def test_power_flow(): fname = Path(__file__).parent.parent.parent / \ 'Grids_and_profiles' / 'grids' / 'IEEE 30 Bus with storage.xlsx' print('Reading...') main_circuit = FileOpen(fname).open() options = PowerFlowOptions(SolverType.NR, verbose=False, initialize_with_existing_solution=False, multi_core=False, dispatch_storage=True, control_q=ReactivePowerControlMode.NoControl, control_p=True) # exit() #################################################################################################################### # PowerFlowDriver #################################################################################################################### print('\n\n') power_flow = PowerFlowDriver(main_circuit, options) power_flow.run() print('\n\n', main_circuit.name) print('\t|V|:', abs(power_flow.results.voltage)) print('\t|Sbranch|:', abs(power_flow.results.Sbranch)) print('\t|loading|:', abs(power_flow.results.loading) * 100) print('\tReport') print(power_flow.results.get_report_dataframe()) assert power_flow.results.error() < 1e-3
def test_ieee_grids(): """ Checks the .RAW files of IEEE grids against the PSS/e results This test checks 2 things: - PSS/e import fidelity - PSS/e vs GridCal results :return: Nothing if ok, fails if not """ files = [ ('IEEE 14 bus.raw', 'IEEE 14 bus.sav.xlsx'), ('IEEE 30 bus.raw', 'IEEE 30 bus.sav.xlsx'), ('IEEE 118 Bus v2.raw', 'IEEE 118 Bus.sav.xlsx'), ] for solver_type in [SolverType.NR, SolverType.IWAMOTO, SolverType.LM]: print(solver_type) options = PowerFlowOptions( solver_type, verbose=False, initialize_with_existing_solution=False, multi_core=False, dispatch_storage=True, control_q=ReactivePowerControlMode.NoControl, control_p=True, retry_with_other_methods=False) for f1, f2 in files: print(f1, end=' ') fname = os.path.join('data', 'grids', f1) main_circuit = FileOpen(fname).open() power_flow = PowerFlowDriver(main_circuit, options) power_flow.run() # load the associated results file df_v = pd.read_excel(os.path.join('data', 'results', f2), sheet_name='Vabs', index_col=0) df_p = pd.read_excel(os.path.join('data', 'results', f2), sheet_name='Pbranch', index_col=0) v_gc = np.abs(power_flow.results.voltage) v_psse = df_v.values[:, 0] p_gc = power_flow.results.Sf.real p_psse = df_p.values[:, 0] v_ok = np.allclose(v_gc, v_psse, atol=1e-3) flow_ok = np.allclose(p_gc, p_psse, atol=1e-0) assert (v_ok) assert (flow_ok) print(solver_type, 'ok')
def test_power_flow(): fname = Path(__file__).parent.parent.parent / \ 'Grids_and_profiles' / 'grids' / 'IEEE 5 Bus.xlsx' print('Reading...') main_circuit = FileOpen(fname).open() options = PowerFlowOptions(SolverType.NR, verbose=False, initialize_with_existing_solution=False, multi_core=False, dispatch_storage=True, control_q=ReactivePowerControlMode.Direct, control_p=True) # grid.export_profiles('ppppppprrrrroooofiles.xlsx') # exit() #################################################################################################################### # PowerFlowDriver #################################################################################################################### print('\n\n') power_flow = PowerFlowDriver(main_circuit, options) power_flow.run() main_circuit.build_graph() print('\n\n', main_circuit.name) print('\t|V|:', abs(power_flow.results.voltage)) print('\t|Sbranch|:', abs(power_flow.results.Sbranch)) print('\t|loading|:', abs(power_flow.results.loading) * 100) print('\tReport') print(power_flow.results.get_report_dataframe()) vc_options = VoltageCollapseOptions() numeric_circuit = main_circuit.compile() numeric_inputs = numeric_circuit.compute() Sbase = np.zeros(len(main_circuit.buses), dtype=complex) Vbase = np.zeros(len(main_circuit.buses), dtype=complex) for c in numeric_inputs: Sbase[c.original_bus_idx] = c.Sbus Vbase[c.original_bus_idx] = c.Vbus unitary_vector = -1 + 2 * np.random.random(len(main_circuit.buses)) vc_inputs = VoltageCollapseInput(Sbase=Sbase, Vbase=Vbase, Starget=Sbase * (1 + unitary_vector)) vc = VoltageCollapse(circuit=main_circuit, options=vc_options, inputs=vc_inputs) vc.run() mdl = vc.results.mdl() mdl.plot() plt.show()
def n_minus_k_mt(self, k=1, indices=None, vmin=200, states_number_limit=None): """ Run N-K simulation in series :param k: Parameter level (1 for n-1, 2 for n-2, etc...) :param indices: time indices {np.array([0])} :param vmin: minimum nominal voltage to allow (filters out branches and buses below) :param states_number_limit: limit the amount of states :return: Nothing, saves a report """ self.progress_text.emit("Filtering elements by voltage") # filter branches branch_names = list() branch_index = list() branches = list() # list of filtered branches for i, branch in enumerate(self.grid.branches): if branch.bus_from.Vnom > vmin or branch.bus_to.Vnom > vmin: branch_names.append(branch.name) branch_index.append(i) branches.append(branch) branch_index = np.array(branch_index) # filter buses bus_names = list() bus_index = list() for i, bus in enumerate(self.grid.buses): if bus.Vnom > vmin: bus_names.append(bus.name) bus_index.append(i) bus_index = np.array(bus_index) # get N-k states self.progress_text.emit("Enumerating states") states, failed_indices = enumerate_states_n_k(m=len(branch_names), k=k) # limit states for memory reasons if states_number_limit is not None: states = states[:states_number_limit, :] failed_indices = failed_indices[:states_number_limit] # compile the multi-circuit self.progress_text.emit("Compiling assets...") self.progress_signal.emit(0) numerical_circuit = self.grid.compile_time_series() # if no base profile time is given, pick the base values if indices is None: time_indices = np.array([0]) numerical_circuit.set_base_profile() else: time_indices = indices # re-index the profile (this is essential for time-compatibility) self.progress_signal.emit(100) # construct the profile indices profile_indices = np.tile(time_indices, len(states)) numerical_circuit.re_index_time(t_idx=profile_indices) # set the branch states numerical_circuit.branch_active_prof[:, branch_index] = np.tile(states, (len(time_indices), 1)) # initialize the power flow pf_options = PowerFlowOptions(solver_type=SolverType.LACPF) # initialize the grid time series results we will append the island results with another function n = len(self.grid.buses) m = self.circuit.get_branch_number() nt = len(profile_indices) n_k_results = NMinusKResults(n, m, nt, time_array=numerical_circuit.time_array, states=states) # do the topological computation self.progress_text.emit("Compiling topology...") self.progress_signal.emit(0.0) calc_inputs_dict = numerical_circuit.compute(ignore_single_node_islands=pf_options.ignore_single_node_islands) n_k_results.bus_types = numerical_circuit.bus_types # for each partition of the profiles... self.progress_text.emit("Simulating states...") for t_key, calc_inputs in calc_inputs_dict.items(): # For every island, run the time series for island_index, calculation_input in enumerate(calc_inputs): # find the original indices bus_original_idx = calculation_input.original_bus_idx branch_original_idx = calculation_input.original_branch_idx # if there are valid profiles... if self.grid.time_profile is not None: # declare a results object for the partition # nt = calculation_input.ntime nt = len(calculation_input.original_time_idx) n = calculation_input.nbus m = calculation_input.nbr partial_results = NMinusKResults(n, m, nt) last_voltage = calculation_input.Vbus # traverse the time profiles of the partition and simulate each time step for it, t in enumerate(calculation_input.original_time_idx): self.progress_signal.emit(it / nt * 100.0) # set the power values # if the storage dispatch option is active, the batteries power is not included # therefore, it shall be included after processing Ysh = calculation_input.Ysh_prof[:, it] I = calculation_input.Ibus_prof[:, it] S = calculation_input.Sbus_prof[:, it] branch_rates = calculation_input.branch_rates_prof[it, :] # run power flow at the circuit res = single_island_pf(circuit=calculation_input, Vbus=last_voltage, Sbus=S, Ibus=I, branch_rates=branch_rates, options=pf_options, logger=self.logger) # Recycle voltage solution last_voltage = res.voltage # store circuit results at the time index 't' partial_results.set_at(it, res) # merge the circuit's results n_k_results.apply_from_island(partial_results, bus_original_idx, branch_original_idx, calculation_input.original_time_idx, 'TS') else: self.progress_text.emit('There are no profiles') self.logger.append('There are no profiles') return n_k_results
if __name__ == '__main__': import os import pandas as pd from GridCal.Engine import FileOpen, SolverType # fname = '/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/Lynn 5 Bus pv.gridcal' # fname = '/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/IEEE39_1W.gridcal' # fname = '/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/grid_2_islands.xlsx' # fname = '/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/2869 Pegase.gridcal' fname = os.path.join('..', '..', '..', '..', '..', 'Grids_and_profiles', 'grids', 'IEEE 30 Bus with storage.xlsx') # fname = os.path.join('..', '..', '..', '..', '..', 'Grids_and_profiles', 'grids', '2869 Pegase.gridcal') main_circuit = FileOpen(fname).open() pf_options_ = PowerFlowOptions(solver_type=SolverType.LACPF) options_ = NMinusKOptions(use_multi_threading=False) simulation = NMinusK(grid=main_circuit, options=options_, pf_options=pf_options_) simulation.run() otdf_ = simulation.get_otdf() # save the result br_names = [b.name for b in main_circuit.branches] br_names2 = ['#' + b.name for b in main_circuit.branches] w = pd.ExcelWriter('OTDF IEEE30.xlsx') pd.DataFrame(data=simulation.results.Sbranch.real, columns=br_names, index=['base'] + br_names2).to_excel(w, sheet_name='branch power') pd.DataFrame(data=otdf_, columns=br_names,
def main(): #################################################################################################################### # Define the circuit # # A circuit contains all the grid information regardless of the islands formed or the amount of devices #################################################################################################################### # create a circuit grid = MultiCircuit(name='lynn 5 bus') # let's create a master profile st = datetime.datetime(2020, 1, 1) dates = [st + datetime.timedelta(hours=i) for i in range(24)] time_array = pd.to_datetime(dates) x = np.linspace(-np.pi, np.pi, len(time_array)) y = np.abs(np.sin(x)) df_0 = pd.DataFrame(data=y, index=time_array) # complex values # set the grid master time profile grid.time_profile = df_0.index #################################################################################################################### # Define the buses #################################################################################################################### # I will define this bus with all the properties so you see bus1 = Bus(name='Bus1', vnom=10, # Nominal voltage in kV vmin=0.9, # Bus minimum voltage in per unit vmax=1.1, # Bus maximum voltage in per unit xpos=0, # Bus x position in pixels ypos=0, # Bus y position in pixels height=0, # Bus height in pixels width=0, # Bus width in pixels active=True, # Is the bus active? is_slack=False, # Is this bus a slack bus? area='Defualt', # Area (for grouping purposes only) zone='Default', # Zone (for grouping purposes only) substation='Default' # Substation (for grouping purposes only) ) # the rest of the buses are defined with the default parameters bus2 = Bus(name='Bus2') bus3 = Bus(name='Bus3') bus4 = Bus(name='Bus4') bus5 = Bus(name='Bus5') # add the bus objects to the circuit grid.add_bus(bus1) grid.add_bus(bus2) grid.add_bus(bus3) grid.add_bus(bus4) grid.add_bus(bus5) #################################################################################################################### # Add the loads #################################################################################################################### # In GridCal, the loads, generators ect are stored within each bus object: # we'll define the first load completely l2 = Load(name='Load', G=0, B=0, # admittance of the ZIP model in MVA at the nominal voltage Ir=0, Ii=0, # Current of the ZIP model in MVA at the nominal voltage P=40, Q=20, # Power of the ZIP model in MVA active=True, # Is active? mttf=0.0, # Mean time to failure mttr=0.0 # Mean time to recovery ) grid.add_load(bus2, l2) # Define the others with the default parameters grid.add_load(bus3, Load(P=25, Q=15)) grid.add_load(bus4, Load(P=40, Q=20)) grid.add_load(bus5, Load(P=50, Q=20)) #################################################################################################################### # Add the generators #################################################################################################################### g1 = Generator(name='gen', active_power=0.0, # Active power in MW, since this generator is used to set the slack , is 0 voltage_module=1.0, # Voltage set point to control Qmin=-9999, # minimum reactive power in MVAr Qmax=9999, # Maximum reactive power in MVAr Snom=9999, # Nominal power in MVA power_prof=None, # power profile vset_prof=None, # voltage set point profile active=True # Is active? ) grid.add_generator(bus1, g1) #################################################################################################################### # Add the lines #################################################################################################################### br1 = Branch(bus_from=bus1, bus_to=bus2, name='Line 1-2', r=0.05, # resistance of the pi model in per unit x=0.11, # reactance of the pi model in per unit g=1e-20, # conductance of the pi model in per unit b=0.02, # susceptance of the pi model in per unit rate=50, # Rate in MVA tap=1.0, # Tap value (value close to 1) shift_angle=0, # Tap angle in radians active=True, # is the branch active? mttf=0, # Mean time to failure mttr=0, # Mean time to recovery branch_type=BranchType.Line, # Branch type tag length=1, # Length in km (to be used with templates) template=BranchTemplate() # Branch template (The default one is void) ) grid.add_branch(br1) grid.add_branch(Branch(bus1, bus3, name='Line 1-3', r=0.05, x=0.11, b=0.02, rate=50)) grid.add_branch(Branch(bus1, bus5, name='Line 1-5', r=0.03, x=0.08, b=0.02, rate=80)) grid.add_branch(Branch(bus2, bus3, name='Line 2-3', r=0.04, x=0.09, b=0.02, rate=3)) grid.add_branch(Branch(bus2, bus5, name='Line 2-5', r=0.04, x=0.09, b=0.02, rate=10)) grid.add_branch(Branch(bus3, bus4, name='Line 3-4', r=0.06, x=0.13, b=0.03, rate=30)) grid.add_branch(Branch(bus4, bus5, name='Line 4-5', r=0.04, x=0.09, b=0.02, rate=30)) FileSave(grid, 'lynn5node.gridcal').save() #################################################################################################################### # Overwrite the default profiles with the custom ones #################################################################################################################### for load in grid.get_loads(): load.P_prof = load.P * df_0.values[:, 0] load.Q_prof = load.Q * df_0.values[:, 0] for gen in grid.get_static_generators(): gen.P_prof = gen.Q * df_0.values[:, 0] gen.Q_prof = gen.Q * df_0.values[:, 0] for gen in grid.get_generators(): gen.P_prof = gen.P * df_0.values[:, 0] #################################################################################################################### # Run a power flow simulation #################################################################################################################### # We need to specify power flow options pf_options = PowerFlowOptions(solver_type=SolverType.NR, # Base method to use verbose=False, # Verbose option where available tolerance=1e-6, # power error in p.u. max_iter=25, # maximum iteration number control_q=True # if to control the reactive power ) # Declare and execute the power flow simulation pf = PowerFlowDriver(grid, pf_options) pf.run() writer = pd.ExcelWriter('Results.xlsx') # now, let's compose a nice DataFrame with the voltage results headers = ['Vm (p.u.)', 'Va (Deg)', 'Vre', 'Vim'] Vm = np.abs(pf.results.voltage) Va = np.angle(pf.results.voltage, deg=True) Vre = pf.results.voltage.real Vim = pf.results.voltage.imag data = np.c_[Vm, Va, Vre, Vim] v_df = pd.DataFrame(data=data, columns=headers, index=grid.bus_names) # print('\n', v_df) v_df.to_excel(writer, sheet_name='V') # Let's do the same for the branch results headers = ['Loading (%)', 'Current(p.u.)', 'Power (MVA)'] loading = np.abs(pf.results.loading) * 100 current = np.abs(pf.results.If) power = np.abs(pf.results.Sf) data = np.c_[loading, current, power] br_df = pd.DataFrame(data=data, columns=headers, index=grid.branch_names) br_df.to_excel(writer, sheet_name='Br') # Finally the execution metrics print('\nError:', pf.results.error) print('Elapsed time (s):', pf.results.elapsed, '\n') # print(tabulate(v_df, tablefmt="pipe", headers=v_df.columns.values)) # print() # print(tabulate(br_df, tablefmt="pipe", headers=br_df.columns.values)) #################################################################################################################### # Run a time series power flow simulation #################################################################################################################### ts = TimeSeries(grid=grid, options=pf_options, opf_time_series_results=None, start_=0, end_=None) ts.run() print() print('-' * 200) print('Time series') print('-' * 200) print('Voltage time series') df_voltage = pd.DataFrame(data=np.abs(ts.results.voltage), columns=grid.bus_names, index=grid.time_profile) df_voltage.to_excel(writer, sheet_name='Vts') writer.close()
""" run the voltage collapse simulation @return: """ print('Running voltage collapse...') # compile the numerical circuit numerical_circuit = compile_snapshot_circuit(self.circuit) evt = get_reliability_scenario(numerical_circuit) run_events(nc=numerical_circuit, events_list=evt) print('done!') self.progress_text.emit('Done!') self.done_signal.emit() def cancel(self): self.__cancel__ = True if __name__ == '__main__': from GridCal.Engine import * fname = '/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/IEEE 30 Bus with storage.xlsx' circuit_ = FileOpen(fname).open() study = ReliabilityStudy(circuit=circuit_, pf_options=PowerFlowOptions()) study.run()
def test_xfo_static_tap_1(): """ Basic test with the main transformer's HV tap (X_C3) set at +5% (1.05 pu), which lowers the LV by the same amount (-5%). """ test_name = "test_xfo_static_tap_1" grid = MultiCircuit(name=test_name) grid.Sbase = Sbase grid.time_profile = None grid.logger = Logger() # Create buses POI = Bus( name="POI", vnom=100, #kV is_slack=True) grid.add_bus(POI) B_C3 = Bus(name="B_C3", vnom=10) #kV grid.add_bus(B_C3) B_MV_M32 = Bus(name="B_MV_M32", vnom=10) #kV grid.add_bus(B_MV_M32) B_LV_M32 = Bus(name="B_LV_M32", vnom=0.6) #kV grid.add_bus(B_LV_M32) # Create voltage controlled generators (or slack, a.k.a. swing) UT = Generator(name="Utility") UT.bus = POI grid.add_generator(POI, UT) # Create static generators (with fixed power factor) M32 = StaticGenerator(name="M32", P=4.2, Q=0.0) # MVA (complex) M32.bus = B_LV_M32 grid.add_static_generator(B_LV_M32, M32) # Create transformer types s = 5 # MVA z = 8 # % xr = 40 SS = TransformerType( name="SS", hv_nominal_voltage=100, # kV lv_nominal_voltage=10, # kV nominal_power=s, copper_losses=complex_impedance(z, xr).real * s * 1000 / Sbase, iron_losses=6.25, # kW no_load_current=0.5, # % short_circuit_voltage=z) grid.add_transformer_type(SS) s = 5 # MVA z = 6 # % xr = 20 PM = TransformerType( name="PM", hv_nominal_voltage=10, # kV lv_nominal_voltage=0.6, # kV nominal_power=s, copper_losses=complex_impedance(z, xr).real * s * 1000 / Sbase, iron_losses=6.25, # kW no_load_current=0.5, # % short_circuit_voltage=z) grid.add_transformer_type(PM) # Create branches X_C3 = Branch(bus_from=POI, bus_to=B_C3, name="X_C3", branch_type=BranchType.Transformer, template=SS, tap=1.05) grid.add_branch(X_C3) C_M32 = Branch(bus_from=B_C3, bus_to=B_MV_M32, name="C_M32", r=0.784, x=0.174) grid.add_branch(C_M32) X_M32 = Branch(bus_from=B_MV_M32, bus_to=B_LV_M32, name="X_M32", branch_type=BranchType.Transformer, template=PM) grid.add_branch(X_M32) # Apply templates (device types) grid.apply_all_branch_types() print("Buses:") for i, b in enumerate(grid.buses): print(f" - bus[{i}]: {b}") print() options = PowerFlowOptions(SolverType.NR, verbose=True, initialize_with_existing_solution=True, multi_core=True, control_q=ReactivePowerControlMode.Direct, tolerance=1e-6, max_iter=99) power_flow = PowerFlowDriver(grid, options) power_flow.run() approx_volt = [round(100 * abs(v), 1) for v in power_flow.results.voltage] solution = [100.0, 94.7, 98.0, 98.1] # Expected solution from GridCal print() print(f"Test: {test_name}") print(f"Results: {approx_volt}") print(f"Solution: {solution}") print() print("Generators:") for g in grid.get_generators(): print(f" - Generator {g}: q_min={g.Qmin} MVAR, q_max={g.Qmax} MVAR") print() print("Branches:") for b in grid.branches: print(f" - {b}:") print(f" R = {round(b.R, 4)} pu") print(f" X = {round(b.X, 4)} pu") print(f" X/R = {round(b.X/b.R, 1)}") print(f" G = {round(b.G, 4)} pu") print(f" B = {round(b.B, 4)} pu") print() print("Transformer types:") for t in grid.transformer_types: print( f" - {t}: Copper losses={int(t.Pcu)}kW, Iron losses={int(t.Pfe)}kW, SC voltage={t.Vsc}%" ) print() print("Losses:") for i in range(len(grid.branches)): print( f" - {grid.branches[i]}: losses={1000*round(power_flow.results.losses[i], 3)} kVA" ) print() equal = True for i in range(len(approx_volt)): if approx_volt[i] != solution[i]: equal = False assert equal
def test_xfo_static_tap_3(): """ Basic test with the main transformer's HV tap (X_C3) set at -2.5% (0.975 pu), which raises the LV by the same amount (+2.5%). """ test_name = "test_xfo_static_tap_3" grid = MultiCircuit(name=test_name) grid.Sbase = Sbase grid.time_profile = None grid.logger = Logger() # Create buses POI = Bus( name="POI", vnom=100, # kV is_slack=True) grid.add_bus(POI) B_C3 = Bus(name="B_C3", vnom=10) # kV grid.add_bus(B_C3) B_MV_M32 = Bus(name="B_MV_M32", vnom=10) # kV grid.add_bus(B_MV_M32) B_LV_M32 = Bus(name="B_LV_M32", vnom=0.6) # kV grid.add_bus(B_LV_M32) # Create voltage controlled generators (or slack, a.k.a. swing) UT = Generator(name="Utility") UT.bus = POI grid.add_generator(POI, UT) # Create static generators (with fixed power factor) M32 = StaticGenerator(name="M32", P=4.2, Q=0.0) # MVA (complex) M32.bus = B_LV_M32 grid.add_static_generator(B_LV_M32, M32) # Create transformer types s = 5 # MVA z = 8 # % xr = 40 SS = TransformerType( name="SS", hv_nominal_voltage=100, # kV lv_nominal_voltage=10, # kV nominal_power=s, copper_losses=complex_impedance(z, xr).real * s * 1000 / Sbase, iron_losses=6.25, # kW no_load_current=0.5, # % short_circuit_voltage=z) grid.add_transformer_type(SS) s = 5 # MVA z = 6 # % xr = 20 PM = TransformerType( name="PM", hv_nominal_voltage=10, # kV lv_nominal_voltage=0.6, # kV nominal_power=s, copper_losses=complex_impedance(z, xr).real * s * 1000 / Sbase, iron_losses=6.25, # kW no_load_current=0.5, # % short_circuit_voltage=z) grid.add_transformer_type(PM) # Create branches X_C3 = Branch(bus_from=POI, bus_to=B_C3, name="X_C3", branch_type=BranchType.Transformer, template=SS, tap=0.975) # update to a more precise tap changer X_C3.apply_tap_changer( TapChanger(taps_up=20, taps_down=20, max_reg=1.1, min_reg=0.9)) grid.add_branch(X_C3) C_M32 = Branch(bus_from=B_C3, bus_to=B_MV_M32, name="C_M32", r=0.784, x=0.174) grid.add_branch(C_M32) X_M32 = Branch(bus_from=B_MV_M32, bus_to=B_LV_M32, name="X_M32", branch_type=BranchType.Transformer, template=PM) grid.add_branch(X_M32) # Apply templates (device types) grid.apply_all_branch_types() print("Buses:") for i, b in enumerate(grid.buses): print(f" - bus[{i}]: {b}") print() options = PowerFlowOptions(SolverType.NR, verbose=True, initialize_with_existing_solution=True, multi_core=True, control_q=ReactivePowerControlMode.Direct, tolerance=1e-6, max_iter=15) power_flow = PowerFlowDriver(grid, options) power_flow.run() print() print(f"Test: {test_name}") print() print("Generators:") for g in grid.get_generators(): print(f" - Generator {g}: q_min={g.Qmin} MVAR, q_max={g.Qmax} MVAR") print() print("Branches:") for b in grid.branches: print(f" - {b}:") print(f" R = {round(b.R, 4)} pu") print(f" X = {round(b.X, 4)} pu") print(f" X/R = {round(b.X/b.R, 1)}") print(f" G = {round(b.G, 4)} pu") print(f" B = {round(b.B, 4)} pu") print() print("Transformer types:") for t in grid.transformer_types: print(f" - {t}: Copper losses={int(t.Pcu)}kW, " f"Iron losses={int(t.Pfe)}kW, SC voltage={t.Vsc}%") print() print("Losses:") for i in range(len(grid.branches)): print( f" - {grid.branches[i]}: losses={1000*round(power_flow.results.losses[i], 3)} kVA" ) print() equal = False for i, branch in enumerate(grid.branches): if branch.name == "X_C3": equal = power_flow.results.tap_module[i] == branch.tap_module if not equal: grid.export_pf(f"{test_name}_results.xlsx", power_flow.results) grid.save_excel(f"{test_name}_grid.xlsx") assert equal
def test_gridcal_regulator(): """ GridCal test for the new implementation of transformer voltage regulators. """ test_name = "test_gridcal_regulator" grid = MultiCircuit(name=test_name) grid.Sbase = 100.0 # MVA grid.time_profile = None grid.logger = Logger() # Create buses POI = Bus( name="POI", vnom=100, # kV is_slack=True) grid.add_bus(POI) B_C3 = Bus(name="B_C3", vnom=10) # kV grid.add_bus(B_C3) B_MV_M32 = Bus(name="B_MV_M32", vnom=10) # kV grid.add_bus(B_MV_M32) B_LV_M32 = Bus(name="B_LV_M32", vnom=0.6) # kV grid.add_bus(B_LV_M32) # Create voltage controlled generators (or slack, a.k.a. swing) UT = Generator(name="Utility") UT.bus = POI grid.add_generator(POI, UT) # Create static generators (with fixed power factor) M32 = StaticGenerator(name="M32", P=4.2, Q=0.0) # MVA (complex) M32.bus = B_LV_M32 grid.add_static_generator(B_LV_M32, M32) # Create transformer types s = 100 # MVA z = 8 # % xr = 40 SS = TransformerType( name="SS", hv_nominal_voltage=100, # kV lv_nominal_voltage=10, # kV nominal_power=s, # MVA copper_losses=complex_impedance(z, xr).real * s * 1000.0 / grid.Sbase, # kW iron_losses=125, # kW no_load_current=0.5, # % short_circuit_voltage=z) # % grid.add_transformer_type(SS) s = 5 # MVA z = 6 # % xr = 20 PM = TransformerType( name="PM", hv_nominal_voltage=10, # kV lv_nominal_voltage=0.6, # kV nominal_power=s, # MVA copper_losses=complex_impedance(z, xr).real * s * 1000.0 / grid.Sbase, # kW iron_losses=6.25, # kW no_load_current=0.5, # % short_circuit_voltage=z) # % grid.add_transformer_type(PM) # Create branches X_C3 = Branch(bus_from=POI, bus_to=B_C3, name="X_C3", branch_type=BranchType.Transformer, template=SS, bus_to_regulated=True, vset=1.05) X_C3.tap_changer = TapChanger(taps_up=16, taps_down=16, max_reg=1.1, min_reg=0.9) X_C3.tap_changer.set_tap(X_C3.tap_module) grid.add_branch(X_C3) C_M32 = Branch(bus_from=B_C3, bus_to=B_MV_M32, name="C_M32", r=7.84, x=1.74) grid.add_branch(C_M32) X_M32 = Branch(bus_from=B_MV_M32, bus_to=B_LV_M32, name="X_M32", branch_type=BranchType.Transformer, template=PM) grid.add_branch(X_M32) # Apply templates (device types) grid.apply_all_branch_types() print("Buses:") for i, b in enumerate(grid.buses): print(f" - bus[{i}]: {b}") print() options = PowerFlowOptions(SolverType.NR, verbose=True, initialize_with_existing_solution=True, multi_core=True, control_q=ReactivePowerControlMode.Direct, control_taps=TapsControlMode.Direct, tolerance=1e-6, max_iter=99) power_flow = PowerFlowDriver(grid, options) power_flow.run() approx_volt = [round(100 * abs(v), 1) for v in power_flow.results.voltage] solution = [100.0, 105.2, 130.0, 130.1] # Expected solution from GridCal print() print(f"Test: {test_name}") print(f"Results: {approx_volt}") print(f"Solution: {solution}") print() print("Generators:") for g in grid.get_generators(): print(f" - Generator {g}: q_min={g.Qmin}pu, q_max={g.Qmax}pu") print() print("Branches:") branches = grid.get_branches() for b in grid.transformers2w: print( f" - {b}: R={round(b.R, 4)}pu, X={round(b.X, 4)}pu, X/R={round(b.X/b.R, 1)}, vset={b.vset}" ) print() print("Transformer types:") for t in grid.transformer_types: print( f" - {t}: Copper losses={int(t.Pcu)}kW, Iron losses={int(t.Pfe)}kW, SC voltage={t.Vsc}%" ) print() print("Losses:") for i in range(len(branches)): print( f" - {branches[i]}: losses={round(power_flow.results.losses[i], 3)} MVA" ) print() tr_vset = [tr.vset for tr in grid.transformers2w] print(f"Voltage settings: {tr_vset}") equal = np.isclose(approx_volt, solution, atol=1e-3).all() assert equal
def test_basic(): """ Basic GridCal test, also useful for a basic tutorial. In this case the magnetizing branch of the transformers is neglected by inputting 1e-20 excitation current and iron core losses. The results are identical to ETAP's, which always uses this assumption in balanced load flow calculations. """ test_name = "test_basic" grid = MultiCircuit(name=test_name) S_base = 100 # MVA grid.Sbase = S_base grid.time_profile = None grid.logger = Logger() # Create buses POI = Bus( name="POI", vnom=100, #kV is_slack=True) grid.add_bus(POI) B_C3 = Bus(name="B_C3", vnom=10) #kV grid.add_bus(B_C3) B_MV_M32 = Bus(name="B_MV_M32", vnom=10) #kV grid.add_bus(B_MV_M32) B_LV_M32 = Bus(name="B_LV_M32", vnom=0.6) #kV grid.add_bus(B_LV_M32) # Create voltage controlled generators (or slack, a.k.a. swing) UT = Generator(name="Utility") UT.bus = POI grid.add_generator(POI, UT) # Create static generators (with fixed power factor) M32 = StaticGenerator( name="M32", P=4.2, # MW Q=0.0j) # MVAR M32.bus = B_LV_M32 grid.add_static_generator(B_LV_M32, M32) # Create transformer types s = 5 # MVA z = 8 # % xr = 40 SS = TransformerType( name="SS", hv_nominal_voltage=100, # kV lv_nominal_voltage=10, # kV nominal_power=s, copper_losses=complex_impedance(z, xr).real * s * 1000 / S_base, iron_losses=1e-20, no_load_current=1e-20, short_circuit_voltage=z) grid.add_transformer_type(SS) s = 5 # MVA z = 6 # % xr = 20 PM = TransformerType( name="PM", hv_nominal_voltage=10, # kV lv_nominal_voltage=0.6, # kV nominal_power=s, copper_losses=complex_impedance(z, xr).real * s * 1000 / S_base, iron_losses=1e-20, no_load_current=1e-20, short_circuit_voltage=z) grid.add_transformer_type(PM) # Create branches X_C3 = Branch(bus_from=POI, bus_to=B_C3, name="X_C3", branch_type=BranchType.Transformer, template=SS) grid.add_branch(X_C3) C_M32 = Branch(bus_from=B_C3, bus_to=B_MV_M32, name="C_M32", r=0.784, x=0.174) grid.add_branch(C_M32) X_M32 = Branch(bus_from=B_MV_M32, bus_to=B_LV_M32, name="X_M32", branch_type=BranchType.Transformer, template=PM) grid.add_branch(X_M32) # Apply templates (device types) grid.apply_all_branch_types() print("Buses:") for i, b in enumerate(grid.buses): print(f" - bus[{i}]: {b}") print() options = PowerFlowOptions(SolverType.LM, verbose=True, initialize_with_existing_solution=True, multi_core=True, control_q=ReactivePowerControlMode.Direct, tolerance=1e-6, max_iter=99) power_flow = PowerFlowDriver(grid, options) power_flow.run() approx_volt = [round(100 * abs(v), 1) for v in power_flow.results.voltage] solution = [ 100.0, 99.6, 102.7, 102.9 ] # Expected solution from GridCal and ETAP 16.1.0, for reference print() print(f"Test: {test_name}") print(f"Results: {approx_volt}") print(f"Solution: {solution}") print() print("Generators:") for g in grid.get_generators(): print(f" - Generator {g}: q_min={g.Qmin}pu, q_max={g.Qmax}pu") print() print("Branches:") for b in grid.branches: print(f" - {b}:") print(f" R = {round(b.R, 4)} pu") print(f" X = {round(b.X, 4)} pu") print(f" X/R = {round(b.X/b.R, 1)}") print(f" G = {round(b.G, 4)} pu") print(f" B = {round(b.B, 4)} pu") print() print("Transformer types:") for t in grid.transformer_types: print( f" - {t}: Copper losses={int(t.Pcu)}kW, Iron losses={int(t.Pfe)}kW, SC voltage={t.Vsc}%" ) print() print("Losses:") for i in range(len(grid.branches)): print( f" - {grid.branches[i]}: losses={1000*round(power_flow.results.losses[i], 3)} kVA" ) print() equal = True for i in range(len(approx_volt)): if approx_volt[i] != solution[i]: equal = False assert equal
def test_pv_3(): """ Voltage controlled generator test, also useful for a basic tutorial. In this case the generator M32 regulates the voltage at a setpoint of 1.025 pu, and the slack bus (POI) regulates it at 1.0 pu. The transformers' magnetizing branch losses are considered, as well as the main power transformer's voltage regulator (X_C3) which regulates bus B_MV_M32 at 1.005 pu. In addition, the iterative PV control method is used instead of the usual (faster) method. """ test_name = "test_pv_3" grid = MultiCircuit(name=test_name) Sbase = 100 # MVA grid.Sbase = Sbase grid.time_profile = None grid.logger = Logger() # Create buses POI = Bus( name="POI", vnom=100, # kV is_slack=True) grid.add_bus(POI) B_MV_M32 = Bus(name="B_MV_M32", vnom=10) # kV grid.add_bus(B_MV_M32) B_LV_M32 = Bus(name="B_LV_M32", vnom=0.6) # kV grid.add_bus(B_LV_M32) # Create voltage controlled generators (or slack, a.k.a. swing) UT = Generator(name="Utility") UT.bus = POI grid.add_generator(POI, UT) M32 = Generator(name="M32", active_power=4.2, voltage_module=1.025, Qmin=-2.5, Qmax=2.5) M32.bus = B_LV_M32 grid.add_generator(B_LV_M32, M32) # Create transformer types s = 100 # MVA z = 8 # % xr = 40 SS = TransformerType( name="SS", hv_nominal_voltage=100, # kV lv_nominal_voltage=10, # kV nominal_power=s, copper_losses=complex_impedance(z, xr).real * s * 1000 / Sbase, iron_losses=125, # kW no_load_current=0.5, # % short_circuit_voltage=z) grid.add_transformer_type(SS) s = 5 # MVA z = 6 # % xr = 20 PM = TransformerType( name="PM", hv_nominal_voltage=10, # kV lv_nominal_voltage=0.6, # kV nominal_power=s, copper_losses=complex_impedance(z, xr).real * s * 1000 / Sbase, iron_losses=6.25, # kW no_load_current=0.5, # % short_circuit_voltage=z) grid.add_transformer_type(PM) # Create branches X_C3 = Branch(bus_from=POI, bus_to=B_MV_M32, name="X_C3", branch_type=BranchType.Transformer, template=SS, bus_to_regulated=True, vset=1.005) X_C3.tap_changer = TapChanger(taps_up=16, taps_down=16, max_reg=1.1, min_reg=0.9) X_C3.tap_changer.set_tap(X_C3.tap_module) grid.add_branch(X_C3) X_M32 = Branch(bus_from=B_MV_M32, bus_to=B_LV_M32, name="X_M32", branch_type=BranchType.Transformer, template=PM) grid.add_branch(X_M32) # Apply templates (device types) grid.apply_all_branch_types() print("Buses:") for i, b in enumerate(grid.buses): print(f" - bus[{i}]: {b}") print() options = PowerFlowOptions(SolverType.LM, verbose=True, initialize_with_existing_solution=True, multi_core=True, control_q=ReactivePowerControlMode.Iterative, control_taps=TapsControlMode.Direct, tolerance=1e-6, max_iter=99) power_flow = PowerFlowDriver(grid, options) power_flow.run() approx_volt = [round(100 * abs(v), 1) for v in power_flow.results.voltage] solution = [100.0, 100.7, 102.5] # Expected solution from GridCal print() print(f"Test: {test_name}") print(f"Results: {approx_volt}") print(f"Solution: {solution}") print() print("Generators:") for g in grid.get_generators(): print(f" - Generator {g}: q_min={g.Qmin} MVAR, q_max={g.Qmax} MVAR") print() print("Branches:") for b in grid.branches: print(f" - {b}:") print(f" R = {round(b.R, 4)} pu") print(f" X = {round(b.X, 4)} pu") print(f" X/R = {round(b.X / b.R, 1)}") print(f" G = {round(b.G, 4)} pu") print(f" B = {round(b.B, 4)} pu") print() print("Transformer types:") for t in grid.transformer_types: print( f" - {t}: Copper losses={int(t.Pcu)}kW, Iron losses={int(t.Pfe)}kW, SC voltage={t.Vsc}%" ) print() print("Losses:") for i in range(len(grid.branches)): print( f" - {grid.branches[i]}: losses={1000 * round(power_flow.results.losses[i], 3)} kVA" ) print() equal = True for i in range(len(approx_volt)): if approx_volt[i] != solution[i]: equal = False assert equal
def main(): #################################################################################################################### # Define the circuit # # A circuit contains all the grid information regardless of the islands formed or the amount of devices #################################################################################################################### grid = MultiCircuit(name='lynn 5 bus') #################################################################################################################### # Define the buses #################################################################################################################### # I will define this bus with all the properties so you see bus1 = Bus(name='Bus1', vnom=10, # Nominal voltage in kV vmin=0.9, # Bus minimum voltage in per unit vmax=1.1, # Bus maximum voltage in per unit xpos=0, # Bus x position in pixels ypos=0, # Bus y position in pixels height=0, # Bus height in pixels width=0, # Bus width in pixels active=True, # Is the bus active? is_slack=False, # Is this bus a slack bus? area='Defualt', # Area (for grouping purposes only) zone='Default', # Zone (for grouping purposes only) substation='Default' # Substation (for grouping purposes only) ) # the rest of the buses are defined with the default parameters bus2 = Bus(name='Bus2') bus3 = Bus(name='Bus3') bus4 = Bus(name='Bus4') bus5 = Bus(name='Bus5') # add the bus objects to the circuit grid.add_bus(bus1) grid.add_bus(bus2) grid.add_bus(bus3) grid.add_bus(bus4) grid.add_bus(bus5) #################################################################################################################### # Add the loads #################################################################################################################### # In GridCal, the loads, generators ect are stored within each bus object: # we'll define the first load completely l2 = Load(name='Load', G=0, # Impedance of the ZIP model in MVA at the nominal voltage B=0, Ir=0, Ii=0, # Current of the ZIP model in MVA at the nominal voltage P=40, Q=20, # Power of the ZIP model in MVA P_prof=None, # Impedance profile Q_prof=None, # Current profile Ir_prof=None, # Power profile Ii_prof=None, G_prof=None, B_prof=None, active=True, # Is active? mttf=0.0, # Mean time to failure mttr=0.0 # Mean time to recovery ) grid.add_load(bus2, l2) # Define the others with the default parameters grid.add_load(bus3, Load(P=25, Q=15)) grid.add_load(bus4, Load(P=40, Q=20)) grid.add_load(bus5, Load(P=50, Q=20)) #################################################################################################################### # Add the generators #################################################################################################################### g1 = Generator(name='gen', active_power=0.0, # Active power in MW, since this generator is used to set the slack , is 0 voltage_module=1.0, # Voltage set point to control Qmin=-9999, # minimum reactive power in MVAr Qmax=9999, # Maximum reactive power in MVAr Snom=9999, # Nominal power in MVA power_prof=None, # power profile vset_prof=None, # voltage set point profile active=True # Is active? ) grid.add_generator(bus1, g1) #################################################################################################################### # Add the lines #################################################################################################################### br1 = Branch(bus_from=bus1, bus_to=bus2, name='Line 1-2', r=0.05, # resistance of the pi model in per unit x=0.11, # reactance of the pi model in per unit g=1e-20, # conductance of the pi model in per unit b=0.02, # susceptance of the pi model in per unit rate=50, # Rate in MVA tap=1.0, # Tap value (value close to 1) shift_angle=0, # Tap angle in radians active=True, # is the branch active? mttf=0, # Mean time to failure mttr=0, # Mean time to recovery branch_type=BranchType.Line, # Branch type tag length=1, # Length in km (to be used with templates) template=BranchTemplate() # Branch template (The default one is void) ) grid.add_branch(br1) grid.add_branch(Branch(bus1, bus3, name='Line 1-3', r=0.05, x=0.11, b=0.02, rate=50)) grid.add_branch(Branch(bus1, bus5, name='Line 1-5', r=0.03, x=0.08, b=0.02, rate=80)) grid.add_branch(Branch(bus2, bus3, name='Line 2-3', r=0.04, x=0.09, b=0.02, rate=3)) grid.add_branch(Branch(bus2, bus5, name='Line 2-5', r=0.04, x=0.09, b=0.02, rate=10)) grid.add_branch(Branch(bus3, bus4, name='Line 3-4', r=0.06, x=0.13, b=0.03, rate=30)) grid.add_branch(Branch(bus4, bus5, name='Line 4-5', r=0.04, x=0.09, b=0.02, rate=30)) #################################################################################################################### # Run a power flow simulation #################################################################################################################### # We need to specify power flow options pf_options = PowerFlowOptions(solver_type=SolverType.NR, # Base method to use verbose=False, # Verbose option where available tolerance=1e-6, # power error in p.u. max_iter=25, # maximum iteration number control_q=True # if to control the reactive power ) # Declare and execute the power flow simulation pf = PowerFlowDriver(grid, pf_options) pf.run() # now, let's compose a nice DataFrame with the voltage results headers = ['Vm (p.u.)', 'Va (Deg)', 'Vre', 'Vim'] Vm = np.abs(pf.results.voltage) Va = np.angle(pf.results.voltage, deg=True) Vre = pf.results.voltage.real Vim = pf.results.voltage.imag data = np.c_[Vm, Va, Vre, Vim] v_df = pd.DataFrame(data=data, columns=headers, index=grid.bus_names) print('\n', v_df) # Let's do the same for the branch results headers = ['Loading (%)', 'Current(p.u.)', 'Power (MVA)'] loading = np.abs(pf.results.loading) * 100 current = np.abs(pf.results.Ibranch) power = np.abs(pf.results.Sbranch) data = np.c_[loading, current, power] br_df = pd.DataFrame(data=data, columns=headers, index=grid.branch_names) print('\n', br_df) # Finally the execution metrics print('\nError:', pf.results.error) print('Elapsed time (s):', pf.results.elapsed, '\n') print(v_df) print() print(br_df)