def read_add(system, file):
"""
Read an addition PSS/E dyr file.
Parameters
----------
system : System
System instance to which data will be loaded
file : str
Path to the additional `dyr` file
Returns
-------
bool
data parsing status
"""
dyr_dict = _read_dyr_dict(file)
system.dyr_dict = dyr_dict
# read yaml and set header for each pss/e model
dirname = os.path.dirname(__file__)
with open(f'{dirname}/psse-dyr.yaml', 'r') as f:
dyr_yaml = yaml.full_load(f)
sorted_models = sort_psse_models(dyr_yaml, system)
for psse_model in dyr_dict:
if psse_model in dyr_yaml:
if 'inputs' in dyr_yaml[psse_model]:
dyr_dict[psse_model].columns = dyr_yaml[psse_model]['inputs']
# collect not supported models
not_supported = []
for model in dyr_dict:
if model not in sorted_models:
not_supported.append(model)
# print out debug messages
if len(dyr_dict):
logger.debug('dyr contains models %s', ", ".join(dyr_dict.keys()))
if len(not_supported):
logger.warning('Models not yet supported: %s',
", ".join(not_supported))
else:
logger.debug('All dyr models are supported.')
# load data into models
for psse_model in sorted_models:
if psse_model not in dyr_dict:
# device not exist
continue
if psse_model not in dyr_yaml:
logger.error(f"PSS/E Model <{psse_model}> is not supported.")
continue
logger.debug(f'Parsing PSS/E model {psse_model}')
dest = dyr_yaml[psse_model]['destination']
find = {}
if 'find' in dyr_yaml[psse_model]:
for name, source in dyr_yaml[psse_model]['find'].items():
for model, conditions in source.items():
allow_none = conditions.pop('allow_none', 0)
cond_names = conditions.keys()
cond_values = []
for col in conditions.values():
if col in find:
cond_values.append(find[col])
else:
cond_values.append(dyr_dict[psse_model][col])
try:
logger.debug(
"<%s> trying to find <%s> using cond_names=%s and cond_values=%s",
psse_model, model, cond_names, cond_values)
logger.debug("<%s> contains %d devices", model,
system.__dict__[model].n)
find[name] = system.__dict__[model].find_idx(
cond_names, cond_values, allow_none=allow_none)
except IndexError as e:
logger.error(
"Data file likely contains references to unsupported models."
)
logger.error(e)
return False
if 'get' in dyr_yaml[psse_model]:
for name, source in dyr_yaml[psse_model]['get'].items():
for model, conditions in source.items():
idx_name = conditions['idx']
if idx_name in dyr_dict[psse_model]:
conditions['idx'] = dyr_dict[psse_model][idx_name]
else:
conditions['idx'] = find[idx_name]
find[name] = system.__dict__[model].get(**conditions)
if 'outputs' in dyr_yaml[psse_model]:
output_keys = list(dyr_yaml[psse_model]['outputs'].keys())
output_exprs = list(dyr_yaml[psse_model]['outputs'].values())
out_dict = {}
for idx in range(len(output_exprs)):
out_key = output_keys[idx]
expr = output_exprs[idx]
if expr in find:
out_dict[out_key] = find[expr]
elif ';' in expr:
args, func = expr.split(';')
func = eval(func)
args = args.split(',')
# support local and external model parameters
argv = list()
for param in args:
if '.' in param:
argv.append(param.split('.'))
else:
argv.append((psse_model, param))
argv = [dyr_dict[model][param] for model, param in argv]
out_dict[output_keys[idx]] = func(*argv)
else:
out_dict[output_keys[idx]] = dyr_dict[psse_model][expr]
df = pd.DataFrame.from_dict(out_dict)
for row in df.to_dict(orient='records'):
system.add(dest, row)
system.link_ext_param(system.__dict__[dest])
return True
def read_add(system, file):
"""
Read addition PSS/E dyr file.
Parameters
----------
system
file
Returns
-------
"""
warn_experimental("PSS/E dyr support")
with open(file, 'r') as f:
input_list = [line.strip() for line in f]
# concatenate multi-line device data
input_concat_dict = defaultdict(list)
multi_line = list()
for i, line in enumerate(input_list):
if line == '':
continue
if '/' not in line:
multi_line.append(line)
else:
multi_line.append(line.split('/')[0])
single_line = ' '.join(multi_line)
single_list = single_line.split("'")
psse_model = single_list[1].strip()
input_concat_dict[psse_model].append(single_list[0] +
single_list[2])
multi_line = list()
# construct pandas dataframe for all models
dyr_dict = dict()
for psse_model, all_rows in input_concat_dict.items():
dev_params_num = [([to_number(cell) for cell in row.split()])
for row in all_rows]
dyr_dict[psse_model] = pd.DataFrame(dev_params_num)
# read yaml and set header for each pss/e model
dirname = os.path.dirname(__file__)
with open(f'{dirname}/psse-dyr.yaml', 'r') as f:
dyr_yaml = yaml.full_load(f)
for psse_model in dyr_dict:
if psse_model in dyr_yaml:
if 'inputs' in dyr_yaml[psse_model]:
dyr_dict[psse_model].columns = dyr_yaml[psse_model]['inputs']
# load data into models
for psse_model in dyr_dict:
if psse_model not in dyr_yaml:
logger.error(f"PSS/E Model <{psse_model}> is not supported.")
continue
dest = dyr_yaml[psse_model]['destination']
find = {}
if 'find' in dyr_yaml[psse_model]:
for name, source in dyr_yaml[psse_model]['find'].items():
for model, conditions in source.items():
cond_names = conditions.keys()
cond_values = [
dyr_dict[psse_model][col]
for col in conditions.values()
]
find[name] = system.__dict__[model].find_idx(
cond_names, cond_values)
if 'get' in dyr_yaml[psse_model]:
for name, source in dyr_yaml[psse_model]['get'].items():
for model, conditions in source.items():
idx_name = conditions['idx']
if idx_name in dyr_dict[psse_model]:
conditions['idx'] = dyr_dict[psse_model][idx_name]
else:
conditions['idx'] = find[idx_name]
find[name] = system.__dict__[model].get(**conditions)
if 'outputs' in dyr_yaml[psse_model]:
output_keys = list(dyr_yaml[psse_model]['outputs'].keys())
output_exprs = list(dyr_yaml[psse_model]['outputs'].values())
out_dict = {}
for idx in range(len(output_exprs)):
out_key = output_keys[idx]
expr = output_exprs[idx]
if expr in find:
out_dict[out_key] = find[expr]
elif ';' in expr:
args, func = expr.split(';')
func = eval(func)
args = args.split(',')
argv = [pairs.split('.') for pairs in args]
argv = [dyr_dict[model][param] for model, param in argv]
out_dict[output_keys[idx]] = func(*argv)
else:
out_dict[output_keys[idx]] = dyr_dict[psse_model][expr]
df = pd.DataFrame.from_dict(out_dict)
for row in df.to_dict(orient='records'):
system.add(dest, row)
system.link_ext_param(system.__dict__[dest])
return True
https://github.com/anderson-optimization/em-psse
License Pending
"""
import os
from io import StringIO
from andes.shared import pd, yaml
import logging
logger = logging.getLogger(__name__)
dirname = os.path.dirname(__file__)
with open('{}/psse-modes.yaml'.format(dirname), 'r') as in_file:
modes = yaml.full_load(in_file)
def get_signals(line_num, line, current_mode):
# print(line_num,line)
signals = []
for m in modes:
for s in m['signal']:
if 'text' in s:
if s['text'] in line:
signals.append((s, m))
if 'line' in s:
if s['line'] == line_num:
signals.append((s, m))
return signals
def read_add(system, file):
"""
Read an addition PSS/E dyr file.
Parameters
----------
system : System
System instance to which data will be loaded
file : str
Path to the additional `dyr` file
Returns
-------
bool
data parsing status
"""
with open(file, 'r') as f:
input_list = [line.strip() for line in f]
# concatenate multi-line device data
input_concat_dict = defaultdict(list)
multi_line = list()
for i, line in enumerate(input_list):
if line == '':
continue
if '/' not in line:
multi_line.append(line)
else:
multi_line.append(line.split('/')[0])
single_line = ' '.join(multi_line)
if single_line.strip() == '':
continue
single_list = single_line.split("'")
psse_model = single_list[1].strip()
input_concat_dict[psse_model].append(single_list[0] +
single_list[2])
multi_line = list()
# construct pandas dataframe for all models
dyr_dict = dict() # input data from dyr file
for psse_model, all_rows in input_concat_dict.items():
dev_params_num = [([to_number(cell) for cell in row.split()])
for row in all_rows]
dyr_dict[psse_model] = pd.DataFrame(dev_params_num)
# read yaml and set header for each pss/e model
dirname = os.path.dirname(__file__)
with open(f'{dirname}/psse-dyr.yaml', 'r') as f:
dyr_yaml = yaml.full_load(f)
sorted_models = sort_psse_models(dyr_yaml)
for psse_model in dyr_dict:
if psse_model in dyr_yaml:
if 'inputs' in dyr_yaml[psse_model]:
dyr_dict[psse_model].columns = dyr_yaml[psse_model]['inputs']
# collect not supported models
not_supported = []
for model in dyr_dict:
if model not in sorted_models:
not_supported.append(model)
# print out debug messages
if len(dyr_dict):
logger.debug(f'dyr contains models {", ".join(dyr_dict.keys())}')
if len(not_supported):
logger.warning(f'Models not yet supported: {", ".join(not_supported)}')
else:
logger.debug('All dyr models are supported.')
# load data into models
for psse_model in sorted_models:
if psse_model not in dyr_dict:
# device not exist
continue
if psse_model not in dyr_yaml:
logger.error(f"PSS/E Model <{psse_model}> is not supported.")
continue
logger.debug(f'Parsing PSS/E model {psse_model}')
dest = dyr_yaml[psse_model]['destination']
find = {}
if 'find' in dyr_yaml[psse_model]:
for name, source in dyr_yaml[psse_model]['find'].items():
for model, conditions in source.items():
allow_none = conditions.pop('allow_none', 0)
cond_names = conditions.keys()
cond_values = []
for col in conditions.values():
if col in find:
cond_values.append(find[col])
else:
cond_values.append(dyr_dict[psse_model][col])
try:
find[name] = system.__dict__[model].find_idx(
cond_names, cond_values, allow_none=allow_none)
except IndexError as e:
logger.error(
"Data file likely contains references to unsupported models."
)
logger.error(e)
return False
if 'get' in dyr_yaml[psse_model]:
for name, source in dyr_yaml[psse_model]['get'].items():
for model, conditions in source.items():
idx_name = conditions['idx']
if idx_name in dyr_dict[psse_model]:
conditions['idx'] = dyr_dict[psse_model][idx_name]
else:
conditions['idx'] = find[idx_name]
find[name] = system.__dict__[model].get(**conditions)
if 'outputs' in dyr_yaml[psse_model]:
output_keys = list(dyr_yaml[psse_model]['outputs'].keys())
output_exprs = list(dyr_yaml[psse_model]['outputs'].values())
out_dict = {}
for idx in range(len(output_exprs)):
out_key = output_keys[idx]
expr = output_exprs[idx]
if expr in find:
out_dict[out_key] = find[expr]
elif ';' in expr:
args, func = expr.split(';')
func = eval(func)
args = args.split(',')
argv = [pairs.split('.') for pairs in args]
argv = [dyr_dict[model][param] for model, param in argv]
out_dict[output_keys[idx]] = func(*argv)
else:
out_dict[output_keys[idx]] = dyr_dict[psse_model][expr]
df = pd.DataFrame.from_dict(out_dict)
for row in df.to_dict(orient='records'):
system.add(dest, row)
system.link_ext_param(system.__dict__[dest])
return True
def read_add(system, file):
"""
Read addition PSS/E dyr file.
TODO: implement this function
Parameters
----------
system
file
Returns
-------
"""
warn_experimental("PSS/E dyr support is incomplete.")
with open(file, 'r') as f:
input_list = [line.strip() for line in f]
# concatenate multi-line device data
all_dict = defaultdict(list)
data_list = list()
for i, line in enumerate(input_list):
if line == '':
continue
if '/' not in line:
data_list.append(line)
else:
data_list.append(line.split('/')[0])
data_str = ' '.join(data_list)
data_split = data_str.split("'")
model_name = data_split[1].strip()
all_dict[model_name].append(data_split[0] + data_split[2])
data_list = list()
# construct pandas dataframe for all models
df_dict = dict()
for key, val in all_dict.items():
df_1row = pd.DataFrame(val)
df_str = df_1row[0].str.split(expand=True)
df_dict[key] = df_str.astype(float)
# set header for each
dirname = os.path.dirname(__file__)
with open('{}/psse-dyr.yaml'.format(dirname), 'r') as f:
dyr_format = yaml.full_load(f)
dyr_dict = dict()
for item in dyr_format:
dyr_dict.update(item)
for key in df_dict:
if key in dyr_dict:
if 'inputs' in dyr_dict[key]:
df_dict[key].columns = dyr_dict[key]['inputs']
system.df_dict = df_dict
# TODO: Load data into models
return True