def check_var(self, dae_t, *args, **kwargs):
# Storage:
# Output values is in the first col.
# Latest values are stored in /appended to the last column
self.rewind = False
if dae_t == 0:
self._v_mem[:] = self.u.v[:, None]
elif dae_t < self.t[-1]:
self.rewind = True
self.t[-1] = dae_t
self._v_mem[:, -1] = self.u.v
elif dae_t == self.t[-1]:
self._v_mem[:, -1] = self.u.v
elif dae_t > self.t[-1]:
if self.mode == 'step':
self.t[:-1] = self.t[1:]
self.t[-1] = dae_t
self._v_mem[:, :-1] = self._v_mem[:, 1:]
self._v_mem[:, -1] = self.u.v
else:
self.t = np.append(self.t, dae_t)
self._v_mem = np.hstack((self._v_mem, self.u.v[:, None]))
if dae_t - self.t[0] > self.delay:
t_interp = dae_t - self.delay
idx = np.argmax(self.t >= t_interp) - 1
v_interp = interp_n2(t_interp, self.t[idx:idx + 2],
self._v_mem[:, idx:idx + 2])
self.t[idx] = t_interp
self._v_mem[:, idx] = v_interp
self.t = np.delete(self.t, np.arange(0, idx))
self._v_mem = np.delete(self._v_mem,
np.arange(0, idx),
axis=1)
self.v[:] = self._v_mem[:, 0]
def run(self, **kwargs):
succeed = False
system = self.system
self.singular_idx = np.array([], dtype=int)
if system.PFlow.converged is False:
logger.warning(
'Power flow not solved. Eig analysis will not continue.')
return succeed
else:
if system.TDS.initialized is False:
system.TDS.init()
system.TDS._itm_step()
if system.dae.n == 0:
logger.error('No dynamic model. Eig analysis will not continue.')
else:
if sum(system.dae.Tf != 0) != len(system.dae.Tf):
self.singular_idx = np.argwhere(np.equal(
system.dae.Tf, 0.0)).ravel().astype(int)
logger.info(
f"System contains {len(self.singular_idx)} zero time constants. "
)
logger.debug([system.dae.x_name[i] for i in self.singular_idx])
self.x_name = np.array(system.dae.x_name)
self.x_name = np.delete(self.x_name, self.singular_idx)
self.summary()
t1, s = elapsed()
self.calc_state_matrix()
self.remove_singular_rc()
self.calc_part_factor()
if not self.system.files.no_output:
self.report()
if system.options.get('state_matrix') is True:
self.export_state_matrix()
if self.config.plot:
self.plot()
_, s = elapsed(t1)
logger.info('Eigenvalue analysis finished in {:s}.'.format(s))
succeed = True
system.exit_code = 0 if succeed else 1
return succeed
def remove_singular_rc(self):
"""
Remove rows and cols associated with zero time constant.
"""
self.As = np.delete(self.As, self.singular_idx, axis=0)
self.As = np.delete(self.As, self.singular_idx, axis=1)