def __init__(self, pll=None, pdroop=None, qdroop=None, **kwargs):
super().__init__(**kwargs)
pdroop = {**dict(gain=40000.0), **(pdroop or {})}
qdroop = {**dict(gain=50.0), **(qdroop or {})}
pll = {**dict(kP=10, kI=200), **(pll or {})}
# toDo: set time Constant for droop Filter correct
self.pdroop_ctl = InverseDroopController(
InverseDroopParams(tau=self.net.ts, nom_value=self.net.freq_nom, **pdroop), self.net.ts)
self.qdroop_ctl = InverseDroopController(
InverseDroopParams(tau=self.net.ts, nom_value=self.net.v_nom, **qdroop), self.net.ts)
# default pll params and new ones
self.pll = PLL(PLLParams(f_nom=self.net.freq_nom, **pll), self.net.ts)
qdroop_param = DroopParams(QDroopGain, 0.002, v_nom)
# Add to dict
ctrl.append(
MultiPhaseDQ0PIPIController(voltage_dqp_iparams,
current_dqp_iparams,
droop_param,
qdroop_param,
ts_sim=delta_t,
name='master'))
#####################################
# Define the current sourcing inverter as slave
# Current control PI gain parameters for the current sourcing inverter
current_dqp_iparams = PI_params(kP=0.005, kI=200, limits=(-1, 1))
# PI gain parameters for the PLL in the current forming inverter
pll_params = PLLParams(kP=10, kI=200, limits=None, f_nom=freq_nom)
# Droop characteristic for the active power Watts/Hz, W.s/Hz
droop_param = InverseDroopParams(DroopGain,
delta_t,
freq_nom,
tau_filt=0.04)
# Droop characteristic for the reactive power VAR/Volt Var.s/Volt
qdroop_param = InverseDroopParams(50, delta_t, v_nom, tau_filt=0.01)
# Add to dict
ctrl.append(
MultiPhaseDQCurrentController(current_dqp_iparams,
pll_params,
i_lim,
droop_param,
qdroop_param,
ts_sim=delta_t,
###############
# define Master
voltage_dqp_iparams = PI_params(kP=0.025, kI=60, limits=(-i_lim, i_lim))
# Current control PI gain parameters for the voltage sourcing inverter
current_dqp_iparams = PI_params(kP=0.012, kI=90, limits=(-1, 1))
# Define a current sourcing inverter as master inverter using the pi and droop parameters from above
ctrl.append(MultiPhaseDQ0PIPIController(voltage_dqp_iparams, current_dqp_iparams, droop_param_master,
qdroop_param_master, ts_sim=delta_t, ts_ctrl=2 * delta_t, name='master'))
###############
# define slave
current_dqp_iparams = PI_params(kP=0.005, kI=200, limits=(-1, 1))
# PI gain parameters for the PLL in the current forming inverter
pll_params = PLLParams(kP=10, kI=200, limits=(-10000, 10000), f_nom=freq_nom)
# Droop characteristic for the active power Watts/Hz, W.s/Hz
# Add to dict
ctrl.append(MultiPhaseDQCurrentController(current_dqp_iparams, pll_params, i_lim, droop_param_slave,
qdroop_param_slave, ts_sim=delta_t, name='slave'))
#####################################
# Definition of the optimization agent
# The agent is using the SafeOpt algorithm by F. Berkenkamp (https://arxiv.org/abs/1509.01066) in this example
# Arguments described above
# History is used to store results
agent = SafeOptAgent(mutable_params,
abort_reward,
j_min,
kernel,