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