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add validation notebooks for PF using matpower reader
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Signed-off-by: martin.moraga <[email protected]>
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martinmoraga committed Jan 16, 2024
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286 changes: 286 additions & 0 deletions examples/Notebooks/MatDyn/case14_PF.ipynb
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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# IEEE14 Powerflow"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Run simulation"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Import Libraries"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys, os\n",
"\n",
"notebook_dir = os.path.abspath('')\n",
"dpsim_root_dir = os.path.join(notebook_dir, \"../../..\")\n",
"\n",
"sys.path.insert(0, os.path.join(dpsim_root_dir, 'python/src/dpsim'))\n",
"sys.path.insert(0, os.path.join(dpsim_root_dir, 'build'))\n",
"\n",
"import matpower\n",
"import dpsimpy\n",
"\n",
"from villas.dataprocessing.readtools import *\n",
"from villas.dataprocessing.timeseries import *\n",
"import urllib.request\n",
"import matplotlib.pyplot as plt"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Simulation parameters"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# simulation files\n",
"path_static_file = './IEEE14/ieee14.mat'"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1. Powerflow for initialization"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"sim_name_pf = 'IEEE14_PF'\n",
"dpsimpy.Logger.set_log_dir('logs/' + sim_name_pf)\n",
"\n",
"# read and create dpsim topology\n",
"mpc_reader = matpower.Reader(mpc_file_path=path_static_file, mpc_name='ieee14')\n",
"mpc_reader.load_mpc(domain=matpower.Domain.PF)\n",
"system_pf = mpc_reader.system\n",
"\n",
"# log results\n",
"logger = dpsimpy.Logger(sim_name_pf)\n",
"for node in system_pf.nodes:\n",
" logger.log_attribute(node.name()+'.V', 'v', node)\n",
" logger.log_attribute(node.name()+'.S', 's', node)\n",
"\n",
"# Parametrize and run simulation\n",
"sim_pf = dpsimpy.Simulation(sim_name_pf, dpsimpy.LogLevel.info)\n",
"sim_pf.set_system(system_pf)\n",
"sim_pf.set_time_step(0.1)\n",
"sim_pf.set_final_time(0.1)\n",
"sim_pf.set_domain(dpsimpy.Domain.SP)\n",
"sim_pf.set_solver(dpsimpy.Solver.NRP)\n",
"sim_pf.do_init_from_nodes_and_terminals(False)\n",
"sim_pf.set_solver_component_behaviour(dpsimpy.SolverBehaviour.Initialization)\n",
"sim_pf.add_logger(logger)\n",
"sim_pf.run()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Read pf results"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dpsim_result_file = 'logs/' + sim_name_pf + '/' + sim_name_pf + '.csv'\n",
"ts_dpsim_pf = read_timeseries_csv(dpsim_result_file)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### DPsim results"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dpsim_results = pd.DataFrame(columns=['Bus', 'Vm [pu]', 'Va [°]', 'P [MW]', 'Q [MVAr]'])\n",
"base_power = 100 #mw\n",
"for i in range(len(system_pf.nodes)):\n",
" node_name = system_pf.nodes[i].name() #ex. N5\n",
" node_number = node_name.replace('N', '')\n",
" node_baseV = mpc_reader.mpc_bus_data.loc[mpc_reader.mpc_bus_data['bus_i'] == int(node_number), 'baseKV'].iloc[0] * 1e3\n",
" w_mw = 1e-6\n",
" dpsim_results.loc[i] = ([node_name] + [round(np.absolute(ts_dpsim_pf[node_name + '.V'].values[-1]) / node_baseV, 5)]\n",
" + [round(np.angle(ts_dpsim_pf[node_name + '.V'].values[-1])*180/np.pi, 5)] \n",
" + [round(w_mw * np.real(ts_dpsim_pf[node_name + '.S'].values[-1]), 5)] \n",
" + [round(w_mw * np.imag(ts_dpsim_pf[node_name + '.S'].values[-1]), 5)])\n",
"\n",
"dpsim_results"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Validate Results against PSAT"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"### PSAT Results\n",
"voltage_mag = np.array([1.06, 1.045, 1.01, 1.0186, 1.0203, 1.07, 1.062, 1.09, 1.0564, 1.0513, 1.0571, 1.0552, 1.0504, 1.0358])\n",
"voltage_angle = np.array([0, -0.08693, -0.22197, -0.18019, -0.15328, -0.24823, -0.23332, -0.23332, -0.26087, -0.26362, -0.25823, -0.26315, -0.26457, -0.27993])\n",
"p_loads = np.array([0, 0.217, 0.942, 0.478, 0.076, 0.112, 0, 0, 0.295, 0.09, 0.035, 0.061, 0.135, 0.149])\n",
"q_loads = np.array([0, 0.127, 0.19, -0.039, 0.016, 0.075, 0, 0, -0.04601, 0.058, 0.018, 0.016, 0.058, 0.05])\n",
"p_gen = np.array([2.3239, 0.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])\n",
"q_gen = np.array([-0.16889, 0.42396, 0.23394, 0, 0, 0.1224, 0, 0.17357, 0, 0, 0, 0, 0, 0])\n",
"busses = [\"N1\", \"N2\", \"N3\", \"N4\", \"N5\", \"N6\", \"N7\", \"N8\", \"N9\", \"N10\", \"N11\", \"N12\", \"N13\", \"N14\"]\n",
"d = {\"Bus\": busses, \"V_mag(pu)\": voltage_mag, \"V_angle(deg)\": voltage_angle, \"P(pu)\": -p_loads+p_gen, \"Q(pu)\": -q_loads+q_gen}\n",
"psat_results = pd.DataFrame(d)\n",
"\n",
"psat_results"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Matpower results"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"matpower_pf_results = mpc_reader.get_pf_results()\n",
"matpower_pf_results"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Difference"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"difference_vmag = matpower_pf_results['Vm [pu]'] - dpsim_results['Vm [pu]']\n",
"difference_vangle = matpower_pf_results['Va [°]'] - dpsim_results['Va [°]']\n",
"\n",
"#base power = 100MW\n",
"difference_p = (matpower_pf_results['P [MW]'] - dpsim_results['P [MW]'])\n",
"difference_q = (matpower_pf_results['Q [MVAr]'] - dpsim_results['Q [MVAr]'])\n",
"difference = {\"Bus\": matpower_pf_results['Bus'], \"V_mag [pu]\": difference_vmag, \"Va [°]\": difference_vangle, \"P [MW]\": difference_p, \"Q [MVAr]\": difference_q}\n",
"difference = pd.DataFrame(difference)\n",
"\n",
"difference"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Assertion"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"tolerance = 5e-5\n",
"\n",
"print(np.max(np.absolute(difference_p)))\n",
"assert(np.all(np.absolute(difference_p)<tolerance))\n",
"\n",
"print(np.max(np.absolute(difference_q)))\n",
"assert(np.all(np.absolute(difference_q)<tolerance))\n",
"\n",
"print(np.max(np.absolute(difference_vmag)))\n",
"assert(np.all(np.absolute(difference_vmag)<tolerance))\n",
"\n",
"print(np.max(np.absolute(difference_vangle)))\n",
"assert(np.all(np.absolute(difference_vangle)<tolerance))"
]
}
],
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"nbformat": 4,
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