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 test_api_helm():
np.set_printoptions(precision=4)
fname = os.path.join('..', '..', 'Grids_and_profiles', 'grids', 'IEEE 30 Bus with storage.xlsx')
grid = FileOpen(fname).open()
print('\n\n', grid.name)
# print('Ybus:\n', grid.circuits[0].power_flow_input.Ybus.todense())
options = PowerFlowOptions(SolverType.HELM, verbose=False, tolerance=1e-9)
power_flow = PowerFlowDriver(grid, options)
power_flow.run()
print_power_flow_results(power_flow)
def test_demo_5_node(root_path=ROOT_PATH):
np.core.arrayprint.set_printoptions(precision=4)
grid = MultiCircuit()
# Add buses
bus1 = Bus('Bus 1', vnom=20)
grid.add_bus(bus1)
gen1 = Generator('Slack Generator', voltage_module=1.0)
grid.add_generator(bus1, gen1)
bus2 = Bus('Bus 2', vnom=20)
grid.add_bus(bus2)
grid.add_load(bus2, Load('load 2', P=40, Q=20))
bus3 = Bus('Bus 3', vnom=20)
grid.add_bus(bus3)
grid.add_load(bus3, Load('load 3', P=25, Q=15))
bus4 = Bus('Bus 4', vnom=20)
grid.add_bus(bus4)
grid.add_load(bus4, Load('load 4', P=40, Q=20))
bus5 = Bus('Bus 5', vnom=20)
grid.add_bus(bus5)
grid.add_load(bus5, Load('load 5', P=50, Q=20))
# add branches (Lines in this case)
grid.add_line(Line(bus1, bus2, 'line 1-2', r=0.05, x=0.11, b=0.02))
grid.add_line(Line(bus1, bus3, 'line 1-3', r=0.05, x=0.11, b=0.02))
grid.add_line(Line(bus1, bus5, 'line 1-5', r=0.03, x=0.08, b=0.02))
grid.add_line(Line(bus2, bus3, 'line 2-3', r=0.04, x=0.09, b=0.02))
grid.add_line(Line(bus2, bus5, 'line 2-5', r=0.04, x=0.09, b=0.02))
grid.add_line(Line(bus3, bus4, 'line 3-4', r=0.06, x=0.13, b=0.03))
grid.add_line(Line(bus4, bus5, 'line 4-5', r=0.04, x=0.09, b=0.02))
# grid.plot_graph()
print('\n\n', grid.name)
FileSave(grid, 'demo_5_node.json').save()
options = PowerFlowOptions(SolverType.NR, verbose=False)
power_flow = PowerFlowDriver(grid, options)
power_flow.run()
print_power_flow_results(power_flow=power_flow)
v = np.array([1., 0.9553, 0.9548, 0.9334, 0.9534])
all_ok = np.isclose(np.abs(power_flow.results.voltage), v, atol=1e-3)
return all_ok
def test_demo_5_node(root_path):
np.core.arrayprint.set_printoptions(precision=4)
grid = MultiCircuit()
# Add buses
bus1 = Bus('Bus 1', vnom=20)
# bus1.is_slack = True
grid.add_bus(bus1)
gen1 = Generator('Slack Generator', voltage_module=1.0)
grid.add_generator(bus1, gen1)
bus2 = Bus('Bus 2', vnom=20)
grid.add_bus(bus2)
grid.add_load(bus2, Load('load 2', P=40, Q=20))
bus3 = Bus('Bus 3', vnom=20)
grid.add_bus(bus3)
grid.add_load(bus3, Load('load 3', P=25, Q=15))
bus4 = Bus('Bus 4', vnom=20)
grid.add_bus(bus4)
grid.add_load(bus4, Load('load 4', P=40, Q=20))
bus5 = Bus('Bus 5', vnom=20)
grid.add_bus(bus5)
grid.add_load(bus5, Load('load 5', P=50, Q=20))
# add branches (Lines in this case)
grid.add_branch(Branch(bus1, bus2, 'line 1-2', r=0.05, x=0.11, b=0.02))
grid.add_branch(Branch(bus1, bus3, 'line 1-3', r=0.05, x=0.11, b=0.02))
grid.add_branch(Branch(bus1, bus5, 'line 1-5', r=0.03, x=0.08, b=0.02))
grid.add_branch(Branch(bus2, bus3, 'line 2-3', r=0.04, x=0.09, b=0.02))
grid.add_branch(Branch(bus2, bus5, 'line 2-5', r=0.04, x=0.09, b=0.02))
grid.add_branch(Branch(bus3, bus4, 'line 3-4', r=0.06, x=0.13, b=0.03))
grid.add_branch(Branch(bus4, bus5, 'line 4-5', r=0.04, x=0.09, b=0.02))
# grid.plot_graph()
print('\n\n', grid.name)
options = PowerFlowOptions(SolverType.NR, verbose=False)
power_flow = PowerFlowDriver(grid, options)
power_flow.run()
print_power_flow_results(power_flow=power_flow)
def test_api_multi_core_starmap():
"""
Test the pool.starmap function together with GridCal
"""
file_name = os.path.join('..', '..', 'Grids_and_profiles', 'grids', 'IEEE 30 Bus with storage.xlsx')
batch_size = 100
grid = FileOpen(file_name).open()
print('\n\n', grid.name)
options = PowerFlowOptions(SolverType.NR, verbose=False)
power_flow = PowerFlowDriver(grid, options)
power_flow.run()
# create instances of the of the power flow simulation given the grid
print('running...')
pool = Pool()
results = pool.starmap(multi_island_pf, [(grid, options, 0)] * batch_size)
def __init__(self,
circuit: MultiCircuit,
options: PowerFlowOptions,
max_iter=1000,
callback=None):
self.circuit = circuit
self.options = options
self.callback = callback
# initialize the power flow
self.power_flow = PowerFlowDriver(self.circuit, self.options)
# compile circuits
self.numerical_circuit = self.circuit.compile()
self.numerical_input_islands = self.numerical_circuit.compute()
n = len(self.circuit.buses)
m = len(self.circuit.branches)
self.max_eval = max_iter
# the dimension is the number of nodes
self.dim = self.numerical_circuit.n_ctrl_gen
self.x0 = np.abs(self.numerical_circuit.generator_voltage) - np.ones(
self.dim)
self.min = 0
self.minimum = np.zeros(self.dim)
self.lb = -0.1 * np.ones(self.dim)
self.ub = 0.1 * np.ones(self.dim)
self.int_var = np.array([])
self.cont_var = np.arange(0, self.dim)
self.info = str(
self.dim) + "Generators voltage set points optimization"
# results
self.results = MonteCarloResults(n,
m,
self.max_eval,
name='Set point optimization')
self.all_f = list()
self.it = 0
def perform_step_run(self):
"""
Perform only one step cascading
Returns:
Nothing
"""
# initialize the simulator
if self.cascade_type is CascadeType.PowerFlow:
model_simulator = PowerFlowDriver(self.grid, self.options)
elif self.cascade_type is CascadeType.LatinHypercube:
model_simulator = StochasticPowerFlowDriver(
self.grid, self.options, sampling_points=self.n_lhs_samples)
else:
model_simulator = PowerFlowDriver(self.grid, self.options)
# For every circuit, run a power flow
# for c in self.grid.circuits:
model_simulator.run()
if self.current_step == 0:
# the first iteration try to trigger the selected indices, if any
idx, criteria = self.remove_elements(
self.grid,
idx=self.triggering_idx,
loading_vector=model_simulator.results.loading)
else:
# cascade normally
idx, criteria = self.remove_elements(
self.grid, loading_vector=model_simulator.results.loading)
# store the removed indices and the results
entry = CascadingReportElement(idx, model_simulator.results, criteria)
self.results.events.append(entry)
# increase the step number
self.current_step += 1
# print(model_simulator.results.get_convergence_report())
# send the finnish signal
self.progress_signal.emit(0.0)
self.progress_text.emit('Done!')
self.done_signal.emit()
def __init__(self,
circuit: MultiCircuit,
options: PowerFlowOptions,
max_iter=1000,
callback=None):
self.circuit = circuit
self.options = options
self.callback = callback
# initialize the power flow
self.power_flow = PowerFlowDriver(self.circuit, self.options)
n = len(self.circuit.buses)
m = self.circuit.get_branch_number()
self.max_eval = max_iter
# the dimension is the number of nodes
self.dim = n
self.min = 0
self.minimum = np.zeros(self.dim)
self.lb = -15 * np.ones(self.dim)
self.ub = 20 * np.ones(self.dim)
self.int_var = np.array([])
self.cont_var = np.arange(0, self.dim)
self.info = str(self.dim) + "Voltage collapse optimization"
# results
self.results = StochasticPowerFlowResults(n,
m,
self.max_eval,
name='Voltage optimization')
# compile circuits
self.numerical_circuit = self.circuit.compile_snapshot()
self.numerical_input_islands = self.numerical_circuit.compute(
ignore_single_node_islands=options.ignore_single_node_islands)
self.it = 0
# fname = os.path.join('..', '..', '..', '..', 'Grids_and_profiles', 'grids', 'IEEE 30 Bus with storage.xlsx')
fname = os.path.join('..', '..', '..', '..', 'Grids_and_profiles', 'grids', 'lynn5buspv.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)
####################################################################################################################
# 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())
####################################################################################################################
# Voltage collapse
####################################################################################################################
vc_options = VoltageCollapseOptions(step=0.001,
approximation_order=VCParametrization.ArcLength,
adapt_step=True,
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_corr_line_losses():
test_name = "test_corr_line_losses"
grid = MultiCircuit(name=test_name)
grid.Sbase = Sbase
grid.time_profile = None
grid.logger = Logger()
# Create buses
Bus0 = Bus(name="Bus0", vnom=10, is_slack=True)
Bus1 = Bus(name="Bus1", vnom=10)
grid.add_bus(Bus0)
grid.add_bus(Bus1)
# Create load
grid.add_load(Bus1, Load(name="Load0", P=1.0, Q=0.4))
# Create slack bus
grid.add_generator(Bus0, Generator(name="Utility"))
# Create cable
cable = Branch(
bus_from=Bus0,
bus_to=Bus1,
name="Cable0",
r=0.784,
x=0.174,
temp_base=20, # °C
temp_oper=90, # °C
alpha=0.00323) # Copper
grid.add_branch(cable)
options = PowerFlowOptions(verbose=True, apply_temperature_correction=True)
power_flow = PowerFlowDriver(grid, options)
power_flow.run()
# Check solution
approx_losses = round(power_flow.results.losses[0], 3)
solution = complex(0.011, 0.002) # Expected solution from GridCal
# Tested on ETAP 16.1.0
print(
"\n=================================================================")
print(f"Test: {test_name}")
print(
"=================================================================\n")
print(f"Results: {approx_losses}")
print(f"Solution: {solution}")
print()
print("Buses:")
for i, b in enumerate(grid.buses):
print(f" - bus[{i}]: {b}")
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, 2)}")
print()
print("Voltages:")
for i in range(len(grid.buses)):
print(
f" - {grid.buses[i]}: voltage={round(power_flow.results.voltage[i], 3)} pu"
)
print()
print("Losses:")
for i in range(len(grid.branches)):
print(
f" - {grid.branches[i]}: losses={round(power_flow.results.losses[i], 3)} MVA"
)
print()
print("Loadings (power):")
for i in range(len(grid.branches)):
print(
f" - {grid.branches[i]}: loading={round(power_flow.results.Sbranch[i], 3)} MVA"
)
print()
print("Loadings (current):")
for i in range(len(grid.branches)):
print(
f" - {grid.branches[i]}: loading={round(power_flow.results.Ibranch[i], 3)} pu"
)
print()
assert approx_losses == solution
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)
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()
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 run(self):
"""
Run the monte carlo simulation
@return:
"""
self.__cancel__ = False
# compile
# print('Compiling...', end='')
numerical_circuit = self.grid.compile()
calculation_inputs = numerical_circuit.compute(branch_tolerance_mode=self.options.branch_impedance_tolerance_mode)
self.results = CascadingResults(self.cascade_type)
# initialize the simulator
if self.cascade_type is CascadeType.PowerFlow:
model_simulator = PowerFlowDriver(self.grid, self.options)
elif self.cascade_type is CascadeType.LatinHypercube:
model_simulator = LatinHypercubeSampling(self.grid, self.options, sampling_points=self.n_lhs_samples)
else:
model_simulator = PowerFlowDriver(self.grid, self.options)
self.progress_signal.emit(0.0)
self.progress_text.emit('Running cascading failure...')
n_grids = len(calculation_inputs) + self.max_additional_islands
if n_grids > len(self.grid.buses): # safety check
n_grids = len(self.grid.buses) - 1
# print('n grids: ', n_grids)
it = 0
while len(calculation_inputs) <= n_grids and it <= n_grids:
# For every circuit, run a power flow
# for c in self.grid.circuits:
model_simulator.run()
# print(model_simulator.results.get_convergence_report())
# remove grid elements (branches)
idx, criteria = self.remove_probability_based(numerical_circuit, model_simulator.results, max_val=1.0, min_prob=0.1)
# store the removed indices and the results
entry = CascadingReportElement(idx, model_simulator.results, criteria)
self.results.events.append(entry)
# recompile grid
calculation_inputs = numerical_circuit.compute()
it += 1
prog = max(len(calculation_inputs) / (n_grids+1), it/(n_grids+1))
self.progress_signal.emit(prog * 100.0)
if self.__cancel__:
break
print('Grid split into ', len(calculation_inputs), ' islands after', it, ' steps')
# send the finnish signal
self.progress_signal.emit(0.0)
self.progress_text.emit('Done!')
self.done_signal.emit()
def _test_api():
fname = os.path.join('..', '..', 'Grids_and_profiles', 'grids',
'IEEE 30 Bus with storage.xlsx')
print('Reading...')
main_circuit = FileOpen(fname).open()
pf_options = PowerFlowOptions(SolverType.NR,
verbose=False,
initialize_with_existing_solution=False,
multi_core=False,
dispatch_storage=True,
control_q=ReactivePowerControlMode.NoControl,
control_p=True)
####################################################################################################################
# PowerFlowDriver
####################################################################################################################
print('\n\n')
power_flow = PowerFlowDriver(main_circuit, pf_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())
####################################################################################################################
# Short circuit
####################################################################################################################
print('\n\n')
print('Short Circuit')
sc_options = ShortCircuitOptions(bus_index=[16])
# grid, options, pf_options:, pf_results:
sc = ShortCircuit(grid=main_circuit,
options=sc_options,
pf_options=pf_options,
pf_results=power_flow.results)
sc.run()
print('\n\n', main_circuit.name)
print('\t|V|:', abs(main_circuit.short_circuit_results.voltage))
print('\t|Sbranch|:', abs(main_circuit.short_circuit_results.Sbranch))
print('\t|loading|:',
abs(main_circuit.short_circuit_results.loading) * 100)
####################################################################################################################
# Time Series
####################################################################################################################
print('Running TS...', '')
ts = TimeSeries(grid=main_circuit, options=pf_options, start_=0, end_=96)
ts.run()
numeric_circuit = main_circuit.compile()
ts_analysis = TimeSeriesResultsAnalysis(numeric_circuit, ts.results)
####################################################################################################################
# OPF
####################################################################################################################
print('Running OPF...', '')
opf_options = OptimalPowerFlowOptions(verbose=False,
solver=SolverType.DC_OPF,
mip_solver=False)
opf = OptimalPowerFlow(grid=main_circuit, options=opf_options)
opf.run()
####################################################################################################################
# OPF Time Series
####################################################################################################################
print('Running OPF-TS...', '')
opf_options = OptimalPowerFlowOptions(verbose=False,
solver=SolverType.NELDER_MEAD_OPF,
mip_solver=False)
opf_ts = OptimalPowerFlowTimeSeries(grid=main_circuit,
options=opf_options,
start_=0,
end_=96)
opf_ts.run()
####################################################################################################################
# Voltage collapse
####################################################################################################################
vc_options = VoltageCollapseOptions()
# just for this test
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()
# vc.results.plot()
####################################################################################################################
# Monte Carlo
####################################################################################################################
print('Running MC...')
mc_sim = MonteCarlo(main_circuit,
pf_options,
mc_tol=1e-5,
max_mc_iter=1000000)
mc_sim.run()
lst = np.array(list(range(mc_sim.results.n)), dtype=int)
# mc_sim.results.plot(ResultTypes.BusVoltageAverage, indices=lst, names=lst)
####################################################################################################################
# Latin Hypercube
####################################################################################################################
print('Running LHC...')
lhs_sim = LatinHypercubeSampling(main_circuit,
pf_options,
sampling_points=100)
lhs_sim.run()
####################################################################################################################
# Cascading
####################################################################################################################
print('Running Cascading...')
cascade = Cascading(main_circuit.copy(),
pf_options,
max_additional_islands=5,
cascade_type_=CascadeType.LatinHypercube,
n_lhs_samples_=10)
cascade.run()
cascade.perform_step_run()
cascade.perform_step_run()
cascade.perform_step_run()
cascade.perform_step_run()
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_line_losses_1():
"""
Basic line losses test.
"""
test_name = "test_line_losses_1"
grid = MultiCircuit(name=test_name)
Sbase = 100 # MVA
grid.Sbase = Sbase
grid.time_profile = None
grid.logger = Logger()
# Create buses
Bus0 = Bus(name="Bus0", vnom=25, is_slack=True)
Bus1 = Bus(name="Bus1", vnom=25)
grid.add_bus(Bus0)
grid.add_bus(Bus1)
# Create load
grid.add_load(Bus1, Load(name="Load0", P=1.0, Q=0.4))
# Create slack bus
grid.add_generator(Bus0, Generator(name="Utility"))
# Create cable (r and x should be in pu)
grid.add_branch(
Line(bus_from=Bus0, bus_to=Bus1, name="Cable1", r=0.01, x=0.05))
# Run non-linear load flow
options = PowerFlowOptions(verbose=True)
power_flow = PowerFlowDriver(grid, options)
power_flow.run()
# Check solution
approx_losses = round(1000 * power_flow.results.losses[0], 3)
solution = complex(0.116, 0.58) # Expected solution from GridCal
# Tested on ETAP 16.1.0 and pandapower
print(
"\n=================================================================")
print(f"Test: {test_name}")
print(
"=================================================================\n")
print(f"Results: {approx_losses}")
print(f"Solution: {solution}")
print()
print("Buses:")
for i, b in enumerate(grid.buses):
print(f" - bus[{i}]: {b}")
print()
print("Branches:")
branches = grid.get_branches()
for b in 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, 2)}")
print()
print("Voltages:")
for i in range(len(grid.buses)):
print(
f" - {grid.buses[i]}: voltage={round(power_flow.results.voltage[i], 3)} pu"
)
print()
print("Losses:")
for i in range(len(branches)):
print(
f" - {branches[i]}: losses={round(power_flow.results.losses[i], 3)} MVA"
)
print()
print("Loadings (power):")
for i in range(len(branches)):
print(
f" - {branches[i]}: loading={round(power_flow.results.Sf[i], 3)} MVA"
)
print()
print("Loadings (current):")
for i in range(len(branches)):
print(
f" - {branches[i]}: loading={round(power_flow.results.If[i], 3)} pu"
)
print()
assert approx_losses == solution
def run_illinois_mode(self, time_indices) -> PtdfTimeSeriesResults:
"""
Run the PTDF with the illinois formulation
:return: TimeSeriesResults instance
"""
# initialize the grid time series results, we will append the island results with another function
nc = compile_opf_time_circuit(
circuit=self.grid,
apply_temperature=self.pf_options.apply_temperature_correction,
branch_tolerance_mode=self.pf_options.
branch_impedance_tolerance_mode)
results = PtdfTimeSeriesResults(
n=nc.nbus,
m=nc.nbr,
time_array=self.grid.time_profile[time_indices],
bus_names=nc.bus_names,
bus_types=nc.bus_types,
branch_names=nc.branch_names)
# if there are valid profiles...
if self.grid.time_profile is not None:
# run a power flow to get the initial branch power and compose the second branch power with the increment
driver = PowerFlowDriver(grid=self.grid, options=self.pf_options)
driver.run()
# compile the islands
islands = split_opf_time_circuit_into_islands(nc)
# compose the power injections
Pbus_0 = driver.results.Sbus.real
V_0 = np.abs(driver.results.voltage)
Pbr_0 = driver.results.Sbranch.real
for island in islands:
PTDF = compute_ptdf(Ybus=island.Ybus,
Yf=island.Yf,
Yt=island.Yt,
Cf=island.C_branch_bus_f,
Ct=island.C_branch_bus_t,
V=island.Vbus[0, :],
Ibus=island.Ibus[:, 0],
Sbus=island.Sbus[:, 0],
pq=island.pq,
pv=island.pv)
# run the PTDF time series
for k, t_idx in enumerate(time_indices):
dP = Pbus_0[
island.original_bus_idx] - island.Sbus[:, t_idx].real
dP1 = island.Sbus[:, t_idx].real
# results.voltage[k, island.original_bus_idx] = V_0[island.original_bus_idx] + np.dot(dP, vtdf)
results.Sbranch[k, island.original_branch_idx] = Pbr_0[
island.original_branch_idx] - (PTDF * dP
) #* island.Sbase
results.loading[
k, island.original_branch_idx] = results.Sbranch[
k, island.original_branch_idx] / (nc.branch_rates[
t_idx, island.original_branch_idx] + 1e-9)
results.S[
k, island.original_bus_idx] = island.Sbus[:,
t_idx].real
progress = ((t_idx - self.start_ + 1) /
(self.end_ - self.start_)) * 100
self.progress_signal.emit(progress)
self.progress_text.emit('Simulating PTDF at ' +
str(self.grid.time_profile[t_idx]))
else:
print('There are no profiles')
self.progress_text.emit('There are no profiles')
return results
def run(self):
"""
Run the monte carlo simulation
@return:
"""
self.__cancel__ = False
# compile
# print('Compiling...', end='')
nc = compile_time_circuit(self.grid)
calculation_inputs = nc.split_into_islands(
ignore_single_node_islands=self.options.ignore_single_node_islands)
self.results = CascadingResults(self.cascade_type)
# initialize the simulator
if self.cascade_type is CascadeType.PowerFlow:
model_simulator = PowerFlowDriver(self.grid, self.options)
elif self.cascade_type is CascadeType.LatinHypercube:
model_simulator = StochasticPowerFlowDriver(
self.grid, self.options, sampling_points=self.n_lhs_samples)
else:
model_simulator = PowerFlowDriver(self.grid, self.options)
self.progress_signal.emit(0.0)
self.progress_text.emit('Running cascading failure...')
n_grids = len(calculation_inputs) + self.max_additional_islands
if n_grids > len(self.grid.buses): # safety check
n_grids = len(self.grid.buses) - 1
# print('n grids: ', n_grids)
it = 0
while len(calculation_inputs) <= n_grids and it <= n_grids:
# For every circuit, run the model (time series, lhs, or whatever)
model_simulator.run()
# remove grid elements (branches)
idx, criteria = self.remove_probability_based(
nc, model_simulator.results, max_val=1.0, min_prob=0.1)
# store the removed indices and the results
entry = CascadingReportElement(idx, model_simulator.results,
criteria)
self.results.events.append(entry)
# recompile grid
calculation_inputs = nc.split_into_islands(
ignore_single_node_islands=self.options.
ignore_single_node_islands)
it += 1
prog = max(
len(calculation_inputs) / (n_grids + 1), it / (n_grids + 1))
self.progress_signal.emit(prog * 100.0)
if self.__cancel__:
break
print('Grid split into ', len(calculation_inputs), ' islands after',
it, ' steps')
# send the finnish signal
self.progress_signal.emit(0.0)
self.progress_text.emit('Done!')
self.done_signal.emit()
def run_jacobian_mode(self, time_indices) -> PtdfTimeSeriesResults:
"""
Run the PTDF with the illinois formulation
:return: TimeSeriesResults instance
"""
# initialize the grid time series results, we will append the island results with another function
nc = compile_opf_time_circuit(
circuit=self.grid,
apply_temperature=self.pf_options.apply_temperature_correction,
branch_tolerance_mode=self.pf_options.
branch_impedance_tolerance_mode)
results = PtdfTimeSeriesResults(
n=nc.nbus,
m=nc.nbr,
time_array=self.grid.time_profile[time_indices],
bus_names=nc.bus_names,
bus_types=nc.bus_types,
branch_names=nc.branch_names)
# if there are valid profiles...
if self.grid.time_profile is not None:
# run a power flow to get the initial branch power and compose the second branch power with the increment
driver = PowerFlowDriver(grid=self.grid, options=self.pf_options)
driver.run()
# compile the islands
islands = split_opf_time_circuit_into_islands(nc)
# compose the power injections
Sbus_0 = driver.results.Sbus
Pbus_0 = Sbus_0.real
V_0 = driver.results.voltage
Pbr_0 = driver.results.Sbranch.real
for island in islands:
V = island.Vbus[0, :]
Ibus = island.Ibus[:, 0]
n = len(V)
# set up indexing for updating V
pvpq = np.r_[island.pv, island.pq]
npv = len(island.pv)
npq = len(island.pq)
# j1:j2 - V angle of pv and pq buses
j1 = 0
j2 = npv + npq
# j2:j3 - V mag of pq buses
j3 = j2 + npq
# compute the Jacobian
J = Jacobian(island.Ybus, V, Ibus, island.pq, pvpq)
Jfact = factorized(J)
dVa = np.zeros(n)
dVm = np.zeros(n)
# run the PTDF time series
for k, t_idx in enumerate(time_indices):
# dP = Pbus_0[island.original_bus_idx] - island.Sbus[:, t_idx].real
# compute the power increment (f)
dS = Sbus_0 - island.Sbus[:, t_idx]
# dS = island.Sbus[:, t_idx]
f = np.r_[dS[pvpq].real, dS[island.pq].imag]
# solve the voltage increment
dx = Jfact(f)
# reassign the solution vector
dVa[pvpq] = dx[j1:j2]
dVm[island.pq] = dx[j2:j3]
dV = dVm * np.exp(1j * dVa)
V = V_0 - dV
Vf = island.C_branch_bus_f * V
If = np.conj(island.Yf * V)
Sf = (Vf * If) * island.Sbase
results.voltage[k, island.original_bus_idx] = np.abs(V)
results.Sbranch[k, island.original_branch_idx] = Sf.real
results.loading[
k, island.original_branch_idx] = Sf.real / (
nc.branch_rates[t_idx,
island.original_branch_idx] + 1e-9)
results.S[
k, island.original_bus_idx] = island.Sbus[:,
t_idx].real
progress = ((t_idx - self.start_ + 1) /
(self.end_ - self.start_)) * 100
self.progress_signal.emit(progress)
self.progress_text.emit('Simulating PTDF at ' +
str(self.grid.time_profile[t_idx]))
else:
print('There are no profiles')
self.progress_text.emit('There are no profiles')
return results
