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)
