def generate_simple_sets(model_run):
"""
Generate basic sets for a given pre-processed ``model_run``.
Parameters
----------
model_run : AttrDict
"""
sets = AttrDict()
flat_techs = model_run.techs.as_dict(flat=True)
flat_locations = model_run.locations.as_dict(flat=True)
sets.resources = set(
flatten_list(v for k, v in flat_techs.items() if '.carrier' in k))
sets.carriers = sets.resources - set(['resource'])
sets.carrier_tiers = set(
key.split('.carrier_')[1] for key in flat_techs.keys()
if '.carrier_' in key)
sets.costs = set(
k.split('costs.')[-1].split('.')[0] for k in flat_locations.keys()
if '.costs.' in k)
sets.locs = set(model_run.locations.keys())
sets.techs_non_transmission = set()
tech_groups = [
'demand', 'supply', 'supply_plus', 'conversion', 'conversion_plus',
'storage'
]
for tech_group in tech_groups:
sets['techs_{}'.format(tech_group)] = set(
k for k, v in model_run.techs.items()
if v.inheritance[-1] == tech_group)
sets.techs_non_transmission.update(sets['techs_{}'.format(tech_group)])
sets.techs_transmission_names = set(k for k, v in model_run.techs.items()
if v.inheritance[-1] == 'transmission')
# This builds the "tech:loc" expansion of transmission technologies
techs_transmission = set()
for loc_name, loc_config in model_run.locations.items():
for link_name, link_config in loc_config.get('links', {}).items():
for tech_name in link_config.techs:
techs_transmission.add('{}:{}'.format(tech_name, link_name))
sets.techs_transmission = techs_transmission
sets.techs = sets.techs_non_transmission | sets.techs_transmission_names
# this extracts location coordinate information
coordinates = set(
k.split('.')[-1] for k in flat_locations.keys()
if '.coordinates.' in k)
if coordinates:
sets.coordinates = coordinates
# `timesteps` set is built from the results of timeseries_data processing
sets.timesteps = list(model_run.timesteps.astype(str))
model_run.del_key('timesteps')
# `techlists` are strings with comma-separated techs used for grouping in
# some model-wide constraints
sets.techlists = set()
for k in model_run.model.get_key('group_share', {}).keys():
sets.techlists.add(k)
# `constraint_groups` are the group names per constraint that is defined
# at a group level
sets.group_constraints = set()
group_constraints = AttrDict({
name: data
for name, data in model_run['group_constraints'].items()
if data.get("exists", True)
})
if len(group_constraints.keys()) > 0:
sets.group_constraints.update(
i.split('.')[1] for i in group_constraints.as_dict_flat().keys()
if i.split('.')[1] not in ['techs', 'locs'])
for constr in sets.group_constraints:
sets['group_names_' + constr] = set(
k for k, v in group_constraints.items() if constr in v.keys())
return sets
def generate_simple_sets(model_run):
"""
Generate basic sets for a given pre-processed ``model_run``.
Parameters
----------
model_run : AttrDict
"""
sets = AttrDict()
flat_techs = model_run.techs.as_dict(flat=True)
flat_locations = model_run.locations.as_dict(flat=True)
sets.resources = set(
flatten_list(v for k, v in flat_techs.items() if '.carrier' in k))
sets.carriers = sets.resources - set(['resource'])
sets.carrier_tiers = set(
key.split('.carrier_')[1] for key in flat_techs.keys()
if '.carrier_' in key)
sets.costs = set(
k.split('costs.')[-1].split('.')[0] for k in flat_locations.keys()
if '.costs.' in k)
sets.locs = set(model_run.locations.keys())
sets.techs_non_transmission = set(k for k, v in model_run.techs.items()
if v.inheritance[-1] != 'transmission')
sets.techs_transmission_names = set(k for k, v in model_run.techs.items()
if v.inheritance[-1] == 'transmission')
# This builds the "tech:loc" expansion of transmission technologies
techs_transmission = set()
for loc_name, loc_config in model_run.locations.items():
for link_name, link_config in loc_config.get('links', {}).items():
for tech_name in link_config.techs:
techs_transmission.add('{}:{}'.format(tech_name, link_name))
sets.techs_transmission = techs_transmission
sets.techs = sets.techs_non_transmission | sets.techs_transmission_names
# this extracts location coordinate information
coordinates = set(
k.split('.')[-1] for k in flat_locations.keys()
if '.coordinates.' in k)
if coordinates:
sets.coordinates = coordinates
# `timesteps` set is built from the results of timeseries_data processing
sets.timesteps = list(model_run.timesteps.astype(str))
model_run.del_key('timesteps')
# `techlists` are strings with comma-separated techs used for grouping in
# some model-wide constraints
sets.techlists = set()
for k in model_run.model.get_key('group_share', {}).keys():
sets.techlists.add(k)
return sets
def generate_simple_sets(model_run):
"""
Generate basic sets for a given pre-processed ``model_run``.
Parameters
----------
model_run : AttrDict
"""
sets = AttrDict()
flat_techs = model_run.techs.as_dict(flat=True)
flat_locations = model_run.locations.as_dict(flat=True)
sets.resources = set(flatten_list(
v for k, v in flat_techs.items()
if '.carrier' in k
))
sets.carriers = sets.resources - set(['resource'])
sets.carrier_tiers = set(
key.split('.carrier_')[1]
for key in flat_techs.keys()
if '.carrier_' in key
)
sets.costs = set(
k.split('costs.')[-1].split('.')[0]
for k in flat_locations.keys()
if '.costs.' in k)
sets.locs = set(model_run.locations.keys())
sets.techs_non_transmission = set(
k for k, v in model_run.techs.items()
if v.inheritance[-1] != 'transmission')
sets.techs_transmission_names = set(
k for k, v in model_run.techs.items()
if v.inheritance[-1] == 'transmission')
# This builds the "tech:loc" expansion of transmission technologies
techs_transmission = set()
for loc_name, loc_config in model_run.locations.items():
for link_name, link_config in loc_config.get('links', {}).items():
for tech_name in link_config.techs:
techs_transmission.add('{}:{}'.format(tech_name, link_name))
sets.techs_transmission = techs_transmission
sets.techs = sets.techs_non_transmission | sets.techs_transmission_names
# this extracts location coordinate information
coordinates = set(
k.split('.')[-1] for k in flat_locations.keys()
if '.coordinates.' in k)
if coordinates:
sets.coordinates = coordinates
# `timesteps` set is built from the results of timeseries_data processing
sets.timesteps = list(model_run.timesteps.astype(str))
model_run.del_key('timesteps')
# `techlists` are strings with comma-separated techs used for grouping in
# some model-wide constraints
sets.techlists = set()
for k in model_run.model.get_key('group_share', {}).keys():
sets.techlists.add(k)
return sets
