def init(self):
"""
Initialize the status, storage and values for TDS.
Returns
-------
array-like
The initial values of xy.
"""
t0, _ = elapsed()
system = self.system
if self.initialized:
return system.dae.xy
self._reset()
self._load_pert()
system.set_address(models=system.exist.tds)
system.set_dae_names(models=system.exist.tds)
system.dae.clear_ts()
system.store_sparse_pattern(models=system.exist.pflow_tds)
system.store_adder_setter(models=system.exist.pflow_tds)
system.vars_to_models()
system.init(system.exist.tds)
system.store_switch_times(system.exist.tds)
self.eye = spdiag([1] * system.dae.n)
self.Teye = spdiag(system.dae.Tf.tolist()) * self.eye
self.qg = np.zeros(system.dae.n + system.dae.m)
self.calc_h()
self.initialized = self.test_init()
_, s1 = elapsed(t0)
if self.initialized is True:
logger.info(f"Initialization was successful in {s1}.")
else:
logger.error(f"Initialization failed in {s1}.")
if system.dae.n == 0:
tqdm.write('No dynamic component loaded.')
return system.dae.xy
def init(self):
"""
Initialize the status, storage and values for TDS.
Returns
-------
array-like
The initial values of xy.
"""
t0, _ = elapsed()
system = self.system
if self.initialized:
return system.dae.xy
self._reset()
self._load_pert()
# Note:
# calling `set_address` on `system.exist.pflow_tds` will point all variables
# to the new array after extending `dae.y`
system.set_address(models=system.exist.pflow_tds)
system.set_dae_names(models=system.exist.tds)
system.dae.clear_ts()
system.store_sparse_pattern(models=system.exist.pflow_tds)
system.store_adder_setter(models=system.exist.pflow_tds)
system.vars_to_models()
# Initialize `system.exist.tds` only to avoid Bus overwriting power flow solutions
system.init(system.exist.tds)
system.store_switch_times(system.exist.tds)
# Build mass matrix into `self.Teye`
self.Teye = spdiag(system.dae.Tf.tolist())
self.qg = np.zeros(system.dae.n + system.dae.m)
self.initialized = self.test_init()
# if `dae.n == 1`, `calc_h_first` depends on new `dae.gy`
self.calc_h()
_, s1 = elapsed(t0)
if self.initialized is True:
logger.info(f"Initialization was successful in {s1}.")
else:
logger.error(f"Initialization failed in {s1}.")
if system.dae.n == 0:
tqdm.write('No dynamic component loaded.')
return system.dae.xy
def _calc_state_matrix(self, fx, fy, gx, gy, Tf, dense=True):
"""
Kernel function for calculating state matrix.
"""
gyx = matrix(gx)
self.solver.linsolve(gy, gyx)
Tfnz = Tf + np.ones_like(Tf) * np.equal(Tf, 0.0)
iTf = spdiag((1 / Tfnz).tolist())
if dense:
return iTf * (fx - fy * gyx)
else:
return sparse(iTf * (fx - fy * gyx))
def _reduce(self, fx, fy, gx, gy, Tf, dense=True):
"""
Reduce algebraic equations (or states associated with zero time constants).
Returns
-------
spmatrix
The reduced state matrix
"""
gyx = matrix(gx)
self.solver.linsolve(gy, gyx)
Tfnz = Tf + np.ones_like(Tf) * np.equal(Tf, 0.0)
iTf = spdiag((1 / Tfnz).tolist())
if dense:
return iTf * (fx - fy * gyx)
else:
return sparse(iTf * (fx - fy * gyx))
def init(self):
"""
Initialize the status, storage and values for TDS.
Returns
-------
array-like
The initial values of xy.
"""
t0, _ = elapsed()
system = self.system
if self.initialized:
return system.dae.xy
self.reset()
self._load_pert()
# restore power flow solutions
system.dae.x[:len(system.PFlow.x_sol)] = system.PFlow.x_sol
system.dae.y[:len(system.PFlow.y_sol)] = system.PFlow.y_sol
# Note:
# calling `set_address` on `system.exist.pflow_tds` will point all variables
# to the new array after extending `dae.y`.
system.set_address(models=system.exist.pflow_tds)
system.set_dae_names(models=system.exist.tds)
system.dae.clear_ts()
system.store_sparse_pattern(models=system.exist.pflow_tds)
system.store_adder_setter(models=system.exist.pflow_tds)
system.store_no_check_init(models=system.exist.pflow_tds)
system.vars_to_models()
system.init(system.exist.tds, routine='tds')
# only store switch times when not replaying CSV data
if self.data_csv is None:
system.store_switch_times(system.exist.tds)
# Build mass matrix into `self.Teye`
self.Teye = spdiag(system.dae.Tf.tolist())
self.qg = np.zeros(system.dae.n + system.dae.m)
self.initialized = True
# test if residuals are close enough to zero
if self.config.test_init:
self.test_ok = self.test_init()
# discard initialized values and use that from CSV if provided
if self.data_csv is not None:
system.dae.x[:] = self.data_csv[0, 1:system.dae.n + 1]
system.dae.y[:] = self.data_csv[0, system.dae.n + 1:system.dae.n + system.dae.m + 1]
system.vars_to_models()
# connect to data streaming server
if system.streaming.dimec is None:
system.streaming.connect()
if system.config.dime_enabled:
# send out system data using DiME
self.streaming_init()
self.streaming_step()
# if `dae.n == 1`, `calc_h_first` depends on new `dae.gy`
self.calc_h()
# allocate for internal variables
self.x0 = np.zeros_like(system.dae.x)
self.y0 = np.zeros_like(system.dae.y)
self.f0 = np.zeros_like(system.dae.f)
_, s1 = elapsed(t0)
logger.info("Initialization for dynamics completed in %s.", s1)
if self.test_ok is True:
logger.info("Initialization was successful.")
elif self.test_ok is False:
logger.error("Initialization failed!!")
else:
logger.warning("Initialization results were not verified.")
if system.dae.n == 0:
tqdm.write('No differential equation detected.')
return system.dae.xy
def _implicit_step(self):
"""
Integrate for a single given step.
This function has an internal Newton-Raphson loop for algebraized semi-explicit DAE.
The function returns the convergence status when done but does NOT progress simulation time.
Returns
-------
bool
Convergence status in ``self.converged``.
"""
system = self.system
dae = self.system.dae
self.mis = []
self.niter = 0
self.converged = False
self.x0 = np.array(dae.x)
self.y0 = np.array(dae.y)
self.f0 = np.array(dae.f)
while True:
system.e_clear(models=self.pflow_tds_models)
system.l_update_var(models=self.pflow_tds_models)
system.f_update(models=self.pflow_tds_models)
system.g_update(models=self.pflow_tds_models)
system.l_check_eq(models=self.pflow_tds_models)
system.l_set_eq(models=self.pflow_tds_models)
system.fg_to_dae()
# lazy jacobian update
if dae.t == 0 or self.niter > 3 or (dae.t - self._last_switch_t < 0.2):
system.j_update(models=self.pflow_tds_models)
self.solver.factorize = True
# solve trapezoidal rule integration
In = spdiag([1] * dae.n)
self.Ac = sparse([[In - self.h * 0.5 * dae.fx, dae.gx],
[-self.h * 0.5 * dae.fy, dae.gy]], 'd')
# reset q as well
q = dae.x - self.x0 - self.h * 0.5 * (dae.f + self.f0)
for item in system.antiwindups:
if len(item.x_set) > 0:
for key, val in item.x_set:
np.put(q, key[np.where(item.zi == 0)], 0)
qg = np.hstack((q, dae.g))
inc = self.solver.solve(self.Ac, -matrix(qg))
# check for np.nan first
if np.isnan(inc).any():
logger.error(f'NaN found in solution. Convergence not likely')
self.niter = self.config.max_iter + 1
self.busted = True
break
# reset really small values to avoid anti-windup limiter flag jumps
inc[np.where(np.abs(inc) < 1e-12)] = 0
# set new values
dae.x += np.ravel(np.array(inc[:dae.n]))
dae.y += np.ravel(np.array(inc[dae.n: dae.n + dae.m]))
system.vars_to_models()
# calculate correction
mis = np.max(np.abs(inc))
self.mis.append(mis)
self.niter += 1
# converged
if mis <= self.config.tol:
self.converged = True
break
# non-convergence cases
if self.niter > self.config.max_iter:
logger.debug(f'Max. iter. {self.config.max_iter} reached for t={dae.t:.6f}, '
f'h={self.h:.6f}, mis={mis:.4g} '
f'({system.dae.xy_name[np.argmax(inc)]})')
break
if mis > 1000 and (mis > 1e8 * self.mis[0]):
logger.error(f'Error increased too quickly. Convergence not likely.')
self.busted = True
break
if not self.converged:
dae.x = np.array(self.x0)
dae.y = np.array(self.y0)
dae.f = np.array(self.f0)
system.vars_to_models()
return self.converged
def init(self):
"""
Initialize the status, storage and values for TDS.
Returns
-------
array-like
The initial values of xy.
"""
t0, _ = elapsed()
system = self.system
if self.initialized:
return system.dae.xy
self.reset()
self._load_pert()
# restore power flow solutions
system.dae.x[:len(system.PFlow.x_sol)] = system.PFlow.x_sol
system.dae.y[:len(system.PFlow.y_sol)] = system.PFlow.y_sol
# Note:
# calling `set_address` on `system.exist.pflow_tds` will point all variables
# to the new array after extending `dae.y`
system.set_address(models=system.exist.pflow_tds)
system.set_dae_names(models=system.exist.tds)
system.dae.clear_ts()
system.store_sparse_pattern(models=system.exist.pflow_tds)
system.store_adder_setter(models=system.exist.pflow_tds)
system.vars_to_models()
system.init(system.exist.tds, routine='tds')
system.store_switch_times(system.exist.tds)
# Build mass matrix into `self.Teye`
self.Teye = spdiag(system.dae.Tf.tolist())
self.qg = np.zeros(system.dae.n + system.dae.m)
self.initialized = self.test_init()
# connect to dime server
if system.config.dime_enabled:
if system.streaming.dimec is None:
system.streaming.connect()
# send out system data using DiME
self.streaming_init()
self.streaming_step()
# if `dae.n == 1`, `calc_h_first` depends on new `dae.gy`
self.calc_h()
_, s1 = elapsed(t0)
if self.initialized is True:
logger.info(f"Initialization for dynamics was successful in {s1}.")
else:
logger.error(f"Initialization for dynamics failed in {s1}.")
if system.dae.n == 0:
tqdm.write('No dynamic component loaded.')
return system.dae.xy