def _run_pf_algorithm(ppci, options, **kwargs):
algorithm = options["algorithm"]
ac = options["ac"]
if ac:
_, pv, pq = bustypes(ppci["bus"], ppci["gen"])
# ----- run the powerflow -----
if pq.shape[0] == 0 and pv.shape[
0] == 0 and not options['distributed_slack']:
# ommission not correct if distributed slack is used
result = _bypass_pf_and_set_results(ppci, options)
elif algorithm == 'bfsw': # forward/backward sweep power flow algorithm
result = _run_bfswpf(ppci, options, **kwargs)[0]
elif algorithm in ['nr', 'iwamoto_nr']:
result = _run_newton_raphson_pf(ppci, options)
elif algorithm in ['fdbx', 'fdxb',
'gs']: # algorithms existing within pypower
result = _runpf_pypower(ppci, options, **kwargs)[0]
else:
raise AlgorithmUnknown(
"Algorithm {0} is unknown!".format(algorithm))
else:
result = _run_dc_pf(ppci)
return result
def _run_pf_algorithm(ppci, options, **kwargs):
algorithm = options["algorithm"]
ac = options["ac"]
if ac:
# ----- run the powerflow -----
if algorithm == 'bfsw': # forward/backward sweep power flow algorithm
result = _run_bfswpf(ppci, options, **kwargs)[0]
elif algorithm == 'nr':
result = _run_newton_raphson_pf(ppci, options)
elif algorithm in ['fdbx', 'fdxb', 'gs']: # algorithms existing within pypower
result = _runpf_pypower(ppci, options, **kwargs)[0]
else:
raise AlgorithmUnknown("Algorithm {0} is unknown!".format(algorithm))
else:
result = _run_dc_pf(ppci)
return result
def test_to_ppc_and_mpc():
# pypower cases to validate
functions = ['case4gs', 'case6ww', 'case30', 'case39']
for fn in functions:
# get pypower grids with results
ppc_net = get_testgrids(fn, 'pypower_cases.p')
# get pandapower grids
pandapower_module = __import__('pandapower', fromlist=['networks'])
pandapower_function = getattr(pandapower_module.networks, fn)
net = pandapower_function()
reset_results(net)
# This should be reviewed
pp.runpp(net)
# convert pandapower grids to ppc
ppc = cv.to_ppc(net)
# convert pandapower grids to mpc (no result validation)
mpc = cv.to_mpc(net)
# validate voltage results of pandapower-to-ppc-converted grids vs. original pypower results
net["_options"]['ac'] = True
net["_options"]['numba'] = True
net["_options"]['tolerance_mva'] = 1e-8
net["_options"]['algorithm'] = "fdbx"
net["_options"]['max_iteration'] = 30
net["_options"]['enforce_q_lims'] = False
net["_options"]['calculate_voltage_angles'] = True
res_converted_pp, status_converted_pp = _runpf_pypower(
ppc, net["_options"])
if status_converted_pp:
# get lookup pp2ppc
bus_lookup = net["_pd2ppc_lookups"]["bus"]
# check for equality in bus voltages
pp_buses = bus_lookup[res_converted_pp['bus'][:,
BUS_I].astype(int)]
res1 = res_converted_pp['bus'][pp_buses, VM:VA + 1]
res2 = ppc_net['bus'][:, VM:VA + 1]
assert np.allclose(res1, res2)
else:
raise LoadflowNotConverged("Loadflow did not converge!")
def _run_pf_algorithm(ppci, options, **kwargs):
algorithm = options["algorithm"]
ac = options["ac"]
if ac:
# ----- run the powerflow -----
if ppci["branch"].shape[0] == 0:
result = _pf_without_branches(ppci, options)
elif algorithm == 'bfsw': # forward/backward sweep power flow algorithm
result = _run_bfswpf(ppci, options, **kwargs)[0]
elif algorithm in ['nr', 'iwamoto_nr']:
result = _run_newton_raphson_pf(ppci, options)
elif algorithm in ['fdbx', 'fdxb']: # fdbx/xb new algos
# this implematation will much like be the newton_raphson
result = _run_fast_decoupled_pf(ppci, options)
elif algorithm == 'gs': # last algorithm imported from pypower
result = _runpf_pypower(ppci, options, **kwargs)[0]
else:
raise AlgorithmUnknown(
"Algorithm {0} is unknown!".format(algorithm))
else:
result = _run_dc_pf(ppci)
return result