def _calc_sc(net):
# t0 = time.perf_counter()
_add_auxiliary_elements(net)
ppc, ppci = _pd2ppc(net)
# t1 = time.perf_counter()
_calc_ybus(ppci)
# t2 = time.perf_counter()
_calc_zbus(ppci)
_calc_rx(net, ppci)
# t3 = time.perf_counter()
_add_kappa_to_ppc(net, ppci)
# t4 = time.perf_counter()
_calc_ikss(net, ppci)
if net["_options"]["ip"]:
_calc_ip(net, ppci)
if net["_options"]["ith"]:
_calc_ith(net, ppci)
if net._options["branch_results"]:
_calc_branch_currents(net, ppci)
ppc = _copy_results_ppci_to_ppc(ppci, ppc, "sc")
_extract_results(net, ppc)
_clean_up(net)
# t5 = time.perf_counter()
# net._et = {"sum": t5-t0, "model": t1-t0, "ybus": t2-t1, "zbus": t3-t2, "kappa": t4-t3,
# "currents": t5-t4}
def _calc_sc(net):
_add_auxiliary_elements(net)
ppc, ppci = _pd2ppc(net)
_calc_ybus(ppci)
try:
_calc_zbus(ppci)
except Exception as e:
_clean_up(net, res=False)
raise (e)
_calc_rx(net, ppci)
_add_kappa_to_ppc(net, ppci)
_calc_ikss(net, ppci)
if net["_options"]["ip"]:
_calc_ip(net, ppci)
if net["_options"]["ith"]:
_calc_ith(net, ppci)
if net._options["branch_results"]:
_calc_branch_currents(net, ppci)
ppc = _copy_results_ppci_to_ppc(ppci, ppc, "sc")
if net["_options"]["return_all_currents"]:
_extract_results(net, ppc, ppc_0=None)
else:
_extract_results(net, ppc, ppc_0=None)
_clean_up(net)
def _optimal_powerflow(net, verbose, suppress_warnings, **kwargs):
ac = net["_options"]["ac"]
ppopt = ppoption(VERBOSE=verbose, OPF_FLOW_LIM=2, PF_DC=not ac, **kwargs)
net["OPF_converged"] = False
net["converged"] = False
_add_auxiliary_elements(net)
reset_results(net)
ppc, ppci = _pd2ppc(net)
if not ac:
ppci["bus"][:, VM] = 1.0
net["_ppc_opf"] = ppc
if len(net.dcline) > 0:
ppci = add_userfcn(ppci, 'formulation', _add_dcline_constraints, args=net)
if suppress_warnings:
with warnings.catch_warnings():
warnings.simplefilter("ignore")
result = opf(ppci, ppopt)
else:
result = opf(ppci, ppopt)
net["_ppc_opf"] = result
if not result["success"]:
raise OPFNotConverged("Optimal Power Flow did not converge!")
# ppci doesn't contain out of service elements, but ppc does -> copy results accordingly
mode = net["_options"]["mode"]
result = _copy_results_ppci_to_ppc(result, ppc, mode=mode)
net["_ppc_opf"] = result
net["OPF_converged"] = True
_extract_results_opf(net, result)
_clean_up(net)
def _calc_sc_1ph(net, bus):
"""
calculation method for single phase to ground short-circuit currents
"""
_add_auxiliary_elements(net)
# pos. seq bus impedance
ppc, ppci = _pd2ppc(net)
_calc_ybus(ppci)
# zero seq bus impedance
ppc_0, ppci_0 = _pd2ppc_zero(net)
_calc_ybus(ppci_0)
if net["_options"]["inverse_y"]:
_calc_zbus(net, ppci)
_calc_zbus(net, ppci_0)
else:
# Factorization Ybus once
ppci["internal"]["ybus_fact"] = factorized(ppci["internal"]["Ybus"])
ppci_0["internal"]["ybus_fact"] = factorized(
ppci_0["internal"]["Ybus"])
_calc_rx(net, ppci, bus=bus)
_add_kappa_to_ppc(net, ppci)
_calc_rx(net, ppci_0, bus=bus)
_calc_ikss_1ph(net, ppci, ppci_0, bus=bus)
if net._options["branch_results"]:
_calc_branch_currents(net, ppci, bus=bus)
ppc_0 = _copy_results_ppci_to_ppc(ppci_0, ppc_0, "sc")
ppc = _copy_results_ppci_to_ppc(ppci, ppc, "sc")
_extract_results(net, ppc, ppc_0, bus=bus)
_clean_up(net)
def _calc_sc(net, bus):
_add_auxiliary_elements(net)
ppc, ppci = _pd2ppc(net)
_calc_ybus(ppci)
if net["_options"]["inverse_y"]:
_calc_zbus(net, ppci)
else:
# Factorization Ybus once
ppci["internal"]["ybus_fact"] = factorized(ppci["internal"]["Ybus"])
_calc_rx(net, ppci, bus)
# kappa required inverse of Zbus, which is optimized
if net["_options"]["kappa"]:
_add_kappa_to_ppc(net, ppci)
_calc_ikss(net, ppci, bus)
if net["_options"]["ip"]:
_calc_ip(net, ppci)
if net["_options"]["ith"]:
_calc_ith(net, ppci)
if net._options["branch_results"]:
_calc_branch_currents(net, ppci, bus)
ppc = _copy_results_ppci_to_ppc(ppci, ppc, "sc")
_extract_results(net, ppc, ppc_0=None, bus=bus)
_clean_up(net)
if "ybus_fact" in ppci["internal"]:
# Delete factorization object
ppci["internal"].pop("ybus_fact")
def _calc_sc(net):
# t0 = time.perf_counter()
_add_auxiliary_elements(net)
ppc, ppci = _pd2ppc(net)
# t1 = time.perf_counter()
_calc_ybus(ppci)
# t2 = time.perf_counter()
try:
_calc_zbus(ppci)
except Exception as e:
_clean_up(net, res=False)
raise(e)
_calc_rx(net, ppci)
# t3 = time.perf_counter()
_add_kappa_to_ppc(net, ppci)
# t4 = time.perf_counter()
_calc_ikss(net, ppci)
if net["_options"]["ip"]:
_calc_ip(net, ppci)
if net["_options"]["ith"]:
_calc_ith(net, ppci)
if net._options["branch_results"]:
_calc_branch_currents(net, ppci)
ppc = _copy_results_ppci_to_ppc(ppci, ppc, "sc")
_extract_results(net, ppc, ppc_0=None)
_clean_up(net)
def _powerflow(net, **kwargs):
"""
Gets called by runpp or rundcpp with different arguments.
"""
# get infos from options
init_results = net["_options"]["init_results"]
ac = net["_options"]["ac"]
recycle = net["_options"]["recycle"]
mode = net["_options"]["mode"]
algorithm = net["_options"]["algorithm"]
max_iteration = net["_options"]["max_iteration"]
net["converged"] = False
net["OPF_converged"] = False
_add_auxiliary_elements(net)
if not ac or init_results:
verify_results(net)
else:
reset_results(net)
# TODO remove this when zip loads are integrated for all PF algorithms
if algorithm not in ['nr', 'bfsw']:
net["_options"]["voltage_depend_loads"] = False
if recycle["ppc"] and "_ppc" in net and net[
"_ppc"] is not None and "_pd2ppc_lookups" in net:
# update the ppc from last cycle
ppc, ppci = _update_ppc(net)
else:
# convert pandapower net to ppc
ppc, ppci = _pd2ppc(net)
# store variables
net["_ppc"] = ppc
if not "VERBOSE" in kwargs:
kwargs["VERBOSE"] = 0
# ----- run the powerflow -----
result = _run_pf_algorithm(ppci, net["_options"], **kwargs)
# ppci doesn't contain out of service elements, but ppc does -> copy results accordingly
result = _copy_results_ppci_to_ppc(result, ppc, mode)
# raise if PF was not successful. If DC -> success is always 1
if result["success"] != 1:
_clean_up(net, res=False)
raise LoadflowNotConverged("Power Flow {0} did not converge after "
"{1} iterations!".format(
algorithm, max_iteration))
else:
net["_ppc"] = result
net["converged"] = True
_extract_results(net, result)
_clean_up(net)
def _runpppf_dd(net, init, ac, calculate_voltage_angles, tolerance_kva,
trafo_model, trafo_loading, enforce_q_lims, numba, recycle,
**kwargs):
"""
Gets called by runpp or rundcpp with different arguments.
"""
net["converged"] = False
if (ac and not init == "results") or not ac:
reset_results(net)
# select elements in service (time consuming, so we do it once)
is_elems = _select_is_elements(net, recycle)
if recycle["ppc"] and "_ppc" in net and net[
"_ppc"] is not None and "_bus_lookup" in net:
# update the ppc from last cycle
ppc, ppci, bus_lookup = _update_ppc(net, is_elems, recycle,
calculate_voltage_angles,
enforce_q_lims, trafo_model)
else:
# convert pandapower net to ppc
ppc, ppci, bus_lookup = _pd2ppc(net,
is_elems,
calculate_voltage_angles,
enforce_q_lims,
trafo_model,
init_results=(init == "results"))
# store variables
net["_ppc"] = ppc
net["_bus_lookup"] = bus_lookup
net["_is_elems"] = is_elems
if not "VERBOSE" in kwargs:
kwargs["VERBOSE"] = 0
# run the powerflow
result = _run_fbsw(ppci,
ppopt=ppoption(ENFORCE_Q_LIMS=enforce_q_lims,
PF_TOL=tolerance_kva * 1e-3,
**kwargs))[0]
# ppci doesn't contain out of service elements, but ppc does -> copy results accordingly
result = _copy_results_ppci_to_ppc(result, ppc, bus_lookup)
# raise if PF was not successful. If DC -> success is always 1
if result["success"] != 1:
raise LoadflowNotConverged("Loadflow did not converge!")
else:
net["_ppc"] = result
net["converged"] = True
_extract_results(net, result, is_elems, bus_lookup, trafo_loading, ac)
_clean_up(net)
def _calc_sc(net):
# net["_is_elements"] = _select_is_elements(net)
_add_auxiliary_elements(net)
ppc, ppci = _pd2ppc(net)
_calc_equiv_sc_impedance(net, ppci)
_add_kappa_to_ppc(net, ppci)
_calc_ikss(net, ppci)
_calc_ip(ppci)
_calc_ith(net, ppci)
ppc = _copy_results_ppci_to_ppc(ppci, ppc, "sc")
_extract_results(net, ppc)
_clean_up(net)
def _calc_sc(net, bus):
ppc, ppci = _init_ppc(net)
_calc_current(net, ppci, bus)
ppc = _copy_results_ppci_to_ppc(ppci, ppc, "sc")
_extract_results(net, ppc, ppc_0=None, bus=bus)
_clean_up(net)
if "ybus_fact" in ppci["internal"]:
# Delete factorization object
ppci["internal"].pop("ybus_fact")
def _calc_zbus(net, ppci):
try:
Ybus = ppci["internal"]["Ybus"]
sparsity = Ybus.nnz / Ybus.shape[0]**2
if sparsity < 0.002:
with warnings.catch_warnings():
warnings.simplefilter("ignore")
ppci["internal"]["Zbus"] = inv_sparse(Ybus).toarray()
else:
ppci["internal"]["Zbus"] = inv(Ybus.toarray())
except Exception as e:
_clean_up(net, res=False)
raise (e)
def _calc_sc_single(net, bus):
_add_auxiliary_elements(net)
ppc, ppci = _pd2ppc(net)
_calc_ybus(ppci)
try:
_calc_zbus(ppci)
except Exception as e:
_clean_up(net, res=False)
raise (e)
_calc_rx(net, ppci)
_calc_ikss(net, ppci)
_calc_single_bus_sc(net, ppci, bus)
ppc = _copy_results_ppci_to_ppc(ppci, ppc, "sc")
_extract_single_results(net, ppc)
_clean_up(net)
def read_pm_results_to_net(net, ppc, ppci, result_pm):
"""
reads power models results from result_pm to ppc / ppci and then to pandapower net
"""
# read power models results from result_pm to result (== ppc with results)
result, multinetwork = pm_results_to_ppc_results(net, ppc, ppci, result_pm)
net._pm_result = result_pm
success = ppc["success"]
if success:
if not multinetwork:
# results are extracted from a single time step to pandapower dataframes
_extract_results(net, result)
_clean_up(net)
net["OPF_converged"] = True
else:
_clean_up(net, res=False)
logger.warning("OPF did not converge!")
def _powerflow(net, **kwargs):
"""
Gets called by runpp or rundcpp with different arguments.
"""
# get infos from options
init = net["_options"]["init"]
ac = net["_options"]["ac"]
recycle = net["_options"]["recycle"]
mode = net["_options"]["mode"]
net["converged"] = False
_add_auxiliary_elements(net)
if (ac and not init == "results") or not ac:
reset_results(net)
if recycle["ppc"] and "_ppc" in net and net[
"_ppc"] is not None and "_pd2ppc_lookups" in net:
# update the ppc from last cycle
ppc, ppci = _update_ppc(net)
else:
# convert pandapower net to ppc
ppc, ppci = _pd2ppc(net)
# store variables
net["_ppc"] = ppc
if not "VERBOSE" in kwargs:
kwargs["VERBOSE"] = 0
# ----- run the powerflow -----
result = _run_pf_algorithm(ppci, net["_options"], **kwargs)
# ppci doesn't contain out of service elements, but ppc does -> copy results accordingly
result = _copy_results_ppci_to_ppc(result, ppc, mode)
# raise if PF was not successful. If DC -> success is always 1
if result["success"] != 1:
raise LoadflowNotConverged("Power Flow did not converge!")
else:
net["_ppc"] = result
net["converged"] = True
_extract_results(net, result)
_clean_up(net)
def _ppci_to_net(result, net):
# reads the results from result (== ppci with results) to pandapower net
mode = net["_options"]["mode"]
# ppci doesn't contain out of service elements, but ppc does -> copy results accordingly
ppc = net["_ppc"]
result = _copy_results_ppci_to_ppc(result, ppc, mode)
# raise if PF was not successful. If DC -> success is always 1
if result["success"] != 1:
_clean_up(net, res=False)
algorithm = net["_options"]["algorithm"]
max_iteration = net["_options"]["max_iteration"]
raise LoadflowNotConverged("Power Flow {0} did not converge after "
"{1} iterations!".format(algorithm, max_iteration))
else:
net["_ppc"] = result
net["converged"] = True
_extract_results(net, result)
_clean_up(net)
def read_pm_results_to_net(net, ppc, ppci, result_pm):
"""
reads power models results from result_pm to ppc / ppci and then to pandapower net
"""
# read power models results from result_pm to result (== ppc with results)
net._pm_result_orig = result_pm
result_pm = _deep_copy_pm_results(result_pm)
result_pm = _convert_pm_units_to_pp_units(result_pm, net.sn_mva)
net._pm_result = result_pm
result, multinetwork = pm_results_to_ppc_results(net, ppc, ppci, result_pm)
success = ppc["success"]
if success:
if not multinetwork:
# results are extracted from a single time step to pandapower dataframes
_extract_results(net, result)
_clean_up(net)
net["OPF_converged"] = True
else:
_clean_up(net, res=False)
logger.warning("OPF did not converge!")
raise OPFNotConverged("PowerModels.jl OPF not converged")
def _calc_sc_1ph(net):
"""
calculation method for single phase to ground short-circuit currents
"""
_add_auxiliary_elements(net)
# pos. seq bus impedance
ppc, ppci = _pd2ppc(net)
_calc_ybus(ppci)
try:
_calc_zbus(ppci)
except Exception as e:
_clean_up(net, res=False)
raise (e)
_calc_rx(net, ppci)
_add_kappa_to_ppc(net, ppci)
# zero seq bus impedance
ppc_0, ppci_0 = _pd2ppc_zero(net)
_calc_ybus(ppci_0)
try:
_calc_zbus(ppci_0)
except Exception as e:
_clean_up(net, res=False)
raise (e)
_calc_rx(net, ppci_0)
_calc_ikss_1ph(net, ppci, ppci_0)
if net._options["branch_results"]:
_calc_branch_currents(net, ppci)
ppc_0 = _copy_results_ppci_to_ppc(ppci_0, ppc_0, "sc")
ppc = _copy_results_ppci_to_ppc(ppci, ppc, "sc")
_extract_results(net, ppc, ppc_0)
_clean_up(net)
def _runpm(net, julia_file=None, pp_to_pm_callback=None):
net["OPF_converged"] = False
net["converged"] = False
_add_auxiliary_elements(net)
reset_results(net)
ppc, ppci = _pd2ppc(net)
pm = ppc_to_pm(net, ppci)
net._pm = pm
if pp_to_pm_callback is not None:
pp_to_pm_callback(net, ppci, pm)
result_pm = _call_powermodels(pm, julia_file)
net._result_pm = result_pm
result = pm_results_to_ppc_results(net, ppc, ppci, result_pm)
success = ppc["success"]
net["_ppc_opf"] = ppci
if success:
_extract_results_opf(net, result)
_clean_up(net)
net["OPF_converged"] = True
else:
_clean_up(net)
logger.warning("OPF did not converge!")
def _runpm(net): #pragma: no cover
net["OPF_converged"] = False
net["converged"] = False
_add_auxiliary_elements(net)
reset_results(net)
ppc, ppci = _pd2ppc(net)
net["_ppc_opf"] = ppci
pm = ppc_to_pm(net, ppci)
net._pm = pm
if net._options["pp_to_pm_callback"] is not None:
net._options["pp_to_pm_callback"](net, ppci, pm)
result_pm = _call_powermodels(pm, net._options["julia_file"])
net._pm_res = result_pm
result = pm_results_to_ppc_results(net, ppc, ppci, result_pm)
net._pm_result = result_pm
success = ppc["success"]
if success:
_extract_results(net, result)
_clean_up(net)
net["OPF_converged"] = True
else:
_clean_up(net, res=False)
logger.warning("OPF did not converge!")
def _extract_result_ppci_to_pp(net, ppc, ppci):
# convert to pandapower indices
ppc = _copy_results_ppci_to_ppc(ppci, ppc, mode="se")
# extract results from ppc
try:
_add_pf_options(net,
tolerance_mva=1e-8,
trafo_loading="current",
numba=True,
ac=True,
algorithm='nr',
max_iteration="auto")
except:
pass
# writes res_bus.vm_pu / va_degree and res_line
_extract_results_se(net, ppc)
# restore backup of previous results
_rename_results(net)
# additionally, write bus power demand results (these are not written in _extract_results)
mapping_table = net["_pd2ppc_lookups"]["bus"]
net.res_bus_est.index = net.bus.index
net.res_bus_est.p_mw = get_values(ppc["bus"][:, 2], net.bus.index.values,
mapping_table)
net.res_bus_est.q_mvar = get_values(ppc["bus"][:, 3], net.bus.index.values,
mapping_table)
_clean_up(net)
# delete results which are not correctly calculated
for k in list(net.keys()):
if k.startswith("res_") and k.endswith("_est") and \
k not in ("res_bus_est", "res_line_est", "res_trafo_est", "res_trafo3w_est"):
del net[k]
return net
def _calc_sc_single(net, bus):
_add_auxiliary_elements(net)
ppc, ppci = _pd2ppc(net)
_calc_ybus(ppci)
if net["_options"]["inverse_y"]:
_calc_zbus(net, ppci)
_calc_rx(net, ppci, bus=None)
_calc_ikss(net, ppci, bus=None)
_calc_single_bus_sc(net, ppci, bus)
else:
# Factorization Ybus once
ppci["internal"]["ybus_fact"] = factorized(ppci["internal"]["Ybus"])
_calc_rx(net, ppci, bus)
_calc_ikss(net, ppci, bus)
_calc_single_bus_sc_no_y_inv(net, ppci, bus)
# Delete factorization object
ppci["internal"].pop("ybus_fact")
ppc = _copy_results_ppci_to_ppc(ppci, ppc, "sc")
_extract_single_results(net, ppc)
_clean_up(net)
def ts_newtonpf(self, net):
options = net["_options"]
bus = self.ppci["bus"]
branch = self.ppci["branch"]
gen = self.ppci["gen"]
# compute complex bus power injections [generation - load]
# self.Cg = _get_Cg(gen_on, bus)
# Sbus = _get_Sbus(self.baseMVA, bus, gen, self.Cg)
Sbus = makeSbus(self.baseMVA, bus, gen)
# run the newton power flow
V, success, _, _, _, _ = nr_pf.newtonpf(self.Ybus, Sbus, self.V,
self.pv, self.pq, self.ppci,
options)
if not success:
logger.warning("Loadflow not converged")
logger.info("Lines of of service:")
logger.info(net.line[~net.line.in_service])
raise LoadflowNotConverged("Power Flow did not converge after")
if self.ppci["gen"].shape[
0] == 1 and not options["voltage_depend_loads"]:
pfsoln = pf_solution_single_slack
else:
pfsoln = pfsoln_full
bus, gen, branch = pfsoln(self.baseMVA,
bus,
gen,
branch,
self.Ybus,
self.Yf,
self.Yt,
V,
self.ref,
self.ref_gens,
Ibus=self.Ibus)
self.ppci["bus"] = bus
self.ppci["branch"] = branch
self.ppci["gen"] = gen
self.ppci["success"] = success
self.ppci["et"] = None
# ppci doesn't contain out of service elements, but ppc does -> copy results accordingly
self.ppc = _copy_results_ppci_to_ppc(self.ppci, self.ppc,
options["mode"])
# raise if PF was not successful. If DC -> success is always 1
if self.ppc["success"] != 1:
_clean_up(net, res=False)
else:
net["_ppc"] = self.ppc
net["converged"] = True
self.V = V
_extract_results(net, self.ppc)
return net
def _runpppf(net, **kwargs):
"""
Gets called by runpp or rundcpp with different arguments.
"""
# get infos from options
init = net["_options"]["init"]
ac = net["_options"]["ac"]
recycle = net["_options"]["recycle"]
numba = net["_options"]["numba"]
enforce_q_lims = net["_options"]["enforce_q_lims"]
tolerance_kva = net["_options"]["tolerance_kva"]
mode = net["_options"]["mode"]
algorithm = net["_options"]["algorithm"]
max_iteration = net["_options"]["max_iteration"]
net["converged"] = False
_add_auxiliary_elements(net)
if (ac and not init == "results") or not ac:
reset_results(net)
# select elements in service (time consuming, so we do it once)
net["_is_elems"] = _select_is_elements(net, recycle)
if recycle["ppc"] and "_ppc" in net and net[
"_ppc"] is not None and "_pd2ppc_lookups" in net:
# update the ppc from last cycle
ppc, ppci = _update_ppc(net, recycle)
else:
# convert pandapower net to ppc
ppc, ppci = _pd2ppc(net)
# store variables
net["_ppc"] = ppc
if not "VERBOSE" in kwargs:
kwargs["VERBOSE"] = 0
# run the powerflow
# algorithms implemented within pypower
algorithm_pypower_dict = {'nr': 1, 'fdBX': 2, 'fdXB': 3, 'gs': 4}
if algorithm == 'fbsw': # foreward/backward sweep power flow algorithm
result = _run_fbsw_ppc(ppci,
ppopt=ppoption(ENFORCE_Q_LIMS=enforce_q_lims,
PF_TOL=tolerance_kva * 1e-3,
PF_MAX_IT_GS=max_iteration,
**kwargs))[0]
elif algorithm in algorithm_pypower_dict:
ppopt = ppoption(**kwargs)
ppopt['PF_ALG'] = algorithm_pypower_dict[algorithm]
ppopt['ENFORCE_Q_LIMS'] = enforce_q_lims
ppopt['PF_TOL'] = tolerance_kva
if max_iteration is not None:
if algorithm == 'nr':
ppopt['PF_MAX_IT'] = max_iteration
elif algorithm == 'gs':
ppopt['PF_MAX_IT_GS'] = max_iteration
else:
ppopt['PF_MAX_IT_FD'] = max_iteration
result = _runpf(ppci,
init,
ac,
numba,
recycle,
ppopt=ppoption(ENFORCE_Q_LIMS=enforce_q_lims,
PF_TOL=tolerance_kva * 1e-3,
**kwargs))[0]
else:
AlgorithmUnknown("Algorithm {0} is unknown!".format(algorithm))
# ppci doesn't contain out of service elements, but ppc does -> copy results accordingly
result = _copy_results_ppci_to_ppc(result, ppc, mode)
# raise if PF was not successful. If DC -> success is always 1
if result["success"] != 1:
raise LoadflowNotConverged("Loadflow did not converge!")
else:
net["_ppc"] = result
net["converged"] = True
_extract_results(net, result)
_clean_up(net)
def _optimal_powerflow(net, verbose, suppress_warnings, **kwargs):
ac = net["_options"]["ac"]
init = net["_options"]["init"]
ppopt = ppoption(VERBOSE=verbose,
OPF_FLOW_LIM=2,
PF_DC=not ac,
INIT=init,
**kwargs)
net["OPF_converged"] = False
net["converged"] = False
_add_auxiliary_elements(net)
reset_results(net, all_empty=False)
ppc, ppci = _pd2ppc(net)
if not ac:
ppci["bus"][:, VM] = 1.0
net["_ppc_opf"] = ppci
if len(net.dcline) > 0:
ppci = add_userfcn(ppci,
'formulation',
_add_dcline_constraints,
args=net)
if init == "pf":
ppci = _run_pf_before_opf(net, ppci)
if suppress_warnings:
with warnings.catch_warnings():
warnings.simplefilter("ignore")
result = opf(ppci, ppopt)
else:
result = opf(ppci, ppopt)
# net["_ppc_opf"] = result
if verbose:
ppopt['OUT_ALL'] = 1
printpf(baseMVA=result["baseMVA"],
bus=result["bus"],
gen=result["gen"],
fd=stdout,
branch=result["branch"],
success=result["success"],
et=result["et"],
ppopt=ppopt)
if verbose:
ppopt['OUT_ALL'] = 1
printpf(baseMVA=result["baseMVA"],
bus=result["bus"],
gen=result["gen"],
fd=stdout,
branch=result["branch"],
success=result["success"],
et=result["et"],
ppopt=ppopt)
if not result["success"]:
raise OPFNotConverged("Optimal Power Flow did not converge!")
# ppci doesn't contain out of service elements, but ppc does -> copy results accordingly
mode = net["_options"]["mode"]
result = _copy_results_ppci_to_ppc(result, ppc, mode=mode)
# net["_ppc_opf"] = result
net["OPF_converged"] = True
_extract_results(net, result)
_clean_up(net)
def runpp_3ph(net,
calculate_voltage_angles=True,
init="auto",
max_iteration="auto",
tolerance_mva=1e-8,
trafo_model='t',
trafo_loading="current",
enforce_q_lims=False,
numba=True,
recycle=None,
check_connectivity=True,
switch_rx_ratio=2.0,
delta_q=0,
v_debug=False,
**kwargs):
"""
runpp_3ph: Performs Unbalanced/Asymmetric/Three Phase Load flow
INPUT:
**net** - The pandapower format network
OPTIONAL:
**algorithm** (str, "nr") - algorithm that is used to solve the power
flow problem.
The following algorithms are available:
- "nr" Newton-Raphson (pypower implementation with numba accelerations)
Used only for positive sequence network
Zero and Negative sequence networks use Current Injection method
Vnew = Y.inv * Ispecified ( from s_abc/v_abc old)
Icalculated = Y * Vnew
**calculate_voltage_angles** (bool, "auto") - consider voltage angles
in loadflow calculation
If True, voltage angles of ext_grids and transformer shifts are
considered in the loadflow calculation. Considering the voltage
angles is only necessary in meshed networks that are usually
found in higher voltage levels. calculate_voltage_angles
in "auto" mode defaults to:
- True, if the network voltage level is above 70 kV
- False otherwise
The network voltage level is defined as the maximum rated voltage
of any bus in the network that is connected to a line.
**max_iteration** (int, "auto") - maximum number of iterations carried
out in the power flow algorithm.
In "auto" mode, the default value depends on the power flow solver:
- 10 for "nr"
For three phase calculations, its extended to 3 * max_iteration
**tolerance_mva** (float, 1e-8) - loadflow termination condition
referring to P / Q mismatch of node power in MVA
**trafo_model**
- transformer equivalent models
- "t" - transformer is modeled as equivalent with the T-model.
- "pi" - This is not recommended, since it is less exact than the T-model. So, for three phase load flow, its not implemented
**trafo_loading** (str, "current") - mode of calculation for
transformer loading
Transformer loading can be calculated relative to the rated
current or the rated power. In both cases the overall transformer
loading is defined as the maximum loading on the two sides of
the transformer.
- "current"- transformer loading is given as ratio of current
flow and rated current of the transformer. This is the recommended
setting, since thermal as well as magnetic effects in the
transformer depend on the current.
- "power" - transformer loading is given as ratio of apparent
power flow to the rated apparent power of the transformer.
**enforce_q_lims** (bool, False) (Not tested with 3 Phase load flow)
- respect generator reactive power limits
If True, the reactive power limits in net.gen.max_q_mvar/min_q_mvar
are respected in the loadflow. This is done by running a second
loadflow if reactive power limits are violated at any generator,
so that the runtime for the loadflow will increase if reactive
power has to be curtailed.
Note: enforce_q_lims only works if algorithm="nr"!
**check_connectivity** (bool, True) - Perform an extra connectivity
test after the conversion from pandapower to PYPOWER.
If True, an extra connectivity test based on SciPy Compressed
Sparse Graph Routines is perfomed. If check finds unsupplied buses,
they are set out of service in the ppc
**voltage_depend_loads** (bool, True)
(Not tested with 3 Phase load flow) - consideration of voltage-dependent loads.
If False, ``net.load.const_z_percent`` and ``net.load.const_i_percent``
are not considered, i.e. ``net.load.p_mw`` and ``net.load.q_mvar``
are considered as constant-power loads.
**consider_line_temperature** (bool, False) (Not tested with 3 Phase
load flow) - adjustment of line impedance based on provided line temperature.
If True, ``net.line`` must contain a column ``temperature_degree_celsius``.
The temperature dependency coefficient alpha must be provided in
the ``net.line.alpha`` column, otherwise the default value of 0.004 is used.
**KWARGS**:
**numba** (bool, True) - Activation of numba JIT compiler in the
newton solver
If set to True, the numba JIT compiler is used to generate
matrices for the powerflow, which leads to significant speed
improvements.
**switch_rx_ratio** (float, 2)
(Not tested with 3 Phase load flow) - rx_ratio of bus-bus-switches.
If impedance is zero, buses connected by a closed bus-bus switch
are fused to model an ideal bus. Otherwise, they are modelled
as branches with resistance defined as z_ohm column in switch
table and this parameter
**delta_q**
(Not tested with 3 Phase load flow) - Reactive power tolerance for option "enforce_q_lims"
in kvar - helps convergence in some cases.
**trafo3w_losses**
(Not tested with 3 Phase load flow) - defines where open loop losses of three-winding
transformers are considered. Valid options are "hv", "mv", "lv"
for HV/MV/LV side or "star" for the star point.
**v_debug** (bool, False) (Not tested with 3 Phase load flow) - if True,
voltage values in each newton-raphson iteration are logged in the ppc.
**init_vm_pu** (string/float/array/Series, None) (Not tested with 3
Phase load flow) - Allows to define initialization specifically for
voltage magnitudes. Only works with ``init == "auto"``!
- "auto": all buses are initialized with the mean value of all
voltage controlled elements in the grid
- "flat" for flat start from 1.0
- "results": voltage magnitude vector is taken from result table
- a float with which all voltage magnitudes are initialized
- an iterable with a voltage magnitude value for each bus
(length and order has to match with the buses in net.bus)
- a pandas Series with a voltage magnitude value for each bus
(indexes have to match the indexes in net.bus)
**init_va_degree** (string/float/array/Series, None) (Not tested with
3 Phase load flow) - Allows to define initialization specifically for voltage angles.
Only works with ``init == "auto"``!
- "auto": voltage angles are initialized from DC power flow
if angles are calculated or as 0 otherwise
- "dc": voltage angles are initialized from DC power flow
- "flat" for flat start from 0
- "results": voltage angle vector is taken from result table
- a float with which all voltage angles are initialized
- an iterable with a voltage angle value for each bus (length
and order has to match with the buses in net.bus)
- a pandas Series with a voltage angle value for each bus (indexes
have to match the indexes in net.bus)
**recycle** (dict, none) - Reuse of internal powerflow variables for
time series calculation.
Contains a dict with the following parameters:
bus_pq: If True PQ values of buses are updated
gen: If True Sbus and the gen table in the ppc are recalculated
Ybus: If True the admittance matrix (Ybus, Yf, Yt) is taken from
ppc["internal"] and not reconstructed
**neglect_open_switch_branches** (bool, False)
(Not tested with 3 Phase load flow) - If True no auxiliary
buses are created for branches when switches are opened at the branch.
Instead branches are set out of service
SEE ALSO:
pp.add_zero_impedance_parameters(net):
To add zero sequence parameters into network from the standard type
EXAMPLES:
Use this module like this:
.. code-block:: python
from pandapower.pf.runpp_3ph import runpp_3ph
runpp_3ph(net)
NOTES:
- Three phase load flow uses Sequence Frame for power flow solution.
- Three phase system is modelled with earth return.
- PH-E load type is called as wye since Neutral and Earth are considered same
- This solver has proved successful only for Earthed transformers (i.e Dyn,Yyn,YNyn & Yzn vector groups)
"""
# =============================================================================
# pandapower settings
# =============================================================================
overrule_options = {}
if "user_pf_options" in net.keys() and len(net.user_pf_options) > 0:
passed_parameters = _passed_runpp_parameters(locals())
overrule_options = {
key: val
for key, val in net.user_pf_options.items()
if key not in passed_parameters.keys()
}
if numba:
numba = _check_if_numba_is_installed(numba)
ac = True
mode = "pf_3ph" # TODO: Make valid modes (pf, pf_3ph, se, etc.) available in seperate file (similar to idx_bus.py)
# v_debug = kwargs.get("v_debug", False)
copy_constraints_to_ppc = False
if trafo_model == 'pi':
raise Not_implemented("Three phase Power Flow doesnot support pi model\
because of lack of accuracy")
# if calculate_voltage_angles == "auto":
# calculate_voltage_angles = False
# hv_buses = np.where(net.bus.vn_kv.values > 70)[0] # Todo: Where does that number come from?
# if len(hv_buses) > 0:
# line_buses = net.line[["from_bus", "to_bus"]].values.flatten()
# if len(set(net.bus.index[hv_buses]) & set(line_buses)) > 0:
# scipy spsolve options in NR power flow
use_umfpack = kwargs.get("use_umfpack", True)
permc_spec = kwargs.get("permc_spec", None)
calculate_voltage_angles = True
if init == "results" and net.res_bus_3ph.empty:
init = "auto"
if init == "auto":
init = "dc" if calculate_voltage_angles else "flat"
default_max_iteration = {
"nr": 10,
"bfsw": 10,
"gs": 10000,
"fdxb": 30,
"fdbx": 30
}
if max_iteration == "auto":
max_iteration = default_max_iteration["nr"]
neglect_open_switch_branches = kwargs.get("neglect_open_switch_branches",
False)
only_v_results = kwargs.get("only_v_results", False)
net._options = {}
_add_ppc_options(net, calculate_voltage_angles=calculate_voltage_angles,
trafo_model=trafo_model, check_connectivity=check_connectivity,
mode=mode, switch_rx_ratio=switch_rx_ratio,
init_vm_pu=init, init_va_degree=init,
enforce_q_lims=enforce_q_lims, recycle=None,
voltage_depend_loads=False, delta=delta_q,\
neglect_open_switch_branches=neglect_open_switch_branches
)
_add_pf_options(net, tolerance_mva=tolerance_mva, trafo_loading=trafo_loading,
numba=numba, ac=ac, algorithm="nr", max_iteration=max_iteration,\
only_v_results=only_v_results,v_debug=v_debug, use_umfpack=use_umfpack,
permc_spec=permc_spec)
net._options.update(overrule_options)
_check_bus_index_and_print_warning_if_high(net)
_check_gen_index_and_print_warning_if_high(net)
# =========================================================================
# pd2ppc conversion
# =========================================================================
_, ppci1 = _pd2ppc_recycle(net, 1, recycle=recycle)
_, ppci2 = _pd2ppc_recycle(net, 2, recycle=recycle)
gs_eg, bs_eg = _add_ext_grid_sc_impedance(net, ppci2)
_, ppci0 = _pd2ppc_recycle(net, 0, recycle=recycle)
_, bus0, gen0, branch0, _, _, _ = _get_pf_variables_from_ppci(ppci0)
base_mva, bus1, gen1, branch1, sl_bus, _, pq_bus = _get_pf_variables_from_ppci(
ppci1)
_, bus2, gen2, branch2, _, _, _ = _get_pf_variables_from_ppci(ppci2)
# initialize the results after the conversion to ppc is done, otherwise init=results does not work
init_results(net, "pf_3ph")
# =============================================================================
# P Q values aggragated and summed up for each bus to make s_abc matrix
# s_abc for wye connections ; s_abc_delta for delta connection
# =============================================================================
s_abc_delta, s_abc = _load_mapping(net, ppci1)
# =========================================================================
# Construct Sequence Frame Bus admittance matrices Ybus
# =========================================================================
ppci0, ppci1, ppci2, y_0_pu, y_1_pu, y_2_pu, y_0_f, y_1_f, _,\
y_0_t, y_1_t, _ = _get_y_bus(ppci0, ppci1, ppci2, recycle)
# =========================================================================
# Initial voltage values
# =========================================================================
nb = ppci1["bus"].shape[0]
# make sure flat start is always respected, even with other voltage data in recycled ppc
if init == "flat":
v_012_it = np.zeros((3, nb), dtype=np.complex128)
v_012_it[1, :] = 1.0
else:
v_012_it = np.concatenate([
np.array(ppc["bus"][:, VM] *
np.exp(1j * np.deg2rad(ppc["bus"][:, VA]))).reshape(
(1, nb)) for ppc in (ppci0, ppci1, ppci2)
],
axis=0).astype(np.complex128)
# For Delta transformation:
# Voltage changed from line-earth to line-line using V_T
# s_abc/v_abc will now give line-line currents. This is converted to line-earth
# current using I-T
v_del_xfmn = np.array([[1, -1, 0], [0, 1, -1], [-1, 0, 1]])
i_del_xfmn = np.array([[1, 0, -1], [-1, 1, 0], [0, -1, 1]])
v_abc_it = sequence_to_phase(v_012_it)
# =========================================================================
# Iteration using Power mismatch criterion
# =========================================================================
outer_tolerance_mva = 3e-8
count = 0
s_mismatch = np.array([[True], [True]], dtype=bool)
t0 = perf_counter()
while (s_mismatch >
outer_tolerance_mva).any() and count < 30 * max_iteration:
# =====================================================================
# Voltages and Current transformation for PQ and Slack bus
# =====================================================================
s_abc_pu = -np.divide(s_abc, ppci1["baseMVA"])
s_abc_delta_pu = -np.divide(s_abc_delta, ppci1["baseMVA"])
i_abc_it_wye = (np.divide(s_abc_pu, v_abc_it)).conjugate()
i_abc_it_delta = np.matmul(i_del_xfmn, (np.divide(
s_abc_delta_pu, np.matmul(v_del_xfmn, v_abc_it))).conjugate())
# For buses with both delta and wye loads we need to sum of their currents
# to sum up the currents
i_abc_it = i_abc_it_wye + i_abc_it_delta
i012_it = phase_to_sequence(i_abc_it)
v1_for_s1 = v_012_it[1, :]
i1_for_s1 = -i012_it[1, :]
v0_pu_it = X012_to_X0(v_012_it)
v2_pu_it = X012_to_X2(v_012_it)
i0_pu_it = X012_to_X0(i012_it)
i2_pu_it = X012_to_X2(i012_it)
s1 = np.multiply(v1_for_s1, i1_for_s1.conjugate())
# =============================================================================
# Current used to find S1 Positive sequence power
# =============================================================================
ppci1["bus"][pq_bus, PD] = np.real(s1[pq_bus]) * ppci1["baseMVA"]
ppci1["bus"][pq_bus, QD] = np.imag(s1[pq_bus]) * ppci1["baseMVA"]
# =============================================================================
# Conduct Positive sequence power flow
# =============================================================================
_run_newton_raphson_pf(ppci1, net._options)
# =============================================================================
# Conduct Negative and Zero sequence power flow
# =============================================================================
v0_pu_it = V_from_I(y_0_pu, i0_pu_it)
v2_pu_it = V_from_I(y_2_pu, i2_pu_it)
# =============================================================================
# Evaluate Positive Sequence Power Mismatch
# =============================================================================
i1_from_v_it = I1_from_V012(v_012_it, y_1_pu).flatten()
s_from_voltage = S_from_VI_elementwise(v1_for_s1, i1_from_v_it)
v1_pu_it = V1_from_ppc(ppci1)
v_012_new = combine_X012(v0_pu_it, v1_pu_it, v2_pu_it)
s_mismatch = np.abs(
np.abs(s1[pq_bus]) - np.abs(s_from_voltage[pq_bus]))
v_012_it = v_012_new
v_abc_it = sequence_to_phase(v_012_it)
count += 1
et = perf_counter() - t0
success = (count < 30 * max_iteration)
for ppc in [ppci0, ppci1, ppci2]:
ppc["et"] = et
ppc["success"] = success
# TODO: Add reference to paper to explain the following steps
# This is required since the ext_grid power results are not correct if its
# not done
ref, pv, pq = bustypes(ppci0["bus"], ppci0["gen"])
ref_gens = ppci0["internal"]["ref_gens"]
ppci0["bus"][ref, GS] -= gs_eg
ppci0["bus"][ref, BS] -= bs_eg
y_0_pu, y_0_f, y_0_t = makeYbus(ppci0["baseMVA"], ppci0["bus"],
ppci0["branch"])
# revert the change, otherwise repeated calculation with recycled elements will fail
ppci0["bus"][ref, GS] += gs_eg
ppci0["bus"][ref, BS] += bs_eg
# Bus, Branch, and Gen power values
bus0, gen0, branch0 = pfsoln(base_mva, bus0, gen0, branch0, y_0_pu, y_0_f,
y_0_t, v_012_it[0, :].flatten(), sl_bus,
ref_gens)
bus1, gen1, branch1 = pfsoln(base_mva, bus1, gen1, branch1, y_1_pu, y_1_f,
y_1_t, v_012_it[1, :].flatten(), sl_bus,
ref_gens)
bus2, gen2, branch2 = pfsoln(base_mva, bus2, gen2, branch2, y_1_pu, y_1_f,
y_1_t, v_012_it[2, :].flatten(), sl_bus,
ref_gens)
ppci0 = _store_results_from_pf_in_ppci(ppci0, bus0, gen0, branch0)
ppci1 = _store_results_from_pf_in_ppci(ppci1, bus1, gen1, branch1)
ppci2 = _store_results_from_pf_in_ppci(ppci2, bus2, gen2, branch2)
i_012_res = _current_from_voltage_results(y_0_pu, y_1_pu, v_012_it)
s_012_res = S_from_VI_elementwise(v_012_it, i_012_res) * ppci1["baseMVA"]
eg_is_mask = net["_is_elements"]['ext_grid']
ext_grid_lookup = net["_pd2ppc_lookups"]["ext_grid"]
eg_is_idx = net["ext_grid"].index.values[eg_is_mask]
eg_idx_ppc = ext_grid_lookup[eg_is_idx]
""" # 2 ext_grids Fix: Instead of the generator index, bus indices of the generators are used"""
eg_bus_idx_ppc = np.real(ppci1["gen"][eg_idx_ppc, GEN_BUS]).astype(int)
ppci0["gen"][eg_idx_ppc, PG] = s_012_res[0, eg_bus_idx_ppc].real
ppci1["gen"][eg_idx_ppc, PG] = s_012_res[1, eg_bus_idx_ppc].real
ppci2["gen"][eg_idx_ppc, PG] = s_012_res[2, eg_bus_idx_ppc].real
ppci0["gen"][eg_idx_ppc, QG] = s_012_res[0, eg_bus_idx_ppc].imag
ppci1["gen"][eg_idx_ppc, QG] = s_012_res[1, eg_bus_idx_ppc].imag
ppci2["gen"][eg_idx_ppc, QG] = s_012_res[2, eg_bus_idx_ppc].imag
ppc0 = net["_ppc0"]
ppc1 = net["_ppc1"]
ppc2 = net["_ppc2"]
# ppci doesn't contain out of service elements, but ppc does -> copy results accordingly
ppc0 = _copy_results_ppci_to_ppc(ppci0, ppc0, mode=mode)
ppc1 = _copy_results_ppci_to_ppc(ppci1, ppc1, mode=mode)
ppc2 = _copy_results_ppci_to_ppc(ppci2, ppc2, mode=mode)
_extract_results_3ph(net, ppc0, ppc1, ppc2)
# Raise error if PF was not successful. If DC -> success is always 1
if not ppci0["success"]:
net["converged"] = False
_clean_up(net, res=False)
raise LoadflowNotConverged("Power Flow {0} did not converge after\
{1} iterations!".format("nr", count))
else:
net["converged"] = True
_clean_up(net)
def estimate(self,
v_start='flat',
delta_start='flat',
calculate_voltage_angles=True,
zero_injection=None,
fuse_buses_with_bb_switch='all'):
"""
The function estimate is the main function of the module. It takes up to three input
arguments: v_start, delta_start and calculate_voltage_angles. The first two are the initial
state variables for the estimation process. Usually they can be initialized in a
"flat-start" condition: All voltages being 1.0 pu and all voltage angles being 0 degrees.
In this case, the parameters can be left at their default values (None). If the estimation
is applied continuously, using the results from the last estimation as the starting
condition for the current estimation can decrease the amount of iterations needed to
estimate the current state. The third parameter defines whether all voltage angles are
calculated absolutely, including phase shifts from transformers. If only the relative
differences between buses are required, this parameter can be set to False. Returned is a
boolean value, which is true after a successful estimation and false otherwise.
The resulting complex voltage will be written into the pandapower network. The result
fields are found res_bus_est of the pandapower network.
INPUT:
**net** - The net within this line should be created
**v_start** (np.array, shape=(1,), optional) - Vector with initial values for all
voltage magnitudes in p.u. (sorted by bus index)
**delta_start** (np.array, shape=(1,), optional) - Vector with initial values for all
voltage angles in degrees (sorted by bus index)
OPTIONAL:
**calculate_voltage_angles** - (bool) - Take into account absolute voltage angles and
phase shifts in transformers Default is True
**zero_injection** - (str, iterable, None) - Defines which buses are zero injection bus or the method
to identify zero injection bus, with 'wls_estimator' virtual measurements will be added, with
'wls_estimator with zero constraints' the buses will be handled as constraints
"auto": all bus without p,q measurement, without p, q value (load, sgen...) and aux buses will be
identified as zero injection bus
"aux_bus": only aux bus will be identified as zero injection bus
None: no bus will be identified as zero injection bus
iterable: the iterable should contain index of the zero injection bus and also aux bus will be identified
as zero-injection bus
**fuse_buses_with_bb_switch** - (str, iterable, None) - Defines how buses with closed bb switches should
be handled, if fuse buses will only fused to one for calculation, if not fuse, an auxiliary bus and
auxiliary line will be automatically added to the network to make the buses with different p,q injection
measurements identifieble
"all": all buses with bb-switches will be fused, the same as the default behaviour in load flow
None: buses with bb-switches and individual p,q measurements will be reconfigurated
by auxiliary elements
iterable: the iterable should contain the index of buses to be fused, the behaviour is contigous e.g.
if one of the bus among the buses connected through bb switch is given, then all of them will still
be fused
OUTPUT:
**successful** (boolean) - True if the estimation process was successful
Optional estimation variables:
The bus power injections can be accessed with *se.s_node_powers* and the estimated
values corresponding to the (noisy) measurement values with *se.hx*. (*hx* denotes h(x))
EXAMPLE:
success = estimate(np.array([1.0, 1.0, 1.0]), np.array([0.0, 0.0, 0.0]))
"""
if self.net is None:
raise UserWarning("Component was not initialized with a network.")
t0 = time()
# change the configuration of the pp net to avoid auto fusing of buses connected
# through bb switch with elements on each bus if this feature enabled
bus_to_be_fused = None
if fuse_buses_with_bb_switch != 'all' and not self.net.switch.empty:
if isinstance(fuse_buses_with_bb_switch, str):
raise UserWarning(
"fuse_buses_with_bb_switch parameter is not correctly initialized"
)
elif hasattr(fuse_buses_with_bb_switch, '__iter__'):
bus_to_be_fused = fuse_buses_with_bb_switch
_add_aux_elements_for_bb_switch(self.net, bus_to_be_fused)
# add initial values for V and delta
# node voltages
# V<delta
if v_start is None:
v_start = "flat"
if delta_start is None:
delta_start = "flat"
# initialize result tables if not existent
_copy_power_flow_results(self.net)
# initialize ppc
ppc, ppci = _init_ppc(self.net, v_start, delta_start,
calculate_voltage_angles)
# add measurements to ppci structure
ppci = _add_measurements_to_ppc(self.net, ppci, zero_injection)
# Finished converting pandapower network to ppci
# Estimate voltage magnitude and angle with the given estimator
delta, v_m = self.estimator.estimate(ppci)
# store results for all elements
# calculate bus power injections
v_cpx = v_m * np.exp(1j * delta)
bus_powers_conj = np.zeros(len(v_cpx), dtype=np.complex128)
for i in range(len(v_cpx)):
bus_powers_conj[i] = np.dot(ppci['internal']['Y_bus'][i, :],
v_cpx) * np.conjugate(v_cpx[i])
ppci["bus"][:, 2] = bus_powers_conj.real # saved in per unit
ppci["bus"][:, 3] = -bus_powers_conj.imag # saved in per unit
ppci["bus"][:, 7] = v_m
ppci["bus"][:, 8] = delta * 180 / np.pi # convert to degree
# calculate line results (in ppc_i)
s_ref, bus, gen, branch = _get_pf_variables_from_ppci(ppci)[0:4]
out = np.flatnonzero(branch[:,
BR_STATUS] == 0) # out-of-service branches
br = np.flatnonzero(branch[:, BR_STATUS]).astype(
int) # in-service branches
# complex power at "from" bus
Sf = v_cpx[np.real(branch[br, F_BUS]).astype(int)] * np.conj(
ppci['internal']['Yf'][br, :] * v_cpx) * s_ref
# complex power injected at "to" bus
St = v_cpx[np.real(branch[br, T_BUS]).astype(int)] * np.conj(
ppci['internal']['Yt'][br, :] * v_cpx) * s_ref
branch[np.ix_(br, [PF, QF, PT, QT])] = np.c_[Sf.real, Sf.imag, St.real,
St.imag]
branch[np.ix_(out, [PF, QF, PT, QT])] = np.zeros((len(out), 4))
et = time() - t0
ppci = _store_results_from_pf_in_ppci(ppci, bus, gen, branch,
self.estimator.successful,
self.estimator.iterations, et)
# convert to pandapower indices
ppc = _copy_results_ppci_to_ppc(ppci, ppc, mode="se")
# extract results from ppc
_add_pf_options(self.net,
tolerance_mva=1e-8,
trafo_loading="current",
numba=True,
ac=True,
algorithm='nr',
max_iteration="auto")
# writes res_bus.vm_pu / va_degree and res_line
_extract_results_se(self.net, ppc)
# restore backup of previous results
_rename_results(self.net)
# additionally, write bus power injection results (these are not written in _extract_results)
mapping_table = self.net["_pd2ppc_lookups"]["bus"]
self.net.res_bus_est.p_mw = -get_values(
ppc["bus"][:, 2], self.net.bus.index.values, mapping_table)
self.net.res_bus_est.q_mvar = -get_values(
ppc["bus"][:, 3], self.net.bus.index.values, mapping_table)
_clean_up(self.net)
# clear the aux elements and calculation results created for the substitution of bb switches
if fuse_buses_with_bb_switch != 'all' and not self.net.switch.empty:
_drop_aux_elements_for_bb_switch(self.net)
# delete results which are not correctly calculated
for k in list(self.net.keys()):
if k.startswith("res_") and k.endswith("_est") and \
k not in ("res_bus_est", "res_line_est", "res_trafo_est", "res_trafo3w_est"):
del self.net[k]
return self.estimator.successful
def _optimal_powerflow(net, verbose, suppress_warnings, **kwargs):
ac = net["_options"]["ac"]
init = net["_options"]["init"]
if "OPF_FLOW_LIM" not in kwargs:
kwargs["OPF_FLOW_LIM"] = 2
if net["_options"]["voltage_depend_loads"] and not (
allclose(net.load.const_z_percent.values, 0)
and allclose(net.load.const_i_percent.values, 0)):
logger.error(
"pandapower optimal_powerflow does not support voltage depend loads."
)
ppopt = ppoption(VERBOSE=verbose, PF_DC=not ac, INIT=init, **kwargs)
net["OPF_converged"] = False
net["converged"] = False
_add_auxiliary_elements(net)
if not ac or net["_options"]["init_results"]:
verify_results(net)
else:
init_results(net, "opf")
ppc, ppci = _pd2ppc(net)
if not ac:
ppci["bus"][:, VM] = 1.0
net["_ppc_opf"] = ppci
if len(net.dcline) > 0:
ppci = add_userfcn(ppci,
'formulation',
_add_dcline_constraints,
args=net)
if init == "pf":
ppci = _run_pf_before_opf(net, ppci)
if suppress_warnings:
with warnings.catch_warnings():
warnings.simplefilter("ignore")
result = opf(ppci, ppopt)
else:
result = opf(ppci, ppopt)
# net["_ppc_opf"] = result
if verbose:
ppopt['OUT_ALL'] = 1
printpf(baseMVA=result["baseMVA"],
bus=result["bus"],
gen=result["gen"],
branch=result["branch"],
f=result["f"],
success=result["success"],
et=result["et"],
fd=stdout,
ppopt=ppopt)
if not result["success"]:
raise OPFNotConverged("Optimal Power Flow did not converge!")
# ppci doesn't contain out of service elements, but ppc does -> copy results accordingly
mode = net["_options"]["mode"]
result = _copy_results_ppci_to_ppc(result, ppc, mode=mode)
# net["_ppc_opf"] = result
net["OPF_converged"] = True
_extract_results(net, result)
_clean_up(net)
def cleanup(self):
_clean_up(self.net)
self.init_newton_variables()