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