def _add_kt(net, ppc):
bus_lookup = net["_pd2ppc_lookups"]["bus"]
branch = ppc["branch"]
# "trafo/trafo3w" are already corrected in pd2ppc, write parameter kt for trafo
if not net.trafo.empty:
f, t = net["_pd2ppc_lookups"]["branch"]["trafo"]
trafo_df = net["trafo"]
cmax = ppc["bus"][bus_lookup[get_trafo_values(trafo_df, "lv_bus")], C_MAX]
kt = _transformer_correction_factor(trafo_df.vk_percent, trafo_df.vkr_percent,
trafo_df.sn_mva, cmax)
branch[f:t, K_T] = kt
def _add_trafo_sc_impedance_zero(net, ppc, trafo_df=None):
if trafo_df is None:
trafo_df = net["trafo"]
branch_lookup = net["_pd2ppc_lookups"]["branch"]
if not "trafo" in branch_lookup:
return
bus_lookup = net["_pd2ppc_lookups"]["bus"]
mode = net["_options"]["mode"]
trafo_model = net["_options"]["trafo_model"]
f, t = branch_lookup["trafo"]
trafo_df["_ppc_idx"] = range(f, t)
bus_lookup = net["_pd2ppc_lookups"]["bus"]
hv_bus = get_trafo_values(trafo_df, "hv_bus").astype(int)
lv_bus = get_trafo_values(trafo_df, "lv_bus").astype(int)
in_service = get_trafo_values(trafo_df, "in_service").astype(int)
ppc["branch"][f:t, F_BUS] = bus_lookup[hv_bus]
ppc["branch"][f:t, T_BUS] = bus_lookup[lv_bus]
buses_all, gs_all, bs_all = np.array([], dtype=int), np.array([]), \
np.array([])
if mode == "sc":
# Should be considered as connected for all in_service branches
ppc["branch"][f:t, BR_X] = 1e20
ppc["branch"][f:t, BR_R] = 1e20
ppc["branch"][f:t, BR_B] = 0
ppc["branch"][f:t, BR_STATUS] = in_service
else:
ppc["branch"][f:t, BR_STATUS] = 0
if not "vector_group" in trafo_df:
raise ValueError(
"Vector Group of transformer needs to be specified for zero \
sequence modelling \n Try : net.trafo[\"vector_group\"] = 'Dyn'"
)
for vector_group, trafos in trafo_df.groupby("vector_group"):
ppc_idx = trafos["_ppc_idx"].values.astype(int)
if vector_group in ["Yy", "Yd", "Dy", "Dd"]:
continue
vk_percent = trafos["vk_percent"].values.astype(float)
vkr_percent = trafos["vkr_percent"].values.astype(float)
sn_mva = trafos["sn_mva"].values.astype(float)
# Just put pos seq parameter if zero seq parameter is zero
if not "vk0_percent" in trafos:
raise ValueError(
"Short circuit voltage of transformer Vk0 needs to be specified for zero \
sequence modelling \n Try : net.trafo[\"vk0_percent\"] = net.trafo[\"vk_percent\"]"
)
vk0_percent = trafos["vk0_percent"].values.astype(float) if \
trafos["vk0_percent"].values.astype(float).all() != 0. else \
trafos["vk_percent"].values.astype(float)
# Just put pos seq parameter if zero seq parameter is zero
if not "vkr0_percent" in trafos:
raise ValueError(
"Real part of short circuit voltage Vk0(Real) needs to be specified for transformer \
modelling \n Try : net.trafo[\"vkr0_percent\"] = net.trafo[\"vkr_percent\"]"
)
vkr0_percent = trafos["vkr0_percent"].values.astype(float) if \
trafos["vkr0_percent"].values.astype(float).all() != 0. else \
trafos["vkr_percent"].values.astype(float)
lv_buses = trafos["lv_bus"].values.astype(int)
hv_buses = trafos["hv_bus"].values.astype(int)
lv_buses_ppc = bus_lookup[lv_buses]
hv_buses_ppc = bus_lookup[hv_buses]
if not "mag0_percent" in trafos:
# For Shell Type transformers vk0 = vk * 1
# and mag0_percent = 10 ... 100 Zm0/ Zsc0
# --pg 50 DigSilent Power Factory Transformer manual
raise ValueError(
"Magnetizing impedance to vk0 ratio needs to be specified for transformer \
modelling \n Try : net.trafo[\"mag0_percent\"] = 100"
)
mag0_ratio = trafos.mag0_percent.values.astype(float)
if not "mag0_rx" in trafos:
raise ValueError(
"Magnetizing impedance R/X ratio needs to be specified for transformer \
modelling \n Try : net.trafo[\"mag0_rx\"] = 0 ")
mag0_rx = trafos["mag0_rx"].values.astype(float)
if not "si0_hv_partial" in trafos:
raise ValueError(
"Zero sequence short circuit impedance partition towards HV side needs to be specified for transformer \
modelling \n Try : net.trafo[\"si0_hv_partial\"] = 0.9 "
)
si0_hv_partial = trafos.si0_hv_partial.values.astype(float)
parallel = trafos.parallel.values.astype(float)
in_service = trafos["in_service"].astype(int)
ppc["branch"][ppc_idx, F_BUS] = hv_buses_ppc
ppc["branch"][ppc_idx, T_BUS] = lv_buses_ppc
vn_trafo_hv, vn_trafo_lv, shift = _calc_tap_from_dataframe(net, trafos)
vn_lv = ppc["bus"][lv_buses_ppc, BASE_KV]
ratio = _calc_nominal_ratio_from_dataframe(ppc, trafos, vn_trafo_hv, \
vn_trafo_lv, bus_lookup)
ppc["branch"][ppc_idx, TAP] = ratio
ppc["branch"][ppc_idx, SHIFT] = shift
# zero seq. transformer impedance
tap_lv = np.square(vn_trafo_lv / vn_lv) * net.sn_mva
if mode == 'pf_3ph':
# =============================================================================
# Changing base from transformer base to Network base to get Zpu(Net)
# Zbase = (kV).squared/S_mva
# Zpu(Net)={Zpu(trafo) * Zb(trafo)} / {Zb(Net)}
# Note:
# Network base voltage is Line-Neutral voltage in each phase
# Line-Neutral voltage= Line-Line Voltage(vn_lv) divided by sq.root(3)
# =============================================================================
tap_lv = np.square(vn_trafo_lv / vn_lv) * (3 * net.sn_mva)
z_sc = vk0_percent / 100. / sn_mva * tap_lv
r_sc = vkr0_percent / 100. / sn_mva * tap_lv
z_sc = z_sc.astype(float)
r_sc = r_sc.astype(float)
x_sc = np.sign(z_sc) * np.sqrt(z_sc**2 - r_sc**2)
# TODO: This equation needs to be checked!
# z0_k = (r_sc + x_sc * 1j) / parallel * max(1, ratio) **2
z0_k = (r_sc + x_sc * 1j) / parallel
y0_k = 1 / z0_k #adding admittance for "pi" model
if mode == "sc": # or trafo_model == "pi":
from pandapower.shortcircuit.idx_bus import C_MAX
cmax = net._ppc["bus"][lv_buses_ppc, C_MAX]
kt = _transformer_correction_factor(vk_percent, vkr_percent, \
sn_mva, cmax)
z0_k *= kt
y0_k = 1 / z0_k
# =============================================================================
# Transformer magnetising impedance for zero sequence
# =============================================================================
z_m = z_sc * mag0_ratio
x_m = z_m / np.sqrt(mag0_rx**2 + 1)
r_m = x_m * mag0_rx
r0_trafo_mag = r_m / parallel
x0_trafo_mag = x_m / parallel
z0_mag = r0_trafo_mag + x0_trafo_mag * 1j
# =============================================================================
# Star - Delta conversion ( T model to Pi Model)
# ----------- |__zc=ZAB__|-----------------
# _| _|
# za=ZAN|_| |_| zb=ZBN
# | |
# =============================================================================
z1 = si0_hv_partial * z0_k
z2 = (1 - si0_hv_partial) * z0_k
z3 = z0_mag
z_temp = z1 * z2 + z2 * z3 + z1 * z3
za = z_temp / z2
# za = z_temp / (z2+z3)
zb = z_temp / z1
# zb = z_temp / (z1+z3)
zc = z_temp / z3 # ZAB Transfer impedance
# zc = z_temp / (z1+z2) # ZAB Transfer impedance
YAB = 1 / zc.astype(complex)
YAN = 1 / za.astype(complex)
YBN = 1 / zb.astype(complex)
# YAB_AN = (zc + za) /(zc * za).astype(complex) # Series conn YAB and YAN
# YAB_BN = (zc + zb) / (zc * zb).astype(complex) # Series conn YAB and YBN
YAB_AN = 1 / (zc + za).astype(complex) # Series conn YAB and YAN
YAB_BN = 1 / (zc + zb).astype(complex) # Series conn YAB and YBN
# y0_k = 1 / z0_k #adding admittance for "pi" model
if vector_group == "Dyn":
buses_all = np.hstack([buses_all, lv_buses_ppc])
if trafo_model == "pi":
y = y0_k # pi model
else:
y = (YAB + YBN).astype(complex) # T model
gs_all = np.hstack([gs_all, y.real * in_service]) * int(
ppc["baseMVA"])
bs_all = np.hstack([bs_all, y.imag * in_service]) * int(
ppc["baseMVA"])
elif vector_group == "YNd":
buses_all = np.hstack([buses_all, hv_buses_ppc])
if trafo_model == "pi":
y = y0_k * ppc["baseMVA"] # pi model
else:
y = (YAB_BN + YAN).astype(complex) #T model
gs_all = np.hstack([gs_all, y.real * in_service]) * int(
ppc["baseMVA"])
bs_all = np.hstack([bs_all, y.imag * in_service]) * int(
ppc["baseMVA"])
elif vector_group == "Yyn":
buses_all = np.hstack([buses_all, lv_buses_ppc])
if trafo_model == "pi":
y = 1 / (z0_mag + z0_k).astype(complex) #pi model
else:
# y = (YAB_AN + YBN).astype(complex) #T model
y = (YAB + YAB_BN + YBN).astype(complex) # T model
gs_all = np.hstack([gs_all, y.real * in_service]) * int(
ppc["baseMVA"])
bs_all = np.hstack([bs_all, y.imag * in_service]) * int(
ppc["baseMVA"])
elif vector_group == "YNyn":
ppc["branch"][ppc_idx, BR_STATUS] = in_service
# zc = ZAB
ppc["branch"][ppc_idx, BR_R] = zc.real
ppc["branch"][ppc_idx, BR_X] = zc.imag
buses_all = np.hstack([buses_all, hv_buses_ppc])
gs_all = np.hstack([gs_all, YAN.real * in_service \
* int(ppc["baseMVA"])])
bs_all = np.hstack([bs_all, YAN.imag * in_service \
* int(ppc["baseMVA"])])
buses_all = np.hstack([buses_all, lv_buses_ppc])
gs_all = np.hstack([gs_all, YBN.real * in_service \
* int(ppc["baseMVA"])])
bs_all = np.hstack([bs_all, YBN.imag * in_service \
* int(ppc["baseMVA"])])
elif vector_group == "YNy":
buses_all = np.hstack([buses_all, hv_buses_ppc])
if trafo_model == "pi":
y = 1 / (z0_mag + z0_k).astype(complex) * int(
ppc["baseMVA"]) #pi model
else:
y = (YAB_BN + YAN).astype(complex) * int(
ppc["baseMVA"]) #T model
gs_all = np.hstack([gs_all, y.real * in_service])
bs_all = np.hstack([bs_all, y.imag * in_service])
elif vector_group == "Yzn":
buses_all = np.hstack([buses_all, lv_buses_ppc])
# y = 1/(z0_mag+z0_k).astype(complex)* int(ppc["baseMVA"])#T model
# y= (za+zb+zc)/((za+zc)*zb).astype(complex)* int(ppc["baseMVA"])#pi model
y = (YAB_AN + YBN).astype(complex) * int(ppc["baseMVA"]) #T model
gs_all = np.hstack([gs_all, (1.1547) * y.real * in_service \
* int(ppc["baseMVA"])])
bs_all = np.hstack([bs_all, (1.1547) * y.imag * in_service \
* int(ppc["baseMVA"])])
elif vector_group[-1].isdigit():
raise ValueError("Unknown transformer vector group %s -\
please specify vector group without \
phase shift number. Phase shift can be \
specified in net.trafo.shift_degree" %
vector_group)
else:
raise ValueError("Transformer vector group %s is unknown\
/ not implemented for three phase load flow" %
vector_group)
buses, gs, bs = aux._sum_by_group(buses_all, gs_all, bs_all)
ppc["bus"][buses, GS] += gs
ppc["bus"][buses, BS] += bs
del net.trafo["_ppc_idx"]
u1 = vn
tap_steps = (trafo_bug["tap_pos"].values -
trafo_bug["tap_neutral"].values
) * trafo_bug["tap_step_percent"].values / 100.
du = u1 * tap_steps
v_modif = np.sqrt((u1 + du * np.cos(tap_angles))**2 +
(du * np.sin(tap_angles))**2)
from pandapower.build_branch import _calc_branch_values_from_trafo_df, get_trafo_values
from pandapower.build_branch import _calc_nominal_ratio_from_dataframe, _calc_r_x_y_from_dataframe
from pandapower.build_branch import _calc_tap_from_dataframe, BASE_KV, _calc_r_x_from_dataframe
ppc = copy.deepcopy(pp_net._ppc)
bus_lookup = pp_net["_pd2ppc_lookups"]["bus"]
trafo_df = pp_net["trafo"]
lv_bus = get_trafo_values(trafo_df, "lv_bus")
vn_lv = ppc["bus"][bus_lookup[lv_bus], BASE_KV]
vn_trafo_hv, vn_trafo_lv, shift_pp = _calc_tap_from_dataframe(
pp_net, trafo_df)
ratio_pp = _calc_nominal_ratio_from_dataframe(
ppc, trafo_df, vn_trafo_hv, vn_trafo_lv, bus_lookup)
r_pp, x_pp, b_pp = _calc_r_x_y_from_dataframe(
pp_net, trafo_df, vn_trafo_lv, vn_lv, pp_net.sn_mva)
y_trafo = 1. / (r_pp[trafo_id] + 1j * x_pp[trafo_id])
ratio_pp[trafo_id]
y_trafo
v_modif / vn
vn / v_modif
# pdb.set_trace()
def _add_trafo3w_sc_impedance_zero(net, ppc):
branch_lookup = net["_pd2ppc_lookups"]["branch"]
if not "trafo3w" in branch_lookup:
return
bus_lookup = net["_pd2ppc_lookups"]["bus"]
branch = ppc["branch"]
f, t = net["_pd2ppc_lookups"]["branch"]["trafo3w"]
trafo_df = _trafo_df_from_trafo3w(net, sequence=0)
hv_bus = get_trafo_values(trafo_df, "hv_bus").astype(int)
lv_bus = get_trafo_values(trafo_df, "lv_bus").astype(int)
in_service = get_trafo_values(trafo_df, "in_service").astype(int)
branch[f:t, F_BUS] = bus_lookup[hv_bus]
branch[f:t, T_BUS] = bus_lookup[lv_bus]
r, x, _, ratio, shift = _calc_branch_values_from_trafo_df(net,
ppc,
trafo_df,
sequence=0)
n_t3 = net.trafo3w.shape[0]
for t3_ix in np.arange(n_t3):
t3 = net.trafo3w.iloc[t3_ix, :]
if t3.vector_group.lower() in set(
map(lambda vg: "".join(vg), product("dy", repeat=3))):
x[[t3_ix, t3_ix + n_t3, t3_ix + n_t3 * 2]] = 1e10
r[[t3_ix, t3_ix + n_t3, t3_ix + n_t3 * 2]] = 1e10
elif t3.vector_group.lower() == "ynyd":
# Correction for YnYD
# z3->y3
ys = 1 / ((x[t3_ix + n_t3 * 2] * 1j + r[t3_ix + n_t3 * 2]) *
ratio[t3_ix + n_t3 * 2]**2)
aux_bus = bus_lookup[lv_bus[t3_ix]]
ppc["bus"][aux_bus, BS] += ys.imag
ppc["bus"][aux_bus, GS] += ys.real
# Set y2/y3 to almost 0 to avoid isolated bus
x[[t3_ix + n_t3, t3_ix + n_t3 * 2]] = 1e10
r[[t3_ix + n_t3, t3_ix + n_t3 * 2]] = 1e10
elif t3.vector_group.lower() == "yynd":
# z3->y3
ys = 1 / ((x[t3_ix + n_t3 * 2] * 1j + r[t3_ix + n_t3 * 2]) *
ratio[t3_ix + n_t3 * 2]**2)
aux_bus = bus_lookup[lv_bus[t3_ix]]
ppc["bus"][aux_bus, BS] += ys.imag
ppc["bus"][aux_bus, GS] += ys.real
# Set y1/y3 to almost 0 to avoid isolated bus
x[[t3_ix, t3_ix + n_t3 * 2]] = 1e10
r[[t3_ix, t3_ix + n_t3 * 2]] = 1e10
elif t3.vector_group.lower() == "ynynd":
# z3->y3
ys = 1 / ((x[t3_ix + n_t3 * 2] * 1j + r[t3_ix + n_t3 * 2]) *
ratio[t3_ix + n_t3 * 2]**2)
aux_bus = bus_lookup[lv_bus[t3_ix]]
ppc["bus"][aux_bus, BS] += ys.imag
ppc["bus"][aux_bus, GS] += ys.real
# Set y3 to almost 0 to avoid isolated bus
x[t3_ix + n_t3 * 2] = 1e10
r[t3_ix + n_t3 * 2] = 1e10
else:
raise UserWarning(
f"{t3.vector_group} not supported yet for trafo3w!")
branch[f:t, BR_R] = r
branch[f:t, BR_X] = x
branch[f:t, BR_B] = 0
branch[f:t, TAP] = ratio
branch[f:t, SHIFT] = shift
branch[f:t, BR_STATUS] = in_service
def _aux_test(self, pn_net):
with tempfile.TemporaryDirectory() as path:
case_name = os.path.join(path, "this_case.json")
pp.to_json(pn_net, case_name)
real_init_file = pp.from_json(case_name)
backend = LightSimBackend()
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
backend.load_grid(case_name)
nb_sub = backend.n_sub
pp_net = backend.init_pp_backend._grid
# first i deactivate all slack bus in pp that are connected but not handled in ls
pp_net.ext_grid["in_service"].loc[:] = False
pp_net.ext_grid["in_service"].iloc[0] = True
conv = backend.runpf()
conv_pp = backend.init_pp_backend.runpf()
assert conv_pp, "Error: pandapower do not converge, impossible to perform the necessary checks"
assert conv, "Error: lightsim do not converge"
por_pp, qor_pp, vor_pp, aor_pp = copy.deepcopy(
backend.init_pp_backend.lines_or_info())
pex_pp, qex_pp, vex_pp, aex_pp = copy.deepcopy(
backend.init_pp_backend.lines_ex_info())
# I- Check for divergence and equality of flows"
por_ls, qor_ls, vor_ls, aor_ls = backend.lines_or_info()
max_mis = np.max(np.abs(por_ls - por_pp))
assert max_mis <= self.tol, f"Error: por do not match, maximum absolute error is {max_mis:.5f} MW"
max_mis = np.max(np.abs(qor_ls - qor_pp))
assert max_mis <= self.tol, f"Error: qor do not match, maximum absolute error is {max_mis:.5f} MVAr"
max_mis = np.max(np.abs(vor_ls - vor_pp))
assert max_mis <= self.tol, f"Error: vor do not match, maximum absolute error is {max_mis:.5f} kV"
max_mis = np.max(np.abs(aor_ls - aor_pp))
assert max_mis <= self.tol, f"Error: aor do not match, maximum absolute error is {max_mis:.5f} A"
# "II - Check for possible solver issues"
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
pp.runpp(backend.init_pp_backend._grid, v_debug=True)
v_tmp = backend.init_pp_backend._grid.res_bus[
"vm_pu"].values[:nb_sub] + 0j
v_tmp *= np.exp(
1j * np.pi / 180. *
backend.init_pp_backend._grid.res_bus["va_degree"].values[:nb_sub])
v_tmp = np.concatenate((v_tmp, v_tmp))
backend._grid.ac_pf(v_tmp, 1000, 1e-5)
Y_pp = backend.init_pp_backend._grid._ppc["internal"]["Ybus"]
Sbus = backend.init_pp_backend._grid._ppc["internal"]["Sbus"]
pv_ = backend.init_pp_backend._grid._ppc["internal"]["pv"]
pq_ = backend.init_pp_backend._grid._ppc["internal"]["pq"]
max_iter = 10
tol_this = 1e-8
All_Vms = backend.init_pp_backend._grid._ppc["internal"]["Vm_it"]
AllVas = backend.init_pp_backend._grid._ppc["internal"]["Va_it"]
for index_V in range(All_Vms.shape[1] - 1, -1, -1):
nb_iter = All_Vms.shape[1] - 1
# i check from easiest to hardest, so from the last iteartion of pandapower to the first iteration of pandapower
# take the same V as pandapower
V_init = All_Vms[:, index_V] * (np.cos(AllVas[:, index_V]) +
1j * np.sin(AllVas[:, index_V]))
# V_init *= np.exp(1j * AllVas[:, 0])
V_init_ref = copy.deepcopy(V_init)
solver = ClassSolver()
solver.solve(scipy.sparse.csc_matrix(Y_pp), V_init, Sbus, pv_, pq_,
max_iter, tol_this)
time_for_nr = solver.get_timers()[3]
if TIMER_INFO:
print(
f"\t Info: Time to perform {nb_iter - index_V} NR iterations for a grid with {nb_sub} "
f"buses: {1000. * time_for_nr:.2f}ms")
error_va = np.abs(
solver.get_Va() -
np.angle(backend.init_pp_backend._grid._ppc["internal"]["V"]))
assert np.max(error_va) <= self.tol, f"Error: VA do not match for iteration {index_V}, maximum absolute " \
f"error is {np.max(error_va):.5f} rad"
error_vm = np.abs(
np.abs(solver.get_Vm() - np.abs(
backend.init_pp_backend._grid._ppc["internal"]["V"])))
assert np.max(error_vm) <= self.tol, f"\t Error: VM do not match for iteration {index_V}, maximum absolute " \
f"error is {np.max(error_vm):.5f} pu"
solver.reset()
if TIMER_INFO:
print("")
# 'III - Check the data conversion'
pp_vect_converter = backend.init_pp_backend._grid._pd2ppc_lookups[
"bus"][:nb_sub]
pp_net = backend.init_pp_backend._grid
# 1) Checking Sbus conversion
Sbus_pp = backend.init_pp_backend._grid._ppc["internal"]["Sbus"]
Sbus_pp_right_order = Sbus_pp[pp_vect_converter]
Sbus_me = backend._grid.get_Sbus()
error_p = np.abs(np.real(Sbus_me) - np.real(Sbus_pp_right_order))
assert np.max(error_p) <= self.tol, f"\t Error: P do not match for Sbus, maximum absolute error is " \
f"{np.max(error_p):.5f} MW, \t Error: significative difference for bus " \
f"index (lightsim): {np.where(error_p > self.tol)[0]}"
error_q = np.abs(np.imag(Sbus_me) - np.imag(Sbus_pp_right_order))
assert np.max(error_q) <= self.tol, f"\t Error: Q do not match for Sbus, maximum absolute error is " \
f"{np.max(error_q):.5f} MVAr, \t Error: significative difference for bus " \
f"index (lightsim): {np.where(error_q > self.tol)[0]}"
# 2) Checking Ybus conversion"
Y_me = backend._grid.get_Ybus()
Y_pp = backend.init_pp_backend._grid._ppc["internal"]["Ybus"]
Y_pp_right_order = Y_pp[pp_vect_converter.reshape(nb_sub, 1),
pp_vect_converter.reshape(1, nb_sub)]
error_p = np.abs(np.real(Y_me) - np.real(Y_pp_right_order))
assert np.max(error_p) <= self.tol, f"Error: P do not match for Ybus, maximum absolute error " \
f"is {np.max(error_p):.5f}"
error_q = np.abs(np.imag(Y_me) - np.imag(Y_pp_right_order))
assert np.max(error_q) <= self.tol, f"\t Error: Q do not match for Ybus, maximum absolute error is " \
f"{np.max(error_q):.5f}"
# "IV - Check for the initialization (dc powerflow)"
# 1) check that the results are same for dc lightsim and dc pandapower
Vinit = np.ones(backend.nb_bus_total,
dtype=np.complex_) * pp_net["_options"]["init_vm_pu"]
backend._grid.deactivate_result_computation()
Vdc = backend._grid.dc_pf(Vinit, max_iter, tol_this)
backend._grid.reactivate_result_computation()
Ydc_me = backend._grid.get_Ybus()
Sdc_me = backend._grid.get_Sbus()
assert np.max(np.abs(V_init_ref[pp_vect_converter] - Vdc[:nb_sub])) <= 100.*self.tol,\
f"\t Error for the DC approximation: resulting voltages are different " \
f"{np.max(np.abs(V_init_ref[pp_vect_converter] - Vdc[:nb_sub])):.5f}pu"
if np.max(np.abs(V_init_ref[pp_vect_converter] -
Vdc[:nb_sub])) >= self.tol:
warnings.warn(
"\t Warning: maximum difference after DC approximation is "
"{np.max(np.abs(V_init_ref[pp_vect_converter] - Vdc[:nb_sub])):.5f} which is higher than "
"the tolerance (this is just a warning because we noticed this could happen even if the "
"results match perfectly. Probably some conversion issue with complex number and "
"radian / degree.")
# "2) check that the Sbus vector is same for PP and lightisim in DC"
from pandapower.pd2ppc import _pd2ppc
from pandapower.pf.run_newton_raphson_pf import _get_pf_variables_from_ppci
from pandapower.pypower.idx_brch import F_BUS, T_BUS, BR_X, TAP, SHIFT, BR_STATUS
from pandapower.pypower.idx_bus import VA, GS
from pandapower.pypower.makeBdc import makeBdc
from pandapower.pypower.makeSbus import makeSbus
pp_net._pd2ppc_lookups = {
"bus": np.array([], dtype=int),
"ext_grid": np.array([], dtype=int),
"gen": np.array([], dtype=int),
"branch": np.array([], dtype=int)
}
# convert pandapower net to ppc
ppc, ppci = _pd2ppc(pp_net)
baseMVA, bus, gen, branch, ref, pv, pq, on, gbus, _, refgen = _get_pf_variables_from_ppci(
ppci)
Va0 = bus[:, VA] * (np.pi / 180.)
B, Bf, Pbusinj, Pfinj = makeBdc(bus, branch)
Pbus = makeSbus(baseMVA, bus, gen) - Pbusinj - bus[:, GS] / baseMVA
Pbus_pp_ro = Pbus[pp_vect_converter]
error_p = np.abs(np.real(Sdc_me) - np.real(Pbus_pp_ro))
test_ok = True
#### pandapower DC algo (yet another one)
Va = copy.deepcopy(Va0)
pvpq = np.r_[pv, pq]
pvpq_matrix = B[pvpq.T, :].tocsc()[:, pvpq]
ref_matrix = np.transpose(Pbus[pvpq] -
B[pvpq.T, :].tocsc()[:, ref] * Va0[ref])
Va[pvpq] = np.real(scipy.sparse.linalg.spsolve(pvpq_matrix,
ref_matrix))
####
assert np.max(error_p) <= self.tol, f"\t Error: P do not match for Sbus (dc), maximum absolute error is " \
f"{np.max(error_p):.5f} MW, \nError: significative difference for bus " \
f"index (lightsim): {np.where(error_p > self.tol)[0]}"
error_q = np.abs(np.imag(Sdc_me) - np.imag(Pbus_pp_ro))
assert np.max(error_q) <= self.tol, f"\t Error: Q do not match for Sbus (dc), maximum absolute error is " \
f"{np.max(error_q):.5f} MVAr, \n\t Error: significative difference for " \
f"bus index (lightsim): {np.where(error_q > self.tol)[0]}"
# "3) check that the Ybus matrix is same for PP and lightisim in DC"
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
pp.rundcpp(pp_net)
Ydc_pp = backend.init_pp_backend._grid._ppc["internal"]["Bbus"]
Ydc_pp_right_order = Ydc_pp[pp_vect_converter.reshape(nb_sub, 1),
pp_vect_converter.reshape(1, nb_sub)]
error_p = np.abs(np.real(Ydc_me) - np.real(Ydc_pp_right_order))
assert np.max(error_p) <= self.tol, f"Error: P do not match for Ybus (dc mode), maximum absolute error " \
f"is {np.max(error_p):.5f}"
error_q = np.abs(np.imag(Ydc_me) - np.imag(Ydc_pp_right_order))
assert np.max(error_q) <= self.tol, f"\t Error: Q do not match for Ybus (dc mdoe), maximum absolute error " \
f"is {np.max(error_q):.5f}"
# "3) check that lightsim ac pf init with pp dc pf give same results (than pp)"
Vinit = np.ones(backend.nb_bus_total,
dtype=np.complex_) * pp_net["_options"]["init_vm_pu"]
Vinit[:nb_sub] = V_init_ref[pp_vect_converter]
conv = backend._grid.ac_pf(Vinit, max_iter, tol_this)
assert conv.shape[
0] > 0, "\t Error: the lightsim diverge when initialized with pandapower Vinit_dc"
lpor, lqor, lvor, laor = backend._grid.get_lineor_res()
tpor, tqor, tvor, taor = backend._grid.get_trafohv_res()
tpex, tqex, tvex, taex = backend._grid.get_trafolv_res()
nb_trafo = tpor.shape[0]
nb_powerline = lpor.shape[0]
p_or_me2 = np.concatenate((lpor, tpor))
q_or_me2 = np.concatenate((lqor, tqor))
v_or_me2 = np.concatenate((lvor, tvor))
a_or_me2 = 1000. * np.concatenate((laor, taor))
test_ok = True
# pdb.set_trace()
max_mis = np.max(np.abs(p_or_me2 - por_pp))
assert np.max(
error_q
) <= self.tol, f"\t Error: por do not match, maximum absolute error is {max_mis:.5f} MW"
max_mis = np.max(np.abs(q_or_me2 - qor_pp))
assert np.max(
error_q
) <= self.tol, f"\t Error: qor do not match, maximum absolute error is {max_mis:.5f} MVAr"
max_mis = np.max(np.abs(v_or_me2 - vor_pp))
assert np.max(
error_q
) <= self.tol, f"\t Error: vor do not match, maximum absolute error is {max_mis:.5f} kV"
max_mis = np.max(np.abs(a_or_me2 - aor_pp))
assert np.max(
error_q
) <= self.tol, f"\t Error: aor do not match, maximum absolute error is {max_mis:.5f} A"
# "V - Check trafo proper conversion to r,x, b"
from lightsim2grid_cpp import GridModel, PandaPowerConverter, SolverType
from pandapower.build_branch import _calc_branch_values_from_trafo_df, get_trafo_values
from pandapower.build_branch import _calc_nominal_ratio_from_dataframe, _calc_r_x_y_from_dataframe
from pandapower.build_branch import _calc_tap_from_dataframe, BASE_KV, _calc_r_x_from_dataframe
# my trafo parameters
converter = PandaPowerConverter()
converter.set_sn_mva(pp_net.sn_mva)
converter.set_f_hz(pp_net.f_hz)
tap_neutral = 1.0 * pp_net.trafo["tap_neutral"].values
tap_neutral[~np.isfinite(tap_neutral)] = 0.
if np.any(tap_neutral != 0.):
raise RuntimeError(
"lightsim converter supposes that tap_neutral is 0 for the transformers"
)
tap_step_pct = 1.0 * pp_net.trafo["tap_step_percent"].values
tap_step_pct[~np.isfinite(tap_step_pct)] = 0.
tap_pos = 1.0 * pp_net.trafo["tap_pos"].values
tap_pos[~np.isfinite(tap_pos)] = 0.
shift_ = 1.0 * pp_net.trafo["shift_degree"].values
shift_[~np.isfinite(shift_)] = 0.
is_tap_hv_side = pp_net.trafo["tap_side"].values == "hv"
is_tap_hv_side[~np.isfinite(is_tap_hv_side)] = True
if np.any(pp_net.trafo["tap_phase_shifter"].values):
raise RuntimeError(
"ideal phase shifter are not modeled. Please remove all trafo with "
"pp_net.trafo[\"tap_phase_shifter\"] set to True.")
tap_angles_ = 1.0 * pp_net.trafo["tap_step_degree"].values
tap_angles_[~np.isfinite(tap_angles_)] = 0.
tap_angles_ = np.deg2rad(tap_angles_)
trafo_r, trafo_x, trafo_b = \
converter.get_trafo_param(tap_step_pct,
tap_pos,
tap_angles_, # in radian !
is_tap_hv_side,
pp_net.bus.loc[pp_net.trafo["hv_bus"]]["vn_kv"],
pp_net.bus.loc[pp_net.trafo["lv_bus"]]["vn_kv"],
pp_net.trafo["vk_percent"].values,
pp_net.trafo["vkr_percent"].values,
pp_net.trafo["sn_mva"].values,
pp_net.trafo["pfe_kw"].values,
pp_net.trafo["i0_percent"].values,
)
# pandapower trafo parameters
ppc = copy.deepcopy(pp_net._ppc)
bus_lookup = pp_net["_pd2ppc_lookups"]["bus"]
trafo_df = pp_net["trafo"]
lv_bus = get_trafo_values(trafo_df, "lv_bus")
vn_lv = ppc["bus"][bus_lookup[lv_bus], BASE_KV]
vn_trafo_hv, vn_trafo_lv, shift_pp = _calc_tap_from_dataframe(
pp_net, trafo_df)
ratio = _calc_nominal_ratio_from_dataframe(ppc, trafo_df, vn_trafo_hv,
vn_trafo_lv, bus_lookup)
r_t, x_t, b_t = _calc_r_x_y_from_dataframe(pp_net, trafo_df,
vn_trafo_lv, vn_lv,
pp_net.sn_mva)
# check where there are mismatch if any
val_r_pp = r_t
val_r_me = trafo_r
all_equals_r = np.abs(val_r_pp - val_r_me) <= self.tol
if not np.all(all_equals_r):
test_ok = False
print(
f"\t Error: some trafo resistance are not equal, max error: {np.max(np.abs(val_r_pp - val_r_me)):.5f}"
)
val_x_pp = x_t
val_x_me = trafo_x
all_equals_x = np.abs(val_x_pp - val_x_me) <= self.tol
assert np.all(all_equals_x), f"\t Error: some trafo x are not equal, max error: " \
f"{np.max(np.abs(val_x_pp - val_x_me)):.5f}"
val_ib_pp = np.imag(b_t)
val_ib_me = np.imag(trafo_b)
all_equals_imag_b = np.abs(val_ib_pp - val_ib_me) <= self.tol
assert np.all(all_equals_imag_b), f"\t Error: some trafo (imag) b are not equal, max error: " \
f"{np.max(np.abs(val_ib_pp - val_ib_me)):.5f}"
val_reb_pp = np.real(b_t)
val_reb_me = np.real(trafo_b)
all_equals_real_b = np.abs(val_reb_pp - val_reb_me) <= self.tol
assert np.all(all_equals_real_b), f"\t Error: some trafo (real) b are not equal, max error: " \
f"{np.max(np.abs(val_reb_pp - val_reb_me)):.5f}"