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adding fdpf powerflow with tests see #63 and fix a bug with shunts
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| Original file line number | Diff line number | Diff line change |
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| # Copyright (c) 2023, RTE (https://www.rte-france.com) | ||
| # See AUTHORS.txt | ||
| # This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0. | ||
| # If a copy of the Mozilla Public License, version 2.0 was not distributed with this file, | ||
| # you can obtain one at http://mozilla.org/MPL/2.0/. | ||
| # SPDX-License-Identifier: MPL-2.0 | ||
| # This file is part of LightSim2grid, LightSim2grid implements a c++ backend targeting the Grid2Op platform. | ||
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| import warnings | ||
| import numpy as np | ||
| from scipy.sparse import csc_matrix | ||
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| from lightsim2grid_cpp import FDPFMethod | ||
| from lightsim2grid.gridmodel import init | ||
| from lightsim2grid.solver import SolverType | ||
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| import pandapower.networks as pn | ||
| import pandapower as pp | ||
| from pandapower.pypower.makeB import makeB | ||
| from pandapower.pf.ppci_variables import _get_pf_variables_from_ppci | ||
| from pandapower.pd2ppc import _pd2ppc | ||
| from pandapower.auxiliary import _init_runpp_options | ||
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| import unittest | ||
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| class BaseFDPFTester: | ||
| def get_solving_method(self): | ||
| return FDPFMethod.XB | ||
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| def get_algo_pp(self): | ||
| # return "fdxb" if self.fdpf_meth == FDPFMethod.XB else "fdbx" # in theory | ||
| return "fdbx" if self.fdpf_meth == FDPFMethod.XB else "fdxb" # but.... https://github.com/e2nIEE/pandapower/issues/2142 | ||
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| def get_network(self): | ||
| return pn.case14() | ||
| # self.net = pn.case118() | ||
| # self.net = pn.case300() | ||
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| def get_pp_options(self): | ||
| return dict(algorithm=self.get_algo_pp(), | ||
| calculate_voltage_angles="auto", | ||
| init="flat", | ||
| max_iteration="auto", | ||
| tolerance_mva=1e-8, | ||
| trafo_model="t", | ||
| trafo_loading="current", | ||
| enforce_q_lims=False, | ||
| check_connectivity=True, | ||
| voltage_depend_loads=True, | ||
| consider_line_temperature=False, | ||
| run_control=False, | ||
| distributed_slack=False, | ||
| tdpf=False, | ||
| tdpf_delay_s=None) | ||
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| def setUp(self) -> None: | ||
| self.net = self.get_network() | ||
| with warnings.catch_warnings(): | ||
| warnings.filterwarnings("ignore") | ||
| self.gridmodel = init(self.net) | ||
| self.tol = 1e-7 | ||
| self.tol_solver = 1e-8 | ||
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| # XB | ||
| self.fdpf_meth = self.get_solving_method() | ||
| self.alg = 2 if self.fdpf_meth == FDPFMethod.XB else 3 | ||
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| # alg = 3 # BX # TODO later | ||
| # self.fdpf_meth = FDPFMethod.BX # TODO later | ||
| return super().setUp() | ||
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| def _aux_get_Bp_Bpp(self): | ||
| # init pp options | ||
| _init_runpp_options(self.net, **self.get_pp_options()) | ||
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| # clear lookups | ||
| self.net._pd2ppc_lookups = {"bus": np.array([], dtype=np.int64), "ext_grid": np.array([], dtype=np.int64), | ||
| "gen": np.array([], dtype=np.int64), "branch": np.array([], dtype=np.int64)} | ||
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| # convert pandapower net to ppc | ||
| ppc, ppci = _pd2ppc(self.net) | ||
| self.net["_ppc"] = ppc | ||
| baseMVA, bus, gen, branch, svc, tcsc, ref, pv, pq, *_, gbus, V0, ref_gens = _get_pf_variables_from_ppci(ppci) | ||
| pp_Bp, pp_Bpp = makeB(baseMVA, bus, np.real(branch), self.alg) | ||
| return pp_Bp, pp_Bpp, pv, pq, V0 | ||
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| def test_bp_bpp(self): | ||
| """test that Bp and Bpp are correct (from the grid)""" | ||
| pp_Bp, pp_Bpp, *_= self._aux_get_Bp_Bpp() | ||
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| # now get the matrices | ||
| self.gridmodel.ac_pf(1.04 * np.ones(self.net.bus.shape[0], dtype=complex), 10, 1e-7) # need to init the "model bus id" id_grid_to_solver | ||
| ls_Bp = self.gridmodel.debug_get_Bp_python(self.fdpf_meth) | ||
| ls_Bpp = self.gridmodel.debug_get_Bpp_python(self.fdpf_meth) | ||
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| assert np.abs(pp_Bp - ls_Bp).max() <= self.tol, f"error in Bp: max {np.abs(pp_Bp - ls_Bp).max():.2e}" | ||
| assert np.abs(pp_Bpp - ls_Bpp).max() <= self.tol, f"error in Bpp: max {np.abs(pp_Bpp - ls_Bpp).max():.2e}" | ||
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| def test_Bp_Bpp_solver(self): | ||
| """test that Bp and Bpp are correct (from the solver: where only some indices are used)""" | ||
| # retrieve the matrix in the solver | ||
| self.gridmodel.change_solver(SolverType.FDPF_XB_SparseLU if self.fdpf_meth == FDPFMethod.XB else SolverType.FDPF_BX_SparseLU) | ||
| V_ls = self.gridmodel.ac_pf(1.04 * np.ones(self.net.bus.shape[0], dtype=complex), 30, 1e0) # to ensure it can "converge" to be able to retrieve Bp and Bpp | ||
| used_solver = self.gridmodel.get_solver().get_fdpf_xb_lu() if self.fdpf_meth == FDPFMethod.XB else self.gridmodel.get_solver().get_fdpf_bx_lu() | ||
| ls_Bp = used_solver.debug_get_Bp_python() | ||
| ls_Bpp = used_solver.debug_get_Bpp_python() | ||
| # recreate the matrices from pandapower | ||
| grid_Bp, grid_Bpp, pv, pq, *_ = self._aux_get_Bp_Bpp() | ||
| pvpq = np.r_[pv, pq] | ||
| pp_Bp = grid_Bp[np.array([pvpq]).T, pvpq].tocsc() | ||
| pp_Bpp = grid_Bpp[np.array([pq]).T, pq].tocsc() | ||
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| # check they match | ||
| assert np.abs(pp_Bp - ls_Bp).max() <= self.tol, f"error in Bp: max {np.abs(pp_Bp - ls_Bp).max():.2f}" | ||
| assert np.abs(pp_Bpp - ls_Bpp).max() <= self.tol, f"error in Bpp: max {np.abs(pp_Bpp - ls_Bpp).max():.2f}" | ||
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| def test_solver(self): | ||
| self.gridmodel.change_solver(SolverType.FDPF_XB_SparseLU if self.fdpf_meth == FDPFMethod.XB else SolverType.FDPF_BX_SparseLU) | ||
| *_, V0 = self._aux_get_Bp_Bpp() | ||
| V_ls = self.gridmodel.ac_pf(1. * V0, 30, self.tol_solver * self.gridmodel.get_sn_mva()) # no division by sn_mva in pypower implementation TODO issue ! | ||
| pp.runpp(self.net, algorithm=self.get_algo_pp(), tol=self.tol_solver, init="flat") | ||
| assert V_ls.size > 0, f"lightsim2grid powerflow has diverged {self.gridmodel.get_solver().get_error()}" | ||
| nb_iter_ls = self.gridmodel.get_solver().get_nb_iter() | ||
| nb_iter_pp = self.net._ppc['iterations'] | ||
| assert nb_iter_pp == nb_iter_ls, f"mismatch nb_iter {nb_iter_pp} vs {nb_iter_ls} maybe https://github.com/e2nIEE/pandapower/issues/2142 has been fixed ?" | ||
| V_pp = self.net.res_bus["vm_pu"].values * np.exp(1j * np.deg2rad(self.net.res_bus["va_degree"].values)) | ||
| assert np.abs(V_ls - V_pp).max() <= self.tol, f"mismatch in V: {np.abs(V_ls - V_pp).max():.2e}" | ||
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| class FDPFTester_Case14_XB(BaseFDPFTester, unittest.TestCase): | ||
| pass | ||
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| class FDPFTester_Case14_BX(BaseFDPFTester, unittest.TestCase): | ||
| def get_solving_method(self): | ||
| return FDPFMethod.BX | ||
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| class FDPFTester_Case118_XB(BaseFDPFTester, unittest.TestCase): | ||
| def get_network(self): | ||
| return pn.case118() | ||
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| class FDPFTester_Case118_BX(BaseFDPFTester, unittest.TestCase): | ||
| def get_network(self): | ||
| return pn.case118() | ||
| def get_solving_method(self): | ||
| return FDPFMethod.BX | ||
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| class FDPFTester_Case300_XB(BaseFDPFTester, unittest.TestCase): | ||
| def get_network(self): | ||
| return pn.case300() | ||
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| class FDPFTester_Case300_BX(BaseFDPFTester, unittest.TestCase): | ||
| def get_network(self): | ||
| return pn.case300() | ||
| def get_solving_method(self): | ||
| return FDPFMethod.BX | ||
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| if __name__ == "__main__": | ||
| unittest.main() |
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