installation path\n", + "- `dynawo-simulation-default-parameters` properties with the path of the provided parameters files:\n", + " - `parametersFile` with `Nordic.par`\n", + " - `network.parametersFile` with `Network.par`\n", + " - `solver.parametersFile` with the path of `Solver.par`\n", + "\n", + "For Linux users, you can run the following commands:" + ] + }, { "cell_type": "code", "execution_count": null, @@ -60,6 +84,7 @@ "source": [ "!mkdir /home/$USER/.itools/\n", "!cp config.yml /home/$USER/.itools/\n", + "!sed -i \"s|WORKING_DIR|$(pwd)|g\" /home/$USER/.itools/config.yml\n", "!cat /home/$USER/.itools/config.yml" ] }, @@ -116,8 +141,6 @@ ], "source": [ "network = pp.network.load('Nordic.xiidm')\n", - "network.clone_variant('InitialState', 'BaseCase')\n", - "network.set_working_variant('BaseCase')\n", "display_nad(network.get_network_area_diagram())" ] }, @@ -306,8 +329,7 @@ "metadata": {}, "outputs": [], "source": [ - "network.clone_variant('InitialState', 'TCBCase')\n", - "network.set_working_variant('TCBCase')\n", + "network = pp.network.load('Nordic.xiidm')\n", "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 300)" ] },