def _runpm(net,
delete_buffer_file=True,
pm_file_path=None): # pragma: no cover
"""
Converts the pandapower net to a pm json file, saves it to disk, runs a PowerModels.jl julia function and reads
the results back to the pandapower net
INPUT
----------
**net** - pandapower net
OPTIONAL
----------
**delete_buffer_file** (bool, True) - deletes the pm buffer json file if True.
"""
# convert pandapower to power models file -> this is done in python
net, pm, ppc, ppci = convert_to_pm_structure(net)
# call optinal callback function
if net._options["pp_to_pm_callback"] is not None:
net._options["pp_to_pm_callback"](net, ppci, pm)
# writes pm json to disk, which is loaded afterwards in julia
buffer_file = dump_pm_json(pm, pm_file_path)
# run power models optimization in julia
result_pm = _call_powermodels(buffer_file, net._options["julia_file"])
# read results and write back to net
read_pm_results_to_net(net, ppc, ppci, result_pm)
if pm_file_path is None and delete_buffer_file:
# delete buffer file after calculation
os.remove(buffer_file)
def _runpm(net,
delete_buffer_file=True,
pm_file_path=None,
pdm_dev_mode=False):
"""
Converts the pandapower net to a pm json file, saves it to disk, runs a PandaModels.jl, and reads
the results back to the pandapower net:
INPUT
----------
**net** - pandapower net
OPTIONAL
----------
**delete_buffer_file** (bool, True) - deletes the pm buffer json file if True.
**pm_file_path** -path to save the converted net json file.
**pdm_dev_mode** (bool, False) - If True, the develop mode of PdM is called.
"""
# convert pandapower to power models file -> this is done in python
net, pm, ppc, ppci = convert_to_pm_structure(net)
# call optional callback function
if net._options["pp_to_pm_callback"] is not None:
net._options["pp_to_pm_callback"](net, ppci, pm)
# writes pm json to disk, which is loaded afterwards in julia
buffer_file = dump_pm_json(pm, pm_file_path)
logger.debug("the json file for converted net is stored in: %s" %
buffer_file)
# run power models optimization in julia
result_pm = _call_pandamodels(buffer_file, net._options["julia_file"],
pdm_dev_mode)
# read results and write back to net
read_pm_results_to_net(net, ppc, ppci, result_pm)
if pm_file_path is None and delete_buffer_file:
# delete buffer file after calculation
os.remove(buffer_file)
logger.debug("the json file for converted net is deleted from %s" %
buffer_file)
def test_pm_to_pp_conversion(simple_opf_test_net):
# this tests checks if the runopp results are the same as the ones from powermodels.
# Results are read from a result file containing the simple_opf_test_net
net = simple_opf_test_net
pp.create_poly_cost(net, 0, "gen", cp1_eur_per_mw=100)
# get pandapower opf results
pp.runopp(net, delta=1e-13)
va_degree = copy.deepcopy(net.res_bus.va_degree)
vm_pu = copy.deepcopy(net.res_bus.vm_pu)
# get previously calculated power models results
pm_res_file = os.path.join(os.path.abspath(os.path.dirname(pp.test.__file__)),
"test_files", "pm_example_res.json")
with open(pm_res_file, "r") as fp:
result_pm = json.load(fp)
net._options["correct_pm_network_data"] = True
ppc, ppci = _pd2ppc(net)
read_pm_results_to_net(net, ppc, ppci, result_pm)
assert np.allclose(net.res_bus.vm_pu, vm_pu, atol=1e-4)
assert np.allclose(net.res_bus.va_degree, va_degree, atol=1e-2, rtol=1e-2)