# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at https://mozilla.org/MPL/2.0/.
# SPDX-License-Identifier: MPL-2.0
import numpy as np
from VeraGridEngine.Devices.Dynamic.var_factory import VarFactory
from VeraGridEngine.Utils.Symbolic import symbolic as sym
from VeraGridEngine.enumerations import DeviceType, VarPowerFlowReferenceType
from VeraGridEngine.Devices.Dynamic.rms_template import RmsModelTemplate
[docs]
def get_genrow1_rms_template(var_factory: VarFactory, name="Genrow rms template") -> RmsModelTemplate:
"""
Get the RMS template model of the Genrow
:return: RmsModelTemplate
"""
templ = RmsModelTemplate()
templ.tpe = DeviceType.GeneratorDevice
templ.name = name
inputs = [var_factory.add_var("Vm_" + name, reference=VarPowerFlowReferenceType.Vm),
var_factory.add_var("Va_" + name, reference=VarPowerFlowReferenceType.Va)]
P_g = var_factory.add_var('P_g')
Q_g = var_factory.add_var('Q_g')
delta = var_factory.add_var("delta")
omega = var_factory.add_var("omega")
psid = var_factory.add_var("psid")
psiq = var_factory.add_var("psiq")
i_d = var_factory.add_var("i_d")
i_q = var_factory.add_var("i_q")
v_d = var_factory.add_var("v_d")
v_q = var_factory.add_var("v_q")
te = var_factory.add_var("te")
et = var_factory.add_var("et")
tm = var_factory.add_var("tm")
R1 = var_factory.add_var("R1")
X1 = var_factory.add_var("X1")
freq = var_factory.add_var("frequ")
M = var_factory.add_var("M")
D = var_factory.add_var("D")
omega_ref = var_factory.add_var("omega_ref")
Kp = var_factory.add_var("Kp")
Ki = var_factory.add_var("Ki")
vf = var_factory.add_var("vf")
tm0 = var_factory.add_var("tm0")
templ.block.event_dict[R1] = var_factory.add_const(0.0)
templ.block.event_dict[X1] = var_factory.add_const(0.3 * 100.0 / 900.0)
templ.block.event_dict[freq] = var_factory.add_const(60.0)
templ.block.event_dict[M] = var_factory.add_const(13.0 * 9.0)
templ.block.event_dict[D] = var_factory.add_const(10.0 * 9.0)
templ.block.event_dict[omega_ref] = var_factory.add_const(1.0)
templ.block.event_dict[Kp] = var_factory.add_const(0.0)
templ.block.event_dict[Ki] = var_factory.add_const(0.0)
templ.block.event_dict[vf] = psid + X1 * i_d
templ.block.event_dict[tm0] = tm
templ.block.algebraic_vars = [P_g, Q_g, v_d, v_q, i_d, i_q, psid, psiq, te, tm, et]
templ.block.algebraic_eqs = [
psid - (R1 * i_q + v_q),
psiq + (R1 * i_d + v_d),
0 - (psid + X1 * i_d - vf),
0 - (psiq + X1 * i_q),
v_d - (inputs[0] * sym.sin(delta - inputs[1])),
v_q - (inputs[0] * sym.cos(delta - inputs[1])),
te - (psid * i_q - psiq * i_d),
P_g - (v_d * i_d + v_q * i_q),
Q_g - (v_q * i_d - v_d * i_q),
tm - (tm0 + Kp * (omega - omega_ref) + Ki * et),
2 * np.pi * freq * et - delta,
]
templ.block.state_vars = [delta, omega]
templ.block.state_eqs = [
(2 * np.pi * freq) * (omega - omega_ref),
(tm - te - D * (omega - omega_ref)) / M,
]
templ.block.init_eqs = {
delta: sym.imag(
sym.log((inputs[0] * sym.exp(1j * inputs[1]) + (R1 + 1j * X1) * (
sym.conj((P_g + 1j * Q_g) / (inputs[0] * sym.exp(1j * inputs[1]))))) / (
sym.abs(inputs[0] * sym.exp(1j * inputs[1]) + (R1 + 1j * X1) * (
sym.conj((P_g + 1j * Q_g) / (inputs[0] * sym.exp(1j * inputs[1])))))))),
omega: omega_ref,
v_d: sym.real((inputs[0] * sym.exp(1j * inputs[1])) * sym.exp(-1j * (delta - np.pi / 2))),
v_q: sym.imag((inputs[0] * sym.exp(1j * inputs[1])) * sym.exp(-1j * (delta - np.pi / 2))),
i_d: sym.real(
sym.conj((P_g + 1j * Q_g) / (inputs[0] * sym.exp(1j * inputs[1]))) * sym.exp(-1j * (delta - np.pi / 2))),
i_q: sym.imag(
sym.conj((P_g + 1j * Q_g) / (inputs[0] * sym.exp(1j * inputs[1]))) * sym.exp(-1j * (delta - np.pi / 2))),
psid: R1 * i_q + v_q,
psiq: -R1 * i_d - v_d,
te: psid * i_q - psiq * i_d,
tm: te,
et: delta / (2 * np.pi * freq),
}
templ.block.external_mapping = {
VarPowerFlowReferenceType.Vm: inputs[0],
VarPowerFlowReferenceType.Va: inputs[1],
VarPowerFlowReferenceType.P: P_g,
VarPowerFlowReferenceType.Q: Q_g
}
templ.block.in_vars = inputs
templ.block.out_vars = [P_g, Q_g]
return templ