.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "drive_examples/grid_connection/plot_2kw_ipmsm_afe_dvf_cvc.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_drive_examples_grid_connection_plot_2kw_ipmsm_afe_dvf_cvc.py: 2.2-kW IPMSM, dual-voltage-forming AFE, CVC =========================================== This example simulates a 2.2-kW interior permanent-magnet synchronous machine (IPMSM) drive whose active front end (AFE) uses dual-voltage-forming control [#Mou2025]_ and is connected to a weak grid. The grid-side converter regulates both the DC-bus voltage and its output voltage magnitude without a cascaded DC-bus voltage controller: the external power fed to the DC bus by the drive is estimated by a disturbance observer and fed forward. The machine-side converter uses sensorless current-vector control (CVC). The two control systems are independent: they have different sampling periods, and their carriers are not synchronized. The system model is otherwise the same as in :doc:`/drive_examples/grid_connection/plot_2kw_ipmsm_afe_cvc`, except for the weak grid. .. GENERATED FROM PYTHON SOURCE LINES 18-30 .. code-block:: Python from math import pi import matplotlib.pyplot as plt import motulator.drive.control.sm as sm_control from motulator.common.model import CompositeModel, DCBus, Simulation, ThreePhaseSource from motulator.drive import model as drive_model from motulator.drive import utils as drive_utils from motulator.grid import control as grid_control from motulator.grid import model as grid_model from motulator.grid import utils as grid_utils .. GENERATED FROM PYTHON SOURCE LINES 31-32 Compute base values based on the nominal values of the machine and the grid converter. .. GENERATED FROM PYTHON SOURCE LINES 32-38 .. code-block:: Python nom_m = drive_utils.NominalValues(U=370, I=4.3, f=75, P=2.2e3, tau=14) base_m = drive_utils.BaseValues.from_nominal(nom_m, n_p=3) nom_g = grid_utils.NominalValues(U=400, I=5, f=50, P=2.2e3) base_g = grid_utils.BaseValues.from_nominal(nom_g) .. GENERATED FROM PYTHON SOURCE LINES 39-41 Configure the system model. The two converters are fed from the same DC bus. The grid is weak: its inductance is 0.74 p.u. .. GENERATED FROM PYTHON SOURCE LINES 41-61 .. code-block:: Python afe = grid_model.VoltageSourceConverter(modulator=grid_model.CarrierComparison()) inv = drive_model.VoltageSourceConverter(modulator=drive_model.CarrierComparison()) dc_bus = DCBus(C_dc=470e-6, u_dc=650) ac_filter = grid_model.LFilter( L_f=0.15 * base_g.L, R_f=0.05 * base_g.Z, L_g=0.74 * base_g.L ) ac_source = ThreePhaseSource(w_g=base_g.w, e_g=base_g.u) grid_sys = grid_model.GridConverterSystem(afe, ac_filter, ac_source, dc_bus=dc_bus) par = drive_model.SynchronousMachinePars( n_p=3, R_s=3.6, L_d=0.036, L_q=0.051, psi_f=0.545 ) machine = drive_model.SynchronousMachine(par) mechanics = drive_model.MechanicalSystem(J=0.015) drive_sys = drive_model.Drive(machine, mechanics, inv, dc_bus=dc_bus) mdl = CompositeModel({"grid": grid_sys, "drive": drive_sys}) .. GENERATED FROM PYTHON SOURCE LINES 62-66 Configure the control systems. The grid-side control runs at 10 kHz (5-kHz switching frequency) and the machine-side control at 8 kHz (4-kHz switching frequency). The gains of the dual-voltage-forming controller are given in per-unit values of the grid converter [#Mou2025]_. .. GENERATED FROM PYTHON SOURCE LINES 66-94 .. code-block:: Python cfg_g = grid_control.DualVoltageFormingControllerCfg( i_max=1.5 * base_g.i, L=0.3 * base_g.L, C_dc=470e-6, R=0.05 * base_g.Z, k_d=base_g.u / base_g.p, alpha_dc=0.15 * base_g.w, alpha_o=2 * base_g.w, alpha_o_dc=1.2 * base_g.w, k_v=6, alpha_c=6 * base_g.w, u_nom=base_g.u, w_nom=base_g.w, T_s=100e-6, ) ctrl_g = grid_control.GridConverterControlSystem( grid_control.DualVoltageFormingController(cfg_g) ) est_par = par # Assume accurate model parameter estimates cfg_m = sm_control.CurrentVectorControllerCfg( i_s_max=1.5 * base_m.i, alpha_o=2 * pi * 100, T_s=125e-6 ) vector_ctrl = sm_control.CurrentVectorController(est_par, cfg_m) speed_ctrl = sm_control.SpeedController(J=0.015, alpha_s=2 * pi * 4) ctrl_m = sm_control.VectorControlSystem(vector_ctrl, speed_ctrl) .. GENERATED FROM PYTHON SOURCE LINES 95-97 Set the references and the external load torque. The speed is reversed under load, after which the drive regenerates power to the grid. .. GENERATED FROM PYTHON SOURCE LINES 97-103 .. code-block:: Python ctrl_g.set_dc_bus_voltage_ref(650) ctrl_g.set_ac_voltage_ref(base_g.u) ctrl_m.set_speed_ref(lambda t: (t > 0.1) * base_m.w_M - (t > 0.7) * 2 * base_m.w_M) mechanics.set_external_load_torque(lambda t: (t > 0.4) * nom_m.tau) .. GENERATED FROM PYTHON SOURCE LINES 104-107 Create the simulation object and simulate. The clocks of the two control systems are not synchronized: the machine-side control starts 40 µs after the grid-side control. The results of each model and its control system are available by the model names. .. GENERATED FROM PYTHON SOURCE LINES 107-113 .. code-block:: Python sim = Simulation(mdl, {"grid": ctrl_g, "drive": ctrl_m}, t_start={"drive": 40e-6}) res = sim.simulate(t_stop=1) res_drive = drive_model.SimulationResults(res.mdl.drive, res.ctrl.drive) res_grid = grid_model.SimulationResults(res.mdl.grid, res.ctrl.grid) .. GENERATED FROM PYTHON SOURCE LINES 114-117 Plot the drive and grid-side results in per-unit values. The active power reference shown is the equivalent reference formed by the dual-voltage-forming controller from the estimated external power and the DC-bus energy error. .. GENERATED FROM PYTHON SOURCE LINES 117-122 .. code-block:: Python # sphinx_gallery_thumbnail_number = 3 drive_utils.plot(res_drive, base_m) grid_utils.plot_control_signals(res_grid, base_g) .. rst-class:: sphx-glr-horizontal * .. image-sg:: /drive_examples/grid_connection/images/sphx_glr_plot_2kw_ipmsm_afe_dvf_cvc_001.png :alt: plot 2kw ipmsm afe dvf cvc :srcset: /drive_examples/grid_connection/images/sphx_glr_plot_2kw_ipmsm_afe_dvf_cvc_001.png :class: sphx-glr-multi-img * .. image-sg:: /drive_examples/grid_connection/images/sphx_glr_plot_2kw_ipmsm_afe_dvf_cvc_002.png :alt: plot 2kw ipmsm afe dvf cvc :srcset: /drive_examples/grid_connection/images/sphx_glr_plot_2kw_ipmsm_afe_dvf_cvc_002.png :class: sphx-glr-multi-img .. GENERATED FROM PYTHON SOURCE LINES 123-128 Plot the DC-bus voltage and the power balance: the estimated external power fed to the DC bus (the estimated disturbance power plus the grid power and the resistive losses of the filter) follows the mechanical power plus the losses (mainly the stator resistive losses), and the power drawn from the grid follows it with the delay of the current dynamics in the weak grid. .. GENERATED FROM PYTHON SOURCE LINES 128-154 .. code-block:: Python ctrl_ts = res.ctrl.grid p_loss = 1.5 * cfg_g.R * abs(ctrl_ts.fbk.i_c) ** 2 p_ext = ctrl_ts.fbk.p_dis + ctrl_ts.fbk.p_g + p_loss p_M = res.mdl.drive.machine.tau_M * res.mdl.drive.machine.w_M fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True) ax1.plot(res.mdl.t, res.mdl.drive.dc_bus.u_dc, label=r"$u_\mathrm{dc}$") ax1.plot( ctrl_ts.t, ctrl_ts.ref.u_dc, "--", ds="steps-post", label=r"$u_\mathrm{dc}^\mathrm{ref}$", ) ax1.set_ylabel("Voltage (V)") ax1.legend() ax2.plot(ctrl_ts.t, -p_ext / 1e3, ds="steps-post", label=r"$-\hat{p}_\mathrm{ext}$") ax2.plot( ctrl_ts.t, -ctrl_ts.fbk.p_g / 1e3, ds="steps-post", label=r"$-\hat{p}_\mathrm{g}$" ) ax2.plot(res.mdl.t, p_M / 1e3, label=r"$\tau_\mathrm{M}\omega_\mathrm{M}$") ax2.set_ylabel("Power (kW)") ax2.set_xlabel("Time (s)") ax2.legend() plt.show() .. image-sg:: /drive_examples/grid_connection/images/sphx_glr_plot_2kw_ipmsm_afe_dvf_cvc_003.png :alt: plot 2kw ipmsm afe dvf cvc :srcset: /drive_examples/grid_connection/images/sphx_glr_plot_2kw_ipmsm_afe_dvf_cvc_003.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 155-157 Plot the grid-side waveforms around the load torque step. The converter current increases within a few milliseconds, as the estimated external power is fed forward. .. GENERATED FROM PYTHON SOURCE LINES 157-162 .. code-block:: Python grid_utils.plot_grid_waveforms( res_grid, base_g, t_lims=(0.39, 0.45), plot_pcc_voltage=False ) .. image-sg:: /drive_examples/grid_connection/images/sphx_glr_plot_2kw_ipmsm_afe_dvf_cvc_004.png :alt: plot 2kw ipmsm afe dvf cvc :srcset: /drive_examples/grid_connection/images/sphx_glr_plot_2kw_ipmsm_afe_dvf_cvc_004.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 163-168 .. rubric:: References .. [#Mou2025] Mourouvin, Nurminen, Hinkkanen, Routimo, "Direct DC-bus control for grid-forming converters: Toward the concept of dual-voltage-forming converters," IEEE Trans. Power Electron., 2025, https://doi.org/10.1109/TPEL.2025.3537332 .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 51.666 seconds) .. _sphx_glr_download_drive_examples_grid_connection_plot_2kw_ipmsm_afe_dvf_cvc.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_2kw_ipmsm_afe_dvf_cvc.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_2kw_ipmsm_afe_dvf_cvc.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_2kw_ipmsm_afe_dvf_cvc.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_