import numpy as np
import pandas as pd
import datetime as dt
from GridCal.Engine import *
####################################################################################################################
# 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
date0 = dt.datetime(2021, 1, 1)
time_array = pd.DatetimeIndex([date0 + dt.timedelta(hours=i) for i in range(26)])
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))
####################################################################################################################
# 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 (%)', 'Power from (MVA)']
loading = np.abs(pf.results.loading) * 100
power = np.abs(pf.results.Sf)
data = np.c_[loading, 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')
####################################################################################################################
# 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')
print(df_voltage)
writer.close()