def __init__(self, agent_id_to_grid_id, fname='Grid.xlsx', dt=1):
self.current_transactions = Transactions()
self.chain = []
self.nodes = set()
self.agent_id_to_grid_id = agent_id_to_grid_id
self.actors_group = ActorsGroup()
self.market = Market(actors_group=self.actors_group)
self.dt = dt
self.grid = MultiCircuit()
self.grid.load_file(fname)
# Create the genesis block
self.new_block(previous_hash='1', proof=100)
def __init__(self, grid: MultiCircuit, verbose=False):
self.grid = grid
self.problem = AcOPFBlackBox(grid, verbose=verbose)
self.numerical_circuit = self.problem.numerical_circuit
self.converged = False
self.result = None
self.load_shedding = np.zeros(len(grid.get_load_names()))
def get_connectivity(file_name):
circuit = MultiCircuit()
circuit.load_file(file_name)
circuit.compile()
# form C
threshold = 1e-5
m = len(circuit.branches)
n = len(circuit.buses)
C = lil_matrix((m, n), dtype=int)
buses_dict = {bus: i for i, bus in enumerate(circuit.buses)}
branches_to_keep_idx = list()
branches_to_remove_idx = list()
states = np.zeros(m, dtype=int)
br_idx = [None] * m
graph = Graph()
for i in range(len(circuit.branches)):
# get the from and to bus indices
f = buses_dict[circuit.branches[i].bus_from]
t = buses_dict[circuit.branches[i].bus_to]
graph.add_edge(f, t)
C[i, f] = 1
C[i, t] = -1
br_idx[i] = i
rx = circuit.branches[i].R + circuit.branches[i].X
if circuit.branches[i].branch_type == BranchType.Branch:
branches_to_remove_idx.append(i)
states[i] = 0
else:
branches_to_keep_idx.append(i)
states[i] = 1
C = csc_matrix(C)
return circuit, states, C, C.transpose() * C, graph
def load_dpx(file_name, contraction_factor=1000):
"""
Read DPX file
:param file_name: file name
:return: MultiCircuit
"""
circuit = MultiCircuit()
Sbase = 100
circuit.Sbase = Sbase
SQRT3 = np.sqrt(3)
# read the raw data into a structured dictionary
print('Reading file...')
structures_dict, logger = read_dpx_data(file_name=file_name)
# format the read data
print('Packing data...')
data_structures, logger = repack(data_structures=structures_dict,
logger=logger)
buses_id_dict = dict()
# create nodes
for tpe in data_structures['Nodes']:
# Airline support post
# __headers__['Nodes']['APOIO'] = ['CLASS', 'ID', 'NAME', 'VBASE', 'GX', 'GY', 'SX', 'SY', 'EXIST']
# __headers__['Nodes']['ARM'] = ['CLASS', 'ID', 'NAME', 'VBASE', 'GX', 'GY', 'SX', 'SY', 'EXIST', 'YEAR']
# __headers__['Nodes']['CX'] = ['CLASS', 'ID', 'NAME', 'VBASE', 'GX', 'GY', 'SX', 'SY', 'EXIST']
# __headers__['Nodes']['CXN'] = ['CLASS', 'ID', 'NAME', 'VBASE', 'GX', 'GY', 'SX', 'SY', 'EXIST']
# __headers__['Nodes']['LOAD'] = ['CLASS', 'ID', 'NAME', 'VBASE', 'GX', 'GY', 'SX', 'SY', 'EXIST', 'VMIN', 'VMAX', 'NCMPLAN'] # fill to fit...
if tpe in ['APOIO', 'ARM', 'CX', 'CXN', 'LOAD']:
df = data_structures['Nodes'][tpe]
for i in range(df.shape[0]):
name = 'B' + str(len(circuit.buses) + 1) + '_' + str(
df['NAME'].values[i])
Vnom = float(df['VBASE'].values[i])
x = float(df['GX'].values[i]) / contraction_factor
y = float(df['GY'].values[i]) / contraction_factor
id_ = df['ID'].values[i]
bus = Bus(name=name,
vnom=Vnom,
xpos=x,
ypos=y,
height=40,
width=60)
circuit.add_bus(bus)
buses_id_dict[id_] = bus
# Network Equivalent
# __headers__['Nodes']['EQUIV'] = ['CLASS', 'ID', 'NAME', 'VBASE', 'GX', 'GY', 'SX', 'SY', 'VMIN', 'VMAX', 'ZONE',
# 'SEPNET', 'AUTOUP', 'P', 'Q', 'ELAST', 'SIMUL', 'HTYP', 'HARM5', 'HARM7',
# 'HARM11',
# 'HARM13', 'NOGRW', 'RS', 'XS', 'R1', 'X1', 'R2', 'X2', 'RH', 'XH', 'COM']
elif tpe == 'EQUIV':
df = data_structures['Nodes'][tpe]
for i in range(df.shape[0]):
name = 'B' + str(len(circuit.buses) + 1) + '_' + str(
df['NAME'].values[i])
Vnom = float(df['VBASE'].values[i])
x = float(df['GX'].values[i]) / contraction_factor
y = float(df['GY'].values[i]) / contraction_factor
id_ = df['ID'].values[i]
bus = Bus(name=name,
vnom=Vnom,
xpos=x,
ypos=y,
height=40,
width=60,
is_slack=True)
circuit.add_bus(bus)
buses_id_dict[id_] = bus
name = 'LD' + str(len(circuit.buses)) + '_' + str(
df['NAME'].values[i])
p = float(df['P'].values[i]) * Sbase
q = float(df['Q'].values[i]) * Sbase
load = Load(name=name, power=complex(p, q))
circuit.add_load(bus, load)
# Generator
# __headers__['Nodes']['GEN'] = ['CLASS', 'ID', 'NAME', 'VBASE', 'GX', 'GY', 'SX', 'SY', 'EXIST', 'MODEL', 'VMIN',
# 'VMAX',
# 'V', 'ENAB', 'P', 'Q', 'QMIN', 'QMAX', 'ELAST', 'HTYP', 'HARM5', 'HARM7',
# 'HARM11',
# 'HARM13', 'VNOM', 'RAT', 'TGEN', 'COST', 'YEAR']
elif tpe == 'GEN':
df = data_structures['Nodes'][tpe]
for i in range(df.shape[0]):
name = 'B' + str(len(circuit.buses) + 1) + '_' + str(
df['NAME'].values[i])
Vnom = float(df['VBASE'].values[i])
x = float(df['GX'].values[i]) / contraction_factor
y = float(df['GY'].values[i]) / contraction_factor
id_ = df['ID'].values[i]
bus = Bus(name=name,
vnom=Vnom,
xpos=x,
ypos=y,
height=40,
width=60)
circuit.add_bus(bus)
buses_id_dict[id_] = bus
mode = int(df['MODEL'].values[i])
if mode == 1:
name = 'GEN' + str(len(circuit.buses)) + '_' + str(
df['NAME'].values[i])
p = float(df['P'].values[i]) * Sbase
q = float(df['Q'].values[i]) * Sbase
v = float(df['V'].values[i]) # p.u.
gen = ControlledGenerator(name=name,
active_power=p,
voltage_module=v)
circuit.add_controlled_generator(bus, gen)
else:
name = 'GENSTAT' + str(len(circuit.buses)) + '_' + str(
df['NAME'].values[i])
p = float(df['P'].values[i]) * Sbase
q = float(df['Q'].values[i]) * Sbase
gen = StaticGenerator(name=name, power=complex(p, q))
circuit.add_static_generator(bus, gen)
# Transformation station
# __headers__['Nodes']['PT'] = ['CLASS', 'ID', 'NAME', 'VBASE', 'GX', 'GY', 'SX', 'SY', 'EXIST', 'VMIN', 'VMAX',
# 'ZONE',
# 'ENAB', 'P', 'Q', 'ELAST', 'SIMUL', 'HTYP', 'HARM5', 'HARM7', 'HARM11', 'HARM13',
# 'NOGRW',
# 'EQEXIST', 'EQPOSS1', 'MCOST1', 'ICOST1', 'EQPOSS2', 'MCOST2', 'ICOST2',
# 'EQPOSS3', 'MCOST3',
# 'ICOST3', 'NCLI', 'EQTYPE', 'YEAR', 'COM', 'INFOCOM', 'ID_AUX']
elif tpe in ['PT', 'PTC']:
df = data_structures['Nodes'][tpe]
for i in range(df.shape[0]):
name = 'B' + str(len(circuit.buses) + 1) + '_' + str(
df['NAME'].values[i])
Vnom = float(df['VBASE'].values[i])
x = float(df['GX'].values[i]) / contraction_factor
y = float(df['GY'].values[i]) / contraction_factor
id_ = df['ID'].values[i]
bus = Bus(name=name,
vnom=Vnom,
xpos=x,
ypos=y,
height=40,
width=60)
name = 'LD' + str(len(circuit.buses) + 1) + '_' + str(
df['NAME'].values[i])
p = float(df['P'].values[i]) * Sbase
q = float(df['Q'].values[i]) * Sbase
load = Load(name=name, power=complex(p, q))
circuit.add_bus(bus)
circuit.add_load(bus, load)
buses_id_dict[id_] = bus
# Reference node
# __headers__['Nodes']['REF'] = ['CLASS', 'ID', 'NAME', 'VBASE', 'GX', 'GY', 'SX', 'SY', 'VREF', 'RAT',
# 'COST', 'TGEN', 'YEAR']
elif tpe == 'REF':
df = data_structures['Nodes'][tpe]
for i in range(df.shape[0]):
name = 'B' + str(len(circuit.buses) + 1) + '_' + str(
df['NAME'].values[i])
Vnom = float(df['VBASE'].values[i])
x = float(df['GX'].values[i]) / contraction_factor
y = float(df['GY'].values[i]) / contraction_factor
id_ = df['ID'].values[i]
bus = Bus(name=name,
vnom=Vnom,
xpos=x,
ypos=y,
height=40,
width=60,
is_slack=True)
circuit.add_bus(bus)
buses_id_dict[id_] = bus
# Voltage Transformer
# __headers__['Nodes']['TT'] = ['CLASS', 'ID', 'NAME', 'VBASE', 'GX', 'GY', 'SX', 'SY', 'EXIST', 'VMIN', 'VMAX',
# 'DISABLE', 'HARM5', 'HARM7', 'HARM11', 'HARM13', 'EQEXIST', 'TAP', 'YEAR',
# 'ID_AUX']
elif tpe == 'TT':
df = data_structures['Nodes'][tpe]
for i in range(df.shape[0]):
name = 'B' + str(len(circuit.buses) + 1) + '_' + str(
df['NAME'].values[i])
Vnom = float(df['VBASE'].values[i])
x = float(df['GX'].values[i]) / contraction_factor
y = float(df['GY'].values[i]) / contraction_factor
id_ = df['ID'].values[i]
bus = Bus(name=name,
vnom=Vnom,
xpos=x,
ypos=y,
height=40,
width=60)
circuit.add_bus(bus)
buses_id_dict[id_] = bus
else:
logger.append(tpe + ' not recognised under Nodes')
# create branches
for tpe in data_structures['Branches']:
# Condenser series or shunt
# __headers__['Branches']['CAP'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'EXIST', 'STAT', 'PERM', 'EQ', 'YEAR']
if tpe in ['CAP', 'IND']:
df = data_structures['Branches'][tpe]
for i in range(df.shape[0]):
name = df['NAME'].values[i]
id1 = df['ID1'].values[i]
id2 = df['ID2'].values[i]
b1 = buses_id_dict[id1]
b2 = buses_id_dict[id2]
# get equipment reference in the catalogue
eq_id = df['EQ'].values[i]
df_cat = data_structures['CatalogBranch'][tpe]
cat_elm = df_cat[df_cat['EQ'] == eq_id]
try:
x = float(cat_elm['REAC'].values[0]) * Sbase
except:
x = 1e-20
br = Branch(bus_from=b1,
bus_to=b2,
name=name,
x=x,
branch_type=BranchType.Branch)
circuit.add_branch(br)
# Estimator
# __headers__['Branches']['ESTIM'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'INDEP', 'I', 'SIMULT']
if tpe in ['ESTIM']:
df = data_structures['Branches'][tpe]
for i in range(df.shape[0]):
name = df['NAME'].values[i]
id1 = df['ID1'].values[i]
id2 = df['ID2'].values[i]
b1 = buses_id_dict[id1]
b2 = buses_id_dict[id2]
br = Branch(bus_from=b1,
bus_to=b2,
name=name,
branch_type=BranchType.Branch)
circuit.add_branch(br)
# Breaker
# __headers__['Branches']['DISJ'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'EXIST', 'STAT', 'PERM', 'FAILRT',
# 'TISOL', 'TRECONF', 'TREPAIR', 'EQ', 'YEAR', 'CONTROL']
# Fuse
# __headers__['Branches']['FUS'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'EXIST', 'STAT', 'PERM', 'FAILRT',
# 'TISOL','TRECONF', 'TREPAIR', 'EQ', 'YEAR']
# Switch
# __headers__['Branches']['INTR'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'EXIST', 'STAT', 'PERM', 'FAILRT',
# 'TISOL', 'TRECONF', 'TREPAIR', 'EQ', 'YEAR', 'DRIVE', 'CONTROL']
# Disconnector
# __headers__['Branches']['SECC'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'EXIST', 'STAT', 'PERM', 'FAILRT',
# 'TISOL', 'TRECONF', 'TREPAIR', 'EQ', 'YEAR', 'DRIVE', 'CONTROL']
if tpe in ['DISJ', 'FUS', 'INTR', 'SECC']:
df = data_structures['Branches'][tpe]
for i in range(df.shape[0]):
name = df['NAME'].values[i]
id1 = df['ID1'].values[i]
id2 = df['ID2'].values[i]
state = bool(int(df['STAT'].values[i]))
b1 = buses_id_dict[id1]
b2 = buses_id_dict[id2]
br = Branch(bus_from=b1,
bus_to=b2,
name=name,
active=state,
branch_type=BranchType.Switch)
circuit.add_branch(br)
# Lines, cables and bars
# fill until it fits or truncate the data
# __headers__['Branches']['LINE'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'EXIST', 'COLOR', 'GEOLEN', 'LEN',
# 'STAT',
# 'PERM', 'FAILRT', 'TISOL', 'TRECONF', 'TREPAIR', 'RERAT', 'EQEXIST', 'NPOSS',
# 'CHOOSEQ', 'INSRTCOST', 'EQPOSS1', 'MATCOST1', 'EQPOSS2', 'MATCOST2',
# 'EQPOSS3',
# 'MATCOST3', 'NCOOG', 'GX1', 'GY1', 'GX2', 'GY2']
if tpe in ['LINE']:
df = data_structures['Branches'][tpe]
for i in range(df.shape[0]):
name = df['NAME'].values[i]
id1 = df['ID1'].values[i]
id2 = df['ID2'].values[i]
b1 = buses_id_dict[id1]
b2 = buses_id_dict[id2]
length = float(df['LEN'].values[i])
# get equipment reference in the catalogue
eq_id = df['EQEXIST'].values[i]
df_cat = data_structures['CatalogBranch'][tpe]
cat_elm = df_cat[df_cat['EQ'] == eq_id]
try:
r = float(cat_elm['R'].values[0]) * length / 1000
except:
r = 1e-20
try:
x = float(cat_elm['X'].values[0]) * length / 1000
except:
x = 1e-20
try:
b = float(cat_elm['B'].values[0]) * length / 1000
except:
b = 1e-20
Imax = float(
cat_elm['RATTYP'].values[0]) / 1000.0 # pass from A to kA
Vnom = float(cat_elm['VNOM'].values[0]) # kV
Smax = Imax * Vnom * SQRT3 # MVA
# correct for zero values which are problematic
r = r if r > 0.0 else 1e-20
x = x if x > 0.0 else 1e-20
b = b if b > 0.0 else 1e-20
br = Branch(bus_from=b1,
bus_to=b2,
name=name,
r=r,
x=x,
b=b,
rate=Smax,
length=length,
branch_type=BranchType.Line)
circuit.add_branch(br)
# Intensity Transformer
# __headers__['Branches']['TI'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'INDEP', 'I', 'SIMULT', 'EXIST', 'STAT',
# 'PERM', 'FAILRT', 'TISOL', 'TRECONF', 'TREPAIR', 'EQ', 'TAP1', 'TAP2', 'YEAR']
if tpe in ['TI']:
df = data_structures['Branches'][tpe]
for i in range(df.shape[0]):
name = df['NAME'].values[i]
id1 = df['ID1'].values[i]
id2 = df['ID2'].values[i]
b1 = buses_id_dict[id1]
b2 = buses_id_dict[id2]
# get equipment reference in the catalogue
eq_id = df['EQ'].values[i]
df_cat = data_structures['CatalogBranch'][tpe]
cat_elm = df_cat[df_cat['EQ'] == eq_id]
br = Branch(bus_from=b1,
bus_to=b2,
name=name,
branch_type=BranchType.Transformer)
circuit.add_branch(br)
# Self-transformer
# __headers__['Branches']['XFORM1'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'ID3', 'ID1N', 'ID2N', 'ID3N',
# 'EXIST',
# 'STAT', 'FAILRT', 'TISOL', 'TRECONF', 'TREPAIR', 'RERAT', 'CON1', 'RE1',
# 'XE1',
# 'CON2', 'RE2', 'XE2', 'CON3', 'RE3', 'XE3', 'LOSS', 'TPERM', 'SETVSEL',
# 'SETV',
# 'EQ', 'TAP1', 'TAP2', 'TAP3', 'YEAR', 'NUM']
if tpe in ['XFORM1', 'XFORM2']:
df = data_structures['Branches'][tpe]
for i in range(df.shape[0]):
name = df['NAME'].values[i]
id1 = df['ID1'].values[i]
id2 = df['ID2'].values[i]
b1 = buses_id_dict[id1]
b2 = buses_id_dict[id2]
# get equipment reference in the catalogue
# eq_id = df['EQ'].values[i]
eq_id = df['XE3'].values[
i] # to correct the bad data formatting these file has...
df_cat = data_structures['CatalogBranch'][tpe]
cat_elm = df_cat[df_cat['EQ'] == eq_id]
if cat_elm.shape[0] > 0:
r1 = float(cat_elm['RD1'].values[0])
r2 = float(cat_elm['RD2'].values[0])
x1 = float(cat_elm['XD1'].values[0])
x2 = float(cat_elm['XD2'].values[0])
s1 = float(cat_elm['SNOMTYP1'].values[0]
) / 1000.0 # from kVA to MVA
s2 = float(cat_elm['SNOMTYP2'].values[0]
) / 1000.0 # from kVA to MVA
r = r1 + r2
x = x1 + x2
s = s1 + s2
r = r if r > 0.0 else 1e-20
x = x if x > 0.0 else 1e-20
s = s if s > 0.0 else 1e-20
else:
r = 1e-20
x = 1e-20
s = 1e-20
logger.append('The ' + tpe + ' type ' + eq_id +
' was not found.')
br = Branch(bus_from=b1,
bus_to=b2,
name=name,
r=r,
x=x,
rate=s,
branch_type=BranchType.Transformer)
circuit.add_branch(br)
# 3-winding transformer
# __headers__['Branches']['XFORM3'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'ID3', 'ID1N', 'ID2N', 'ID3N',
# 'EXIST',
# 'STAT', 'FAILRT', 'TISOL', 'TRECONF', 'TREPAIR', 'RERAT', 'CON1', 'RE1',
# 'XE1',
# 'CON2', 'RE2', 'XE2', 'CON3', 'RE3', 'XE3', 'LOSS', 'TPERM', 'SETVSEL',
# 'SETV',
# 'EQ', 'TAP1', 'TAP2', 'TAP3', 'YEAR', 'NUM']
if tpe in ['XFORM3']:
df = data_structures['Branches'][tpe]
for i in range(df.shape[0]):
name = df['NAME'].values[i]
id1 = df['ID1'].values[i]
id2 = df['ID2'].values[i]
id3 = df['ID3'].values[i]
b1 = buses_id_dict[id1]
b2 = buses_id_dict[id2]
b3 = buses_id_dict[id3]
# get equipment reference in the catalogue
eq_id = df['EQ'].values[i]
df_cat = data_structures['CatalogBranch'][tpe]
cat_elm = df_cat[df_cat['EQ'] == eq_id]
r1 = float(cat_elm['RD1'].values[0])
r2 = float(cat_elm['RD2'].values[0])
r3 = float(cat_elm['RD3'].values[0])
x1 = float(cat_elm['XD1'].values[0])
x2 = float(cat_elm['XD2'].values[0])
x3 = float(cat_elm['XD3'].values[0])
s1 = float(
cat_elm['SNOMTYP1'].values[0]) / 1000.0 # from kVA to MVA
s2 = float(
cat_elm['SNOMTYP2'].values[0]) / 1000.0 # from kVA to MVA
s3 = float(
cat_elm['SNOMTYP3'].values[0]) / 1000.0 # from kVA to MVA
r12 = r1 + r2
x12 = x1 + x2
s12 = s1 + s2
r13 = r1 + r3
x13 = x1 + x3
s13 = s1 + s3
r23 = r2 + r3
x23 = x2 + x3
s23 = s2 + s3
r12 = r12 if r12 > 0.0 else 1e-20
x12 = x12 if x12 > 0.0 else 1e-20
s12 = s12 if s12 > 0.0 else 1e-20
r13 = r13 if r13 > 0.0 else 1e-20
x13 = x13 if x13 > 0.0 else 1e-20
s13 = s13 if s13 > 0.0 else 1e-20
r23 = r23 if r23 > 0.0 else 1e-20
x23 = x23 if x23 > 0.0 else 1e-20
s23 = s23 if s23 > 0.0 else 1e-20
br = Branch(bus_from=b1,
bus_to=b2,
name=name,
r=r12,
x=x12,
rate=s12,
branch_type=BranchType.Transformer)
circuit.add_branch(br)
br = Branch(bus_from=b1,
bus_to=b3,
name=name,
r=r13,
x=x13,
rate=s13,
branch_type=BranchType.Transformer)
circuit.add_branch(br)
br = Branch(bus_from=b2,
bus_to=b3,
name=name,
r=r23,
x=x23,
rate=s23,
branch_type=BranchType.Transformer)
circuit.add_branch(br)
# Neutral impedance
# __headers__['Branches']['ZN'] = ['CLASS', 'ID', 'NAME', 'ID1', 'ID2', 'EXIST', 'STAT', 'PERM', 'FAILRT',
# 'TISOL','TRECONF', 'TREPAIR', 'EQ', 'YEAR']
if tpe in ['ZN']:
df = data_structures['Branches'][tpe]
for i in range(df.shape[0]):
name = df['NAME'].values[i]
id1 = df['ID1'].values[i]
id2 = df['ID2'].values[i]
b1 = buses_id_dict[id1]
b2 = buses_id_dict[id2]
br = Branch(bus_from=b1,
bus_to=b2,
name=name,
branch_type=BranchType.Branch)
circuit.add_branch(br)
# return the circuit and the logs
return circuit, logger
def get_branches_of_bus(B, j):
"""
Get the indices of the branches connected to the bus j
:param B: Branch-bus CSC matrix
:param j: bus index
:return: list of branches in the bus
"""
return [B.indices[k] for k in range(B.indptr[j], B.indptr[j + 1])]
if __name__ == '__main__':
fname = 'D:\\GitHub\\GridCal\\Grids_and_profiles\\grids\\Reduction Model 2.xlsx'
circuit = MultiCircuit()
circuit.load_file(fname)
circuit.compile()
# form C
threshold = 1e-5
m = len(circuit.branches)
n = len(circuit.buses)
C = lil_matrix((m, n), dtype=int)
buses_dict = {bus: i for i, bus in enumerate(circuit.buses)}
branches_to_keep_idx = list()
branches_to_remove_idx = list()
states = np.zeros(m, dtype=int)
br_idx = [None] * m
graph = Graph()
"""
# Sbase shortcut
Sbase = self.numerical_circuit.Sbase
data = self.get_branch_flows() * Sbase
df = pd.DataFrame(data=data,
index=self.numerical_circuit.branch_names,
columns=['Branch flow (MW)'])
return df
if __name__ == '__main__':
main_circuit = MultiCircuit()
# fname = 'D:\\GitHub\\GridCal\\Grids_and_profiles\\grids\\lynn5buspv.xlsx'
fname = 'D:\\GitHub\\GridCal\\Grids_and_profiles\\grids\\IEEE 30 Bus with storage.xlsx'
# fname = 'C:\\Users\\spenate\\Documents\\PROYECTOS\\Sensible\\Report\\Test3 - Batteries\\Evora test 3 with storage.xlsx'
# fname = '/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/IEEE 30 Bus with storage.xlsx'
print('Reading...')
main_circuit.load_file(fname)
problem = DcOpf(main_circuit,
allow_load_shedding=True,
allow_generation_shedding=True)
# run default state
problem.build_solvers()
problem.set_default_state()
def load_iPA(file_name):
circuit = MultiCircuit()
with open(file_name) as json_file:
data = json.load(json_file)
# elements dictionaries
xfrm_dict = {entry['IdEnRed']: entry for entry in data['Transformadores']}
# nodes_dict = {entry['id']: entry for entry in data['Nudos']}
nodes_dict = dict()
buses_dict = dict()
for entry in data['Nudos']:
nodes_dict[entry['id']] = entry
bus = Bus(name=str(entry['id']))
buses_dict[entry['id']] = bus
if entry['id'] > 0: # omit the node 0 because it is the "earth node"...
circuit.add_bus(bus)
gen_dict = {entry['IdEnRed']: entry for entry in data['Generadores']}
load_dict = {entry['IdEnRed']: entry for entry in data['Consumos']}
sw_dict = {entry['IdEnRed']: entry for entry in data['Interruptores']}
# main grid
vector_red = data['Red']
'''
{'id': 0,
'Tipo': 1,
'E': 0,
'EFase': 0,
'Tomas': 0,
'R1': 1e-05,
'X1': 1e-05,
'R0': 1e-05,
'X0': 1e-05,
'RN': 1e-05,
'XN': 1e-05,
'P': 0,
'Q': 0,
'Nudo1': 2410,
'Nudo2': 2403,
'Carga_Max': -1,
'ClassID': 1090,
'ClassMEMBER': 98076366,
'Conf': 'abc',
'LineaMT': '2030:98075347',
'Unom': 15.0}
'''
for entry in vector_red:
# pick the general attributes
identifier = entry['id']
tpe = entry['Tipo']
n1_id = entry['Nudo1']
n2_id = entry['Nudo2']
# get the Bus objects associated to the bus indices
if n1_id in buses_dict.keys():
bus1 = buses_dict[n1_id]
if n2_id in buses_dict.keys():
bus2 = buses_dict[n2_id]
if tpe == 0: # Fuente de Tensión(elemento Ptheta)
# pick the bus that is not the earth bus...
if n1_id == 0:
bus = bus2
else:
bus = bus1
bus.is_slack = True
elm = ControlledGenerator(name='Slack')
circuit.add_controlled_generator(bus, elm)
elif tpe == 1: # Elemento impedancia(lineas)
V = entry['Unom']
Zbase = V * V / circuit.Sbase
if identifier in load_dict.keys():
# load!!!
print('Load found in lines: WTF?')
else:
# line!!!
r = entry['R1'] / Zbase
x = entry['X1'] / Zbase
if r > 1e-5:
branch_type = BranchType.Line
else:
# mark as "generic branch" the branches with very low resistance
branch_type = BranchType.Branch
elm = Branch(bus_from=bus1,
bus_to=bus2,
name=str(identifier),
r=r,
x=x,
branch_type=branch_type)
circuit.add_branch(elm)
elif tpe == 2: # Elemento PQ
# pick the bus that is not the earth bus...
if n1_id == 0:
bus = bus2
else:
bus = bus1
p = entry['P'] # power in MW
q = entry['Q']
elm = Load(name=str(identifier), power=complex(p, q) * 1e-3)
circuit.add_load(bus, elm)
elif tpe == 3: # Elemento PV
pass
elif tpe == 4: # Reg de tensión
V = entry['Unom']
Zbase = V * V / circuit.Sbase
r = entry['R1'] / Zbase
x = entry['X1'] / Zbase
elm = Branch(bus_from=bus1,
bus_to=bus2,
name=str(identifier),
r=r,
x=x,
branch_type=BranchType.Transformer)
circuit.add_branch(elm)
elif tpe == 5: # Transformador
V = entry['Unom']
Zbase = V * V / circuit.Sbase
r = entry['R1'] / Zbase
x = entry['X1'] / Zbase
elm = Branch(bus_from=bus1,
bus_to=bus2,
name=str(identifier),
r=r,
x=x,
branch_type=BranchType.Transformer)
circuit.add_branch(elm)
# return the circuit
return circuit
def __init__(self, multi_circuit: MultiCircuit, options: PowerFlowOptions, verbose=False, break_at_value=True,
good_enough_value=0):
self.break_at_value = break_at_value
self.good_enough_value = good_enough_value
self.multi_circuit = multi_circuit
self.numerical_circuit = self.multi_circuit.compile()
self.calculation_inputs = self.numerical_circuit.compute(add_storage=False, add_generation=True)
self.pf = PowerFlowMP(self.multi_circuit, options)
# indices of generators that contribute to the static power vector 'S'
self.gen_s_idx = np.where((np.logical_not(self.numerical_circuit.controlled_gen_dispatchable)
* self.numerical_circuit.controlled_gen_enabled) == True)[0]
self.bat_s_idx = np.where((np.logical_not(self.numerical_circuit.battery_dispatchable)
* self.numerical_circuit.battery_enabled) == True)[0]
# indices of generators that are to be optimized via the solution vector 'x'
self.gen_x_idx = np.where((self.numerical_circuit.controlled_gen_dispatchable
* self.numerical_circuit.controlled_gen_enabled) == True)[0]
self.bat_x_idx = np.where((self.numerical_circuit.battery_dispatchable
* self.numerical_circuit.battery_enabled) == True)[0]
self.n_batteries = len(self.numerical_circuit.battery_power)
self.n_controlled_gen = len(self.numerical_circuit.controlled_gen_power)
# compute the problem dimension
self.dim = len(self.gen_x_idx) + len(self.bat_x_idx)
# get the limits of the devices to control
gens = np.array(multi_circuit.get_controlled_generators())
bats = np.array(multi_circuit.get_batteries())
gen_x_up = np.array([elm.Pmax for elm in gens[self.gen_x_idx]])
gen_x_low = np.array([elm.Pmin for elm in gens[self.gen_x_idx]])
bat_x_up = np.array([elm.Pmax for elm in bats[self.bat_x_idx]])
bat_x_low = np.array([elm.Pmin for elm in bats[self.bat_x_idx]])
self.ngen = len(self.gen_x_idx)
self.xlow = np.r_[gen_x_low, bat_x_low] / self.multi_circuit.Sbase
self.xup = np.r_[gen_x_up, bat_x_up] / self.multi_circuit.Sbase
self.range = self.xup - self.xlow
# form S static ################################################################################################
# all the loads apply
self.Sfix = None
self.set_default_state() # build Sfix
self.Vbus = np.ones(self.numerical_circuit.nbus, dtype=complex)
self.Ibus = np.zeros(self.numerical_circuit.nbus, dtype=complex)
# other vars needed ############################################################################################
self.converged = False
self.result = None
self.force_batteries_to_charge = False
self.x = np.zeros(self.dim)
self.fx = 0
self.t = 0
self.Emin = None
self.Emax = None
self.E = None
self.bat_idx = None
self.battery_loading_pu = 0.01
self.dt = 0
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%).
"""
grid = MultiCircuit(name=test_name)
grid.Sbase = Sbase
grid.time_profile = None
grid.logger = list()
# 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 = ControlledGenerator(name="Utility")
UT.bus = POI
grid.add_controlled_generator(POI, UT)
# Create static generators (with fixed power factor)
M32 = StaticGenerator(name="M32", power=4.2 + 0.0j) # 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=complexe(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=complexe(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()
grid.compile()
options = PowerFlowOptions(SolverType.NR,
verbose=True,
robust=True,
initialize_with_existing_solution=True,
multi_core=True,
control_q=True,
control_taps=True,
tolerance=1e-6,
max_iter=15)
power_flow = PowerFlow(grid, options)
power_flow.run()
print()
print(f"Test: {test_name}")
print()
print("Controlled generators:")
for g in grid.get_controlled_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.Copper_losses)}kW, "
f"Iron losses={int(t.Iron_losses)}kW, SC voltage={t.Short_circuit_voltage}%"
)
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
d = {1: 'PQ', 2: 'PV', 3: 'VD'}
tpe_str = array([d[i] for i in tpe], dtype=object)
data = c_[tpe_str, Sbus.real, Sbus.imag, vm, va]
cols = ['Type', 'P', 'Q', '|V|', 'angle']
df = pd.DataFrame(data=data, columns=cols)
return df
if __name__ == '__main__':
from GridCal.Engine.CalculationEngine import MultiCircuit, PowerFlowOptions, PowerFlow, SolverType
from matplotlib import pyplot as plt
grid = MultiCircuit()
# grid.load_file('lynn5buspq.xlsx')
# grid.load_file('lynn5buspv.xlsx')
# grid.load_file('IEEE30.xlsx')
# grid.load_file('/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/IEEE 14.xlsx')
# grid.load_file('/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/IEEE39.xlsx')
# grid.load_file('/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/1354 Pegase.xlsx')
grid.load_file(
'/home/santi/Documentos/GitHub/GridCal/UnderDevelopment/GridCal/Monash2.xlsx'
)
grid.compile()
circuit = grid.circuits[0]
print('\nYbus:\n', circuit.power_flow_input.Ybus.todense())
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%).
"""
grid = MultiCircuit(name=test_name)
grid.Sbase = Sbase
grid.time_profile = None
grid.logger = list()
# 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 = ControlledGenerator(name="Utility")
UT.bus = POI
grid.add_controlled_generator(POI, UT)
# Create static generators (with fixed power factor)
M32 = StaticGenerator(name="M32", power=4.2 + 0.0j) # 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=complexe(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=complexe(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()
grid.compile()
options = PowerFlowOptions(SolverType.LM,
verbose=True,
robust=True,
initialize_with_existing_solution=True,
multi_core=True,
control_q=True,
tolerance=1e-6,
max_iter=99)
power_flow = PowerFlow(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("Controlled generators:")
for g in grid.get_controlled_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.Copper_losses)}kW, Iron losses={int(t.Iron_losses)}kW, SC voltage={t.Short_circuit_voltage}%"
)
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
class Blockchain:
def __init__(self, agent_id_to_grid_id, fname='Grid.xlsx', dt=1):
self.current_transactions = Transactions()
self.chain = []
self.nodes = set()
self.agent_id_to_grid_id = agent_id_to_grid_id
self.actors_group = ActorsGroup()
self.market = Market(actors_group=self.actors_group)
self.dt = dt
self.grid = MultiCircuit()
self.grid.load_file(fname)
# Create the genesis block
self.new_block(previous_hash='1', proof=100)
def register_node(self, address):
"""
Add a new node to the list of nodes
:param address: Address of node. Eg. 'http://192.168.0.5:5000'
"""
parsed_url = urlparse(address)
if parsed_url.netloc:
self.nodes.add(parsed_url.netloc)
elif parsed_url.path:
# Accepts an URL without scheme like '192.168.0.5:5000'.
self.nodes.add(parsed_url.path)
else:
raise ValueError('Invalid URL')
def valid_chain(self, chain):
"""
Determine if a given blockchain is valid
:param chain: A blockchain
:return: True if valid, False if not
"""
last_block = chain[0]
current_index = 1
while current_index < len(chain):
block = chain[current_index]
print(f'{last_block}')
print(f'{block}')
print("\n-----------\n")
# Check that the hash of the block is correct
last_block_hash = self.hash(last_block)
if block['previous_hash'] != last_block_hash:
return False
# Check that the Proof of Work is correct
if not self.valid_proof(last_block['proof'], block['proof'], last_block_hash):
return False
last_block = block
current_index += 1
return True
def resolve_conflicts(self):
"""
This is our consensus algorithm, it resolves conflicts
by replacing our chain with the longest one in the network.
:return: True if our chain was replaced, False if not
"""
neighbours = self.nodes
new_chain = None
# We're only looking for chains longer than ours
max_length = len(self.chain)
# Grab and verify the chains from all the nodes in our network
for node in neighbours:
response = requests.get(f'http://{node}/chain')
if response.status_code == 200:
length = response.json()['length']
chain = response.json()['chain']
# Check if the length is longer and the chain is valid
if length > max_length and self.valid_chain(chain):
max_length = length
new_chain = chain
# Replace our chain if we discovered a new, valid chain longer than ours
if new_chain:
self.chain = new_chain
return True
return False
def new_block(self, proof, previous_hash):
"""
Create a new Block in the Blockchain
:param proof: The proof given by the Proof of Work algorithm
:param previous_hash: Hash of previous Block
:return: New Block
"""
block = {
'index': len(self.chain) + 1,
'timestamp': time(),
'transactions': self.current_transactions,
'proof': proof,
'previous_hash': previous_hash or self.hash(self.chain[-1]),
}
# Reset the current list of transactions
self.current_transactions = []
self.chain.append(block)
return block
def new_transaction(self, sender, recipient, energy_amount, price, bid_type, electric_hash):
"""
Creates a new transaction to go into the next mined Block
:param sender: Address of the Sender
:param recipient: Address of the Recipient
:param amount: Amount
:return: The index of the Block that will hold this transaction
"""
tr = Transaction(bid_id=len(self.current_transactions), # this may be repeated but it is only used to print
seller_id=sender, buyer_id=recipient, energy_amount=energy_amount,
price=price, bid_type=bid_type, bid_hash=electric_hash)
# self.current_transactions.append({
# 'sender': sender,
# 'recipient': recipient,
# 'energy_amount': energy_amount,
# 'price': price,
# 'bid_type': bid_type,
# 'electric_hash': electric_hash
# })
self.current_transactions.append(tr)
return self.last_block['index'] + 1
@property
def last_block(self):
return self.chain[-1]
@staticmethod
def hash(block):
"""
Creates a SHA-256 hash of a Block
:param block: Block
"""
# We must make sure that the Dictionary is Ordered, or we'll have inconsistent hashes
# block_string = json.dumps(block, sort_keys=True).encode()
block_string = str(block['index']) + \
str(block['timestamp']) + \
str(block['proof']) + \
str(block['previous_hash']) + \
str([j.hash for j in block['transactions']])
# block_string = block.
# block_string = block.to_json()
return hashlib.sha256(block_string.encode('UTF-8')).hexdigest()
@staticmethod
def valid_proof( proof ):
"""
Validates the Proof
:param proof: <int> Current Proof
:return: <bool> True if correct, False if not.
"""
return proof != None
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.
"""
grid = MultiCircuit(name=test_name)
grid.Sbase = Sbase
grid.time_profile = None
grid.logger = list()
# 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 = ControlledGenerator(name="Utility")
UT.bus = POI
grid.add_controlled_generator(POI, UT)
# Create static generators (with fixed power factor)
M32 = StaticGenerator(name="M32", power=4.2 + 0.0j) # 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=complexe(z, xr).real * s * 1000 / Sbase,
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=complexe(z, xr).real * s * 1000 / Sbase,
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()
grid.compile()
options = PowerFlowOptions(SolverType.LM,
verbose=True,
robust=True,
initialize_with_existing_solution=True,
multi_core=True,
control_q=True,
tolerance=1e-6,
max_iter=99)
power_flow = PowerFlow(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("Controlled generators:")
for g in grid.get_controlled_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.Copper_losses)}kW, Iron losses={int(t.Iron_losses)}kW, SC voltage={t.Short_circuit_voltage}%"
)
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_1():
"""
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, but their
voltage regulators aren't.
"""
grid = MultiCircuit(name=test_name)
grid.Sbase = Sbase
grid.time_profile = None
grid.logger = list()
# 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 = ControlledGenerator(name="Utility")
UT.bus = POI
grid.add_controlled_generator(POI, UT)
M32 = ControlledGenerator(name="M32",
active_power=4.2,
voltage_module=1.025,
Qmin=-2.5,
Qmax=2.5)
M32.bus = B_LV_M32
grid.add_controlled_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=complexe(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=complexe(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)
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()
grid.compile()
options = PowerFlowOptions(SolverType.LM,
verbose=True,
robust=True,
initialize_with_existing_solution=True,
multi_core=True,
control_q=True,
tolerance=1e-6,
max_iter=99)
power_flow = PowerFlow(grid, options)
power_flow.run()
approx_volt = [round(100*abs(v), 1) for v in power_flow.results.voltage]
solution = [100.0, 100.1, 102.5] # 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("Controlled generators:")
for g in grid.get_controlled_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.Copper_losses)}kW, Iron losses={int(t.Iron_losses)}kW, SC voltage={t.Short_circuit_voltage}%")
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
self.progress_signal.emit(0.0)
self.done_signal.emit()
def cancel(self):
"""
Cancel the simulation
:return:
"""
self.__cancel__ = True
self.progress_signal.emit(0.0)
self.progress_text.emit('Cancelled')
self.done_signal.emit()
if __name__ == '__main__':
from matplotlib import pyplot as plt
# fname = 'D:\\GitHub\\GridCal\\Grids_and_profiles\\grids\\Reduction Model 3.xlsx'
fname = 'D:\\GitHub\\GridCal\\UnderDevelopment\\GridCal\\Engine\\Importers\\Export_sensible_v15_modif.json.xlsx'
circuit_ = MultiCircuit()
circuit_.load_file(fname)
# circuit.compile()
top = TopologyReduction(grid=circuit_,
rx_criteria=False,
rx_threshold=1e-5,
type_criteria=True,
selected_type=BranchType.Branch)
top.run()
# circuit_.compile()
# circuit_.plot_graph()
# plt.show()
def test_gridcal_regulator():
"""
GridCal test for the new implementation of transformer voltage regulators.
"""
grid = MultiCircuit(name=test_name)
grid.Sbase = Sbase
grid.time_profile = None
grid.logger = list()
# 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 = ControlledGenerator(name="Utility")
UT.bus = POI
grid.add_controlled_generator(POI, UT)
# Create static generators (with fixed power factor)
M32 = StaticGenerator(name="M32", power=4.2 + 0.0j) # 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=get_complex(z, xr).real * s * 1000 / 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=get_complex(z, xr).real * s * 1000 / 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()
grid.compile()
options = PowerFlowOptions(SolverType.LM,
verbose=True,
robust=True,
initialize_with_existing_solution=True,
multi_core=True,
control_q=True,
control_taps=True,
tolerance=1e-6,
max_iter=99)
power_flow = PowerFlowMP(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("Controlled generators:")
for g in grid.get_controlled_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}: 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.Copper_losses)}kW, Iron losses={int(t.Iron_losses)}kW, SC voltage={t.Short_circuit_voltage}%"
)
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(f"Voltage settings: {grid.numerical_circuit.vset}")
#print("GridCal logger:")
#for l in grid.logger:
#print(f" - {l}")
equal = True
for i in range(len(approx_volt)):
if approx_volt[i] != solution[i]:
equal = False
assert equal
def __init__(self, multi_circuit: MultiCircuit, verbose=False):
################################################################################################################
# Compilation
################################################################################################################
self.verbose = verbose
self.multi_circuit = multi_circuit
self.numerical_circuit = self.multi_circuit.compile()
self.islands = self.numerical_circuit.compute()
# indices of generators that contribute to the static power vector 'S'
self.gen_s_idx = np.where((np.logical_not(self.numerical_circuit.controlled_gen_dispatchable)
* self.numerical_circuit.controlled_gen_enabled) == True)[0]
self.bat_s_idx = np.where((np.logical_not(self.numerical_circuit.battery_dispatchable)
* self.numerical_circuit.battery_enabled) == True)[0]
# indices of generators that are to be optimized via the solution vector 'x'
self.gen_x_idx = np.where((self.numerical_circuit.controlled_gen_dispatchable
* self.numerical_circuit.controlled_gen_enabled) == True)[0]
self.bat_x_idx = np.where((self.numerical_circuit.battery_dispatchable
* self.numerical_circuit.battery_enabled) == True)[0]
# compute the problem dimension
dim = len(self.gen_x_idx) + len(self.bat_x_idx)
# get the limits of the devices to control
gens = np.array(multi_circuit.get_controlled_generators())
bats = np.array(multi_circuit.get_batteries())
gen_x_up = np.array([elm.Pmax for elm in gens[self.gen_x_idx]])
gen_x_low = np.array([elm.Pmin for elm in gens[self.gen_x_idx]])
bat_x_up = np.array([elm.Pmax for elm in bats[self.bat_x_idx]])
bat_x_low = np.array([elm.Pmin for elm in bats[self.bat_x_idx]])
# form S static ################################################################################################
# all the loads apply
self.Sfix = self.numerical_circuit.C_load_bus.T * (
- self.numerical_circuit.load_power / self.numerical_circuit.Sbase * self.numerical_circuit.load_enabled)
# static generators (all apply)
self.Sfix += self.numerical_circuit.C_sta_gen_bus.T * (
self.numerical_circuit.static_gen_power / self.numerical_circuit.Sbase * self.numerical_circuit.static_gen_enabled)
# controlled generators
self.Sfix += (self.numerical_circuit.C_ctrl_gen_bus[self.gen_s_idx, :]).T * (
self.numerical_circuit.controlled_gen_power[self.gen_s_idx] / self.numerical_circuit.Sbase)
# batteries
self.Sfix += (self.numerical_circuit.C_batt_bus[self.bat_s_idx, :]).T * (
self.numerical_circuit.battery_power[self.bat_s_idx] / self.numerical_circuit.Sbase)
# build A_sys per island #######################################################################################
for island in self.islands:
island.build_linear_ac_sys_mat() # builds the A matrix factorization and stores it internally
################################################################################################################
# internal variables for PySOT
################################################################################################################
self.xlow = np.r_[gen_x_low, bat_x_low] / self.multi_circuit.Sbase
self.xup = np.r_[gen_x_up, bat_x_up] / self.multi_circuit.Sbase
self.dim = dim
self.info = str(dim) + "-dimensional OPF problem"
self.min = 0
self.integer = []
self.continuous = np.arange(0, dim)
check_opt_prob(self)
d = {1: 'PQ', 2: 'PV', 3: 'VD'}
tpe_str = array([d[i] for i in tpe], dtype=object)
data = c_[tpe_str, Sbus.real, Sbus.imag, vm, va]
cols = ['Type', 'P', 'Q', '|V|', 'angle']
df = pd.DataFrame(data=data, columns=cols)
return df
if __name__ == '__main__':
from GridCal.Engine.CalculationEngine import MultiCircuit, PowerFlowOptions, PowerFlow, SolverType
from matplotlib import pyplot as plt
grid = MultiCircuit()
# grid.load_file('lynn5buspq.xlsx')
# grid.load_file('lynn5buspv.xlsx')
# grid.load_file('IEEE30.xlsx')
grid.load_file(
'/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/IEEE 14.xlsx'
)
# grid.load_file('/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/IEEE39.xlsx')
# grid.load_file('/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/1354 Pegase.xlsx')
grid.compile()
circuit = grid.circuits[0]
print('\nYbus:\n', circuit.power_flow_input.Ybus.todense())
print('\nSbus:\n', circuit.power_flow_input.Sbus)
return V, converged, normF, Scalc
########################################################################################################################
# MAIN
########################################################################################################################
if __name__ == "__main__":
from GridCal.Engine.CalculationEngine import MultiCircuit, PowerFlowOptions, PowerFlow, SolverType
import pandas as pd
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)
grid = MultiCircuit()
# grid.load_file('lynn5buspq.xlsx')
grid.load_file('IEEE30.xlsx')
# grid.load_file('/home/santi/Documentos/GitHub/GridCal/Grids_and_profiles/grids/IEEE 145 Bus.xlsx')
grid.compile()
circuit = grid.circuits[0]
print('\nYbus:\n', circuit.power_flow_input.Ybus.todense())
print('\nYseries:\n', circuit.power_flow_input.Yseries.todense())
print('\nYshunt:\n', circuit.power_flow_input.Yshunt)
print('\nSbus:\n', circuit.power_flow_input.Sbus)
print('\nIbus:\n', circuit.power_flow_input.Ibus)
print('\nVbus:\n', circuit.power_flow_input.Vbus)
print('\ntypes:\n', circuit.power_flow_input.types)
print('\npq:\n', circuit.power_flow_input.pq)
