def solve_network(n, config, solver_log=None, opts='', **kwargs):
solver_options = config['solving']['solver'].copy()
solver_name = solver_options.pop('name')
cf_solving = config['solving']['options']
track_iterations = cf_solving.get('track_iterations', False)
min_iterations = cf_solving.get('min_iterations', 4)
max_iterations = cf_solving.get('max_iterations', 6)
# add to network for extra_functionality
n.config = config
n.opts = opts
if cf_solving.get('skip_iterations', False):
network_lopf(n,
solver_name=solver_name,
solver_options=solver_options,
extra_functionality=None,
**kwargs)
else:
ilopf(n,
solver_name=solver_name,
solver_options=solver_options,
track_iterations=track_iterations,
min_iterations=min_iterations,
max_iterations=max_iterations,
extra_functionality=None,
**kwargs)
return n
def solve_network(n,
config,
solver_log=None,
opts="",
extra_functionality=None,
**kwargs):
solver_options = config["solving"]["solver"].copy()
solver_name = solver_options.pop("name")
track_iterations = config["solving"]["options"].get(
"track_iterations", False)
min_iterations = config["solving"]["options"].get("min_iterations", 4)
max_iterations = config["solving"]["options"].get("max_iterations", 6)
# add to network for extra_functionality
n.config = config
n.opts = opts
if config["solving"]["options"].get("skip_iterations", False):
network_lopf(n,
solver_name=solver_name,
solver_options=solver_options,
extra_functionality=extra_functionality,
**kwargs)
else:
ilopf(n,
solver_name=solver_name,
solver_options=solver_options,
track_iterations=track_iterations,
min_iterations=min_iterations,
max_iterations=max_iterations,
extra_functionality=extra_functionality,
**kwargs)
return n
