def __init__(self, detailed_infos_for_cascading_failures=False):
"""
Initialize an instance of Backend. This does nothing per se. Only the call to :func:`Backend.load_grid`
should guarantee the backend is properly configured.
:param detailed_infos_for_cascading_failures: Whether to be detailed (but slow) when computing cascading failures
:type detailed_infos_for_cascading_failures: :class:`bool`
"""
# lazy loading
from grid2op.Action import CompleteAction
from grid2op.Action._BackendAction import _BackendAction
GridObjects.__init__(self)
# the following parameter is used to control the amount of verbosity when computing a cascading failure
# if it's set to true, it returns all intermediate _grid states. This can slow down the computation!
self.detailed_infos_for_cascading_failures = detailed_infos_for_cascading_failures
# the power _grid manipulated. One powergrid per backend.
self._grid = None
# thermal limit setting, in ampere, at the same "side" of the powerline than self.get_line_overflow
self.thermal_limit_a = None
# action to set me
self.my_bk_act_class = _BackendAction
self._complete_action_class = CompleteAction
# for the shunt (only if supported)
self._sh_vnkv = None # for each shunt gives the nominal value at the bus at which it is connected
def __init__(self):
GridObjects.__init__(self)
# last connected registered
self.last_topo_registered = ValueStore(self.dim_topo, dtype=dt_int)
# topo at time t
self.current_topo = ValueStore(self.dim_topo, dtype=dt_int)
# injection at time t
self.prod_p = ValueStore(self.n_gen, dtype=dt_float)
self.prod_v = ValueStore(self.n_gen, dtype=dt_float)
self.load_p = ValueStore(self.n_load, dtype=dt_float)
self.load_q = ValueStore(self.n_load, dtype=dt_float)
self.activated_bus = np.full((self.n_sub, 2),
dtype=dt_bool,
fill_value=False)
self.big_topo_to_subid = np.repeat(list(range(self.n_sub)),
repeats=self.sub_info)
# shunts
if self.shunts_data_available:
self.shunt_p = ValueStore(self.n_shunt, dtype=dt_float)
self.shunt_q = ValueStore(self.n_shunt, dtype=dt_float)
self.shunt_bus = ValueStore(self.n_shunt, dtype=dt_int)
def __init__(self, envs):
GridObjects.__init__(self)
self.envs = envs
for env in envs:
if not isinstance(env, Environment):
raise MultiEnvException(
"You provided environment of type \"{}\" which is not supported."
"Please only provide a grid2op.Environment.Environment class."
"".format(type(env)))
self.nb_env = len(envs)
max_int = np.iinfo(dt_int).max
self._remotes, self._work_remotes = zip(
*[Pipe() for _ in range(self.nb_env)])
env_params = [
envs[e].get_kwargs(with_backend=False) for e in range(self.nb_env)
]
self._ps = [
RemoteEnv(env_params=env_,
remote=work_remote,
parent_remote=remote,
name="{}_subprocess_{}".format(envs[i].name, i),
seed=envs[i].space_prng.randint(max_int))
for i, (work_remote, remote, env_) in enumerate(
zip(self._work_remotes, self._remotes, env_params))
]
for p in self._ps:
p.daemon = True # if the main process crashes, we should not cause things to hang
p.start()
for remote in self._work_remotes:
remote.close()
self._waiting = True
def __init__(self, nb_env, env):
GridObjects.__init__(self)
self.imported_env = env
self.nb_env = nb_env
self._remotes, self._work_remotes = zip(
*[Pipe() for _ in range(self.nb_env)])
env_params = [env.get_kwargs() for _ in range(self.nb_env)]
for el in env_params:
el["backendClass"] = type(env.backend)
self._ps = [
RemoteEnv(env_params=env_,
remote=work_remote,
parent_remote=remote,
name="env: {}".format(i),
seed=np.random.randint(np.iinfo(dt_int).max))
for i, (work_remote, remote, env_) in enumerate(
zip(self._work_remotes, self._remotes, env_params))
]
for p in self._ps:
p.daemon = True # if the main process crashes, we should not cause things to hang
p.start()
for remote in self._work_remotes:
remote.close()
self._waiting = True
def __init__(
self,
envs_dir,
_add_to_name="", # internal, for test only, do not use !
**kwargs):
GridObjects.__init__(self)
RandomObject.__init__(self)
self.current_env = None
self.env_index = None
self.mix_envs = []
# Special case handling for backend
backendClass = None
if "backend" in kwargs:
backendClass = type(kwargs["backend"])
del kwargs["backend"]
# Inline import to prevent cyclical import
from grid2op.MakeEnv.Make import make
try:
for env_dir in sorted(os.listdir(envs_dir)):
env_path = os.path.join(envs_dir, env_dir)
if not os.path.isdir(env_path):
continue
# Special case for backend
if backendClass is not None:
env = make(env_path,
backend=backendClass(),
_add_to_name=_add_to_name,
**kwargs)
else:
env = make(env_path, **kwargs)
self.mix_envs.append(env)
except Exception as e:
err_msg = "MultiMix environment creation failed: {}".format(e)
raise EnvError(err_msg)
if len(self.mix_envs) == 0:
err_msg = "MultiMix envs_dir did not contain any valid env"
raise EnvError(err_msg)
self.env_index = 0
self.current_env = self.mix_envs[self.env_index]
# Make sure GridObject class attributes are set from first env
# Should be fine since the grid is the same for all envs
multi_env_name = os.path.basename(
os.path.abspath(envs_dir)) + _add_to_name
save_env_name = self.current_env.env_name
self.current_env.env_name = multi_env_name
self.__class__ = self.init_grid(self.current_env)
self.current_env.env_name = save_env_name
def __init__(self, detailed_infos_for_cascading_failures=False):
"""
Initialize an instance of Backend. This does nothing per se. Only the call to :func:`Backend.load_grid`
should guarantee the backend is properly configured.
:param detailed_infos_for_cascading_failures: Whether to be detailed (but slow) when computing cascading failures
:type detailed_infos_for_cascading_failures: :class:`bool`
"""
GridObjects.__init__(self)
# the following parameter is used to control the amount of verbosity when computing a cascading failure
# if it's set to true, it returns all intermediate _grid states. This can slow down the computation!
self.detailed_infos_for_cascading_failures = detailed_infos_for_cascading_failures
# the power _grid manipulated. One powergrid per backend.
self._grid = None
# thermal limit setting, in ampere, at the same "side" of the powerline than self.get_line_overflow
self.thermal_limit_a = None
def __init__(self, obs_env=None, action_helper=None, seed=None):
GridObjects.__init__(self)
self.action_helper = action_helper
# time stamp information
self.year = 1970
self.month = 0
self.day = 0
self.hour_of_day = 0
self.minute_of_hour = 0
self.day_of_week = 0
# for non deterministic observation that would not use default np.random module
self.seed = None
# handles the forecasts here
self._forecasted_grid_act = {}
self._forecasted_inj = []
self.timestep_overflow = np.zeros(shape=(self.n_line, ), dtype=dt_int)
# 0. (line is disconnected) / 1. (line is connected)
self.line_status = np.ones(shape=self.n_line, dtype=dt_bool)
# topological vector
self.topo_vect = np.full(shape=self.dim_topo,
dtype=dt_int,
fill_value=0)
# generators information
self.prod_p = np.full(shape=self.n_gen,
dtype=dt_float,
fill_value=np.NaN)
self.prod_q = np.full(shape=self.n_gen,
dtype=dt_float,
fill_value=np.NaN)
self.prod_v = np.full(shape=self.n_gen,
dtype=dt_float,
fill_value=np.NaN)
# loads information
self.load_p = np.full(shape=self.n_load,
dtype=dt_float,
fill_value=np.NaN)
self.load_q = np.full(shape=self.n_load,
dtype=dt_float,
fill_value=np.NaN)
self.load_v = np.full(shape=self.n_load,
dtype=dt_float,
fill_value=np.NaN)
# lines origin information
self.p_or = np.full(shape=self.n_line,
dtype=dt_float,
fill_value=np.NaN)
self.q_or = np.full(shape=self.n_line,
dtype=dt_float,
fill_value=np.NaN)
self.v_or = np.full(shape=self.n_line,
dtype=dt_float,
fill_value=np.NaN)
self.a_or = np.full(shape=self.n_line,
dtype=dt_float,
fill_value=np.NaN)
# lines extremity information
self.p_ex = np.full(shape=self.n_line,
dtype=dt_float,
fill_value=np.NaN)
self.q_ex = np.full(shape=self.n_line,
dtype=dt_float,
fill_value=np.NaN)
self.v_ex = np.full(shape=self.n_line,
dtype=dt_float,
fill_value=np.NaN)
self.a_ex = np.full(shape=self.n_line,
dtype=dt_float,
fill_value=np.NaN)
# lines relative flows
self.rho = np.full(shape=self.n_line,
dtype=dt_float,
fill_value=np.NaN)
# cool down and reconnection time after hard overflow, soft overflow or cascading failure
self.time_before_cooldown_line = np.full(shape=self.n_line,
dtype=dt_int,
fill_value=-1)
self.time_before_cooldown_sub = np.full(shape=self.n_sub,
dtype=dt_int,
fill_value=-1)
self.time_next_maintenance = np.full(shape=self.n_line,
dtype=dt_int,
fill_value=-1)
self.duration_next_maintenance = np.full(shape=self.n_line,
dtype=dt_int,
fill_value=-1)
# calendar data
self.year = dt_int(1970)
self.month = dt_int(0)
self.day = dt_int(0)
self.hour_of_day = dt_int(0)
self.minute_of_hour = dt_int(0)
self.day_of_week = dt_int(0)
# forecasts
self._forecasted_inj = []
self._forecasted_grid = []
self._obs_env = obs_env
# redispatching
self.target_dispatch = np.full(shape=self.n_gen,
dtype=dt_float,
fill_value=np.NaN)
self.actual_dispatch = np.full(shape=self.n_gen,
dtype=dt_float,
fill_value=np.NaN)
# value to assess if two observations are equal
self._tol_equal = 5e-1
self.attr_list_vect = None
def setUp(self):
"""
The case file is a representation of the case14 as found in the ieee14 powergrid.
:return:
"""
self.tolvect = 1e-2
self.tol_one = 1e-5
self.game_rules = RulesChecker()
self.gridobj = GridObjects()
self.gridobj.init_grid_vect(
name_prod=["gen_{}".format(i) for i in range(5)],
name_load=["load_{}".format(i) for i in range(11)],
name_line=["line_{}".format(i) for i in range(20)],
name_sub=["sub_{}".format(i) for i in range(14)],
sub_info=np.array([3, 6, 4, 6, 5, 6, 3, 2, 5, 3, 3, 3, 4, 3],
dtype=np.int),
load_to_subid=np.array([1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13]),
gen_to_subid=np.array([0, 1, 2, 5, 7]),
line_or_to_subid=np.array(
[0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 6, 8, 8, 9, 11,
12]),
line_ex_to_subid=np.array([
1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11, 12, 7, 8, 9, 13, 10, 12,
13
]),
load_to_sub_pos=np.array([4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1]),
gen_to_sub_pos=np.array([2, 5, 3, 5, 1]),
line_or_to_sub_pos=np.array(
[0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2, 3, 0, 0, 1]),
line_ex_to_sub_pos=np.array(
[0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0, 0]),
load_pos_topo_vect=np.array(
[7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54]),
gen_pos_topo_vect=np.array([2, 8, 12, 29, 34]),
line_or_pos_topo_vect=np.array([
0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38,
40, 46, 50
]),
line_ex_pos_topo_vect=np.array([
3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42,
55, 43, 49, 53
]))
# pdb.set_trace()
self.res = {
'name_gen': ['gen_0', 'gen_1', 'gen_2', 'gen_3', 'gen_4'],
'name_load': [
'load_0', 'load_1', 'load_2', 'load_3', 'load_4', 'load_5',
'load_6', 'load_7', 'load_8', 'load_9', 'load_10'
],
'name_line': [
'line_0', 'line_1', 'line_2', 'line_3', 'line_4', 'line_5',
'line_6', 'line_7', 'line_8', 'line_9', 'line_10', 'line_11',
'line_12', 'line_13', 'line_14', 'line_15', 'line_16',
'line_17', 'line_18', 'line_19'
],
'name_sub': [
'sub_0', 'sub_1', 'sub_2', 'sub_3', 'sub_4', 'sub_5', 'sub_6',
'sub_7', 'sub_8', 'sub_9', 'sub_10', 'sub_11', 'sub_12',
'sub_13'
],
'sub_info': [3, 6, 4, 6, 5, 6, 3, 2, 5, 3, 3, 3, 4, 3],
'load_to_subid': [1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13],
'gen_to_subid': [0, 1, 2, 5, 7],
'line_or_to_subid':
[0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 6, 8, 8, 9, 11, 12],
'line_ex_to_subid': [
1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11, 12, 7, 8, 9, 13, 10, 12,
13
],
'load_to_sub_pos': [4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1],
'gen_to_sub_pos': [2, 5, 3, 5, 1],
'line_or_to_sub_pos':
[0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2, 3, 0, 0, 1],
'line_ex_to_sub_pos':
[0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0, 0],
'load_pos_topo_vect': [7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54],
'gen_pos_topo_vect': [2, 8, 12, 29, 34],
'line_or_pos_topo_vect': [
0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38,
40, 46, 50
],
'line_ex_pos_topo_vect': [
3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42,
55, 43, 49, 53
],
'gen_type':
None,
'gen_pmin':
None,
'gen_pmax':
None,
'gen_redispatchable':
None,
'gen_max_ramp_up':
None,
'gen_max_ramp_down':
None,
'gen_min_uptime':
None,
'gen_min_downtime':
None,
'gen_cost_per_MW':
None,
'gen_startup_cost':
None,
'gen_shutdown_cost':
None,
"grid_layout":
None,
"shunt_to_subid":
None,
"name_shunt":
None
}
# self.size_act = 229
# self.helper_action = ActionSpace(self.gridobj, legal_action=self.game_rules.legal_action)
self.helper_action = self._action_setup()
save_to_dict(self.res, self.helper_action, "subtype",
lambda x: re.sub("(<class ')|('>)", "", "{}".format(x)))
# print(self.res["subtype"])
self.authorized_keys = self.helper_action().authorized_keys
self.size_act = self.helper_action.size()
class TestActionBase(ABC):
@abstractmethod
def _action_setup(self):
pass
def _skipMissingKey(self, key):
if key not in self.authorized_keys:
unittest.TestCase.skipTest(
self, "Skipped: Missing authorized_key {key}")
def setUp(self):
"""
The case file is a representation of the case14 as found in the ieee14 powergrid.
:return:
"""
self.tolvect = 1e-2
self.tol_one = 1e-5
self.game_rules = RulesChecker()
self.gridobj = GridObjects()
self.gridobj.init_grid_vect(
name_prod=["gen_{}".format(i) for i in range(5)],
name_load=["load_{}".format(i) for i in range(11)],
name_line=["line_{}".format(i) for i in range(20)],
name_sub=["sub_{}".format(i) for i in range(14)],
sub_info=np.array([3, 6, 4, 6, 5, 6, 3, 2, 5, 3, 3, 3, 4, 3],
dtype=np.int),
load_to_subid=np.array([1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13]),
gen_to_subid=np.array([0, 1, 2, 5, 7]),
line_or_to_subid=np.array(
[0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 6, 8, 8, 9, 11,
12]),
line_ex_to_subid=np.array([
1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11, 12, 7, 8, 9, 13, 10, 12,
13
]),
load_to_sub_pos=np.array([4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1]),
gen_to_sub_pos=np.array([2, 5, 3, 5, 1]),
line_or_to_sub_pos=np.array(
[0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2, 3, 0, 0, 1]),
line_ex_to_sub_pos=np.array(
[0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0, 0]),
load_pos_topo_vect=np.array(
[7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54]),
gen_pos_topo_vect=np.array([2, 8, 12, 29, 34]),
line_or_pos_topo_vect=np.array([
0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38,
40, 46, 50
]),
line_ex_pos_topo_vect=np.array([
3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42,
55, 43, 49, 53
]))
# pdb.set_trace()
self.res = {
'name_gen': ['gen_0', 'gen_1', 'gen_2', 'gen_3', 'gen_4'],
'name_load': [
'load_0', 'load_1', 'load_2', 'load_3', 'load_4', 'load_5',
'load_6', 'load_7', 'load_8', 'load_9', 'load_10'
],
'name_line': [
'line_0', 'line_1', 'line_2', 'line_3', 'line_4', 'line_5',
'line_6', 'line_7', 'line_8', 'line_9', 'line_10', 'line_11',
'line_12', 'line_13', 'line_14', 'line_15', 'line_16',
'line_17', 'line_18', 'line_19'
],
'name_sub': [
'sub_0', 'sub_1', 'sub_2', 'sub_3', 'sub_4', 'sub_5', 'sub_6',
'sub_7', 'sub_8', 'sub_9', 'sub_10', 'sub_11', 'sub_12',
'sub_13'
],
'sub_info': [3, 6, 4, 6, 5, 6, 3, 2, 5, 3, 3, 3, 4, 3],
'load_to_subid': [1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13],
'gen_to_subid': [0, 1, 2, 5, 7],
'line_or_to_subid':
[0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 6, 8, 8, 9, 11, 12],
'line_ex_to_subid': [
1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11, 12, 7, 8, 9, 13, 10, 12,
13
],
'load_to_sub_pos': [4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1],
'gen_to_sub_pos': [2, 5, 3, 5, 1],
'line_or_to_sub_pos':
[0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2, 3, 0, 0, 1],
'line_ex_to_sub_pos':
[0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0, 0],
'load_pos_topo_vect': [7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54],
'gen_pos_topo_vect': [2, 8, 12, 29, 34],
'line_or_pos_topo_vect': [
0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38,
40, 46, 50
],
'line_ex_pos_topo_vect': [
3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42,
55, 43, 49, 53
],
'gen_type':
None,
'gen_pmin':
None,
'gen_pmax':
None,
'gen_redispatchable':
None,
'gen_max_ramp_up':
None,
'gen_max_ramp_down':
None,
'gen_min_uptime':
None,
'gen_min_downtime':
None,
'gen_cost_per_MW':
None,
'gen_startup_cost':
None,
'gen_shutdown_cost':
None,
"grid_layout":
None,
"shunt_to_subid":
None,
"name_shunt":
None
}
# self.size_act = 229
# self.helper_action = ActionSpace(self.gridobj, legal_action=self.game_rules.legal_action)
self.helper_action = self._action_setup()
save_to_dict(self.res, self.helper_action, "subtype",
lambda x: re.sub("(<class ')|('>)", "", "{}".format(x)))
# print(self.res["subtype"])
self.authorized_keys = self.helper_action().authorized_keys
self.size_act = self.helper_action.size()
def tearDown(self):
self.authorized_keys = {}
def compare_vect(self, pred, true):
return np.max(np.abs(pred - true)) <= self.tolvect
def test_call(self):
action = self.helper_action()
dict_injection, set_status, switch_status, set_topo_vect, switcth_topo_vect, redispatching, shunts = action(
)
def test_compare(self):
action = self.helper_action()
action2 = self.helper_action()
assert action == action2
def test_instanciate_action(self):
"""
test i can instanciate an action without crashing
:return:
"""
action = self.helper_action()
def test_size(self):
action = self.helper_action()
action.size()
def test_proper_size(self):
action = self.helper_action()
assert action.size() == self.size_act
def test_size_action_space(self):
assert self.helper_action.size() == self.size_act
def test_print_notcrash(self):
"""
test the conversion to str does not crash
:return:
"""
action = self.helper_action({})
a = "{}".format(action)
def test_change_p(self):
"""
:return:
"""
self._skipMissingKey('injection')
new_vect = np.random.randn(self.helper_action.n_load)
action = self.helper_action({"injection": {"load_p": new_vect}})
self.compare_vect(action._dict_inj["load_p"], new_vect)
for i in range(self.helper_action.n_load):
assert action.effect_on(load_id=i)["new_p"] == new_vect[i]
def test_change_v(self):
"""
:return:
"""
self._skipMissingKey('injection')
new_vect = np.random.randn(self.helper_action.n_gen)
action = self.helper_action({"injection": {"prod_v": new_vect}})
self.compare_vect(action._dict_inj["prod_v"], new_vect)
for i in range(self.helper_action.n_gen):
assert action.effect_on(gen_id=i)["new_v"] == new_vect[i]
def test_change_p_q(self):
"""
:return:
"""
self._skipMissingKey('injection')
new_vect = np.random.randn(self.helper_action.n_load)
new_vect2 = np.random.randn(self.helper_action.n_load)
action = self.helper_action(
{"injection": {
"load_p": new_vect,
"load_q": new_vect2
}})
assert self.compare_vect(action._dict_inj["load_p"], new_vect)
assert self.compare_vect(action._dict_inj["load_q"], new_vect2)
for i in range(self.helper_action.n_load):
assert action.effect_on(load_id=i)["new_p"] == new_vect[i]
assert action.effect_on(load_id=i)["new_q"] == new_vect2[i]
def test_update_disconnection_1(self):
"""
Test if the disconnection is working properly
:return:
"""
self._skipMissingKey('set_line_status')
for i in range(self.helper_action.n_line):
disco = np.full(shape=self.helper_action.n_line,
fill_value=0,
dtype=np.int)
disco[i] = 1
action = self.helper_action({"set_line_status": disco})
for j in range(self.helper_action.n_line):
assert action.effect_on(line_id=j)["set_line_status"] == disco[
j], "problem with line {} if line {} is disconnected".format(
j, i)
assert action.effect_on(
line_id=j)["change_line_status"] == False
def test_update_disconnection_m1(self):
"""
Test if the disconnection is working properly
:return:
"""
self._skipMissingKey('set_line_status')
for i in range(self.helper_action.n_line):
disco = np.full(shape=self.helper_action.n_line,
fill_value=0,
dtype=np.int)
disco[i] = -1
action = self.helper_action({"set_line_status": disco})
for j in range(self.helper_action.n_line):
assert action.effect_on(line_id=j)["set_line_status"] == disco[
j], "problem with line {} if line {} is disconnected".format(
j, i)
assert action.effect_on(
line_id=j)["change_line_status"] == False
def test_update_hazard(self):
"""
Same test as above, but with hazard
:return:
"""
self._skipMissingKey('hazards')
for i in range(self.helper_action.n_line):
disco = np.full(shape=self.helper_action.n_line,
fill_value=False,
dtype=np.bool)
disco[i] = True
action = self.helper_action({"hazards": disco})
for j in range(self.helper_action.n_line):
expected_res = -1 if j == i else 0
assert action.effect_on(
line_id=j
)["set_line_status"] == expected_res, "problem with line {} if line {} is disconnected".format(
j, i)
assert action.effect_on(
line_id=j)["change_line_status"] == False
def test_update_status(self):
self._skipMissingKey('change_line_status')
for i in range(self.helper_action.n_line):
disco = np.full(shape=self.helper_action.n_line,
fill_value=False,
dtype=np.bool)
disco[i] = True
action = self.helper_action({"change_line_status": disco})
for j in range(self.helper_action.n_line):
expected_res = j == i
assert action.effect_on(line_id=j)["set_line_status"] == 0
assert action.effect_on(
line_id=j)["change_line_status"] == expected_res
def test_update_set_topo_by_dict_obj(self):
self._skipMissingKey('set_bus')
action = self.helper_action({"set_bus": {"loads_id": [(1, 3)]}})
assert action.effect_on(load_id=1)["set_bus"] == 3
assert action.effect_on(load_id=1)["change_bus"] == False
assert action.effect_on(load_id=0)["set_bus"] == 0
assert action.effect_on(load_id=0)["change_bus"] == False
def test_update_set_topo_by_dict_sub(self):
self._skipMissingKey('set_bus')
arr = np.array([1, 1, 1, 2, 2, 2], dtype=np.int)
action = self.helper_action(
{"set_bus": {
"substations_id": [(1, arr)]
}})
assert action.effect_on(line_id=2)["set_bus_or"] == 1
assert action.effect_on(line_id=3)["set_bus_or"] == 1
assert action.effect_on(line_id=4)["set_bus_or"] == 2
assert action.effect_on(line_id=0)["set_bus_ex"] == 1
assert action.effect_on(load_id=0)["set_bus"] == 2
assert action.effect_on(gen_id=1)["set_bus"] == 2
assert action.effect_on(load_id=1)["set_bus"] == 0
assert action.effect_on(gen_id=0)["set_bus"] == 0
def test_update_set_topo_by_dict_sub2(self):
self._skipMissingKey('set_bus')
arr = np.array([1, 1, 1, 2, 2, 2], dtype=np.int)
arr3 = np.array([1, 2, 1, 2, 1, 2], dtype=np.int)
action = self.helper_action(
{"set_bus": {
"substations_id": [(3, arr3), (1, arr)]
}})
assert action.effect_on(line_id=2)["set_bus_or"] == 1
assert action.effect_on(line_id=3)["set_bus_or"] == 1
assert action.effect_on(line_id=4)["set_bus_or"] == 2
assert action.effect_on(line_id=0)["set_bus_ex"] == 1
assert action.effect_on(load_id=0)["set_bus"] == 2
assert action.effect_on(gen_id=1)["set_bus"] == 2
assert action.effect_on(load_id=1)["set_bus"] == 0
assert action.effect_on(gen_id=0)["set_bus"] == 0
def test_update_undo_change_bus(self):
self._skipMissingKey('change_bus')
# Create dummy change_bus action
action = self.helper_action({"change_bus": {"loads_id": [1]}})
# Check it is valid
assert action.effect_on(load_id=0)["set_bus"] == 0
assert action.effect_on(load_id=0)["change_bus"] == False
assert action.effect_on(load_id=1)["set_bus"] == 0
assert action.effect_on(load_id=1)["change_bus"] == True
# Save a copy
action_copy = copy.deepcopy(action)
# Update it
action.update({"change_bus": {"loads_id": [1]}})
# Check it's updated
assert action.effect_on(load_id=0)["set_bus"] == 0
assert action.effect_on(load_id=0)["change_bus"] == False
assert action.effect_on(load_id=1)["set_bus"] == 0
assert action.effect_on(load_id=1)["change_bus"] == False
# Update back to original
action.update({"change_bus": {"loads_id": [1]}})
# Check it's updated
assert action.effect_on(load_id=0)["set_bus"] == 0
assert action.effect_on(load_id=0)["change_bus"] == False
assert action.effect_on(load_id=1)["set_bus"] == 0
assert action.effect_on(load_id=1)["change_bus"] == True
# Check it's equal to original
assert action == action_copy
def test_update_change_bus_by_dict_obj(self):
self._skipMissingKey('change_bus')
action = self.helper_action({"change_bus": {"loads_id": [1]}})
assert action.effect_on(load_id=1)["set_bus"] == 0
assert action.effect_on(load_id=1)["change_bus"] == True
assert action.effect_on(load_id=0)["set_bus"] == 0
assert action.effect_on(load_id=0)["change_bus"] == False
def test_update_change_bus_by_dict_sub(self):
self._skipMissingKey('change_bus')
arr = np.array([True, True, True, False, False, False], dtype=np.bool)
action = self.helper_action(
{"change_bus": {
"substations_id": [(1, arr)]
}})
assert action.effect_on(line_id=2)["change_bus_or"] == True
assert action.effect_on(line_id=3)["change_bus_or"] == True
assert action.effect_on(line_id=4)["change_bus_or"] == False
assert action.effect_on(line_id=0)["change_bus_ex"] == True
assert action.effect_on(load_id=0)["change_bus"] == False
assert action.effect_on(gen_id=1)["change_bus"] == False
assert action.effect_on(load_id=1)["change_bus"] == False
assert action.effect_on(gen_id=0)["change_bus"] == False
def test_update_change_bus_by_dict_sub2(self):
self._skipMissingKey('change_bus')
arr = np.array([True, True, True, False, False, False], dtype=np.bool)
arr3 = np.array([True, False, True, False, True, False], dtype=np.bool)
action = self.helper_action(
{"change_bus": {
"substations_id": [(3, arr3), (1, arr)]
}})
assert action.effect_on(line_id=2)["change_bus_or"] == True
assert action.effect_on(line_id=3)["change_bus_or"] == True
assert action.effect_on(line_id=4)["change_bus_or"] == False
assert action.effect_on(line_id=0)["change_bus_ex"] == True
assert action.effect_on(load_id=0)["change_bus"] == False
assert action.effect_on(gen_id=1)["change_bus"] == False
assert action.effect_on(load_id=1)["change_bus"] == False
assert action.effect_on(gen_id=0)["change_bus"] == False
def test_ambiguity_topo(self):
self._skipMissingKey('change_bus')
action = self.helper_action({"change_bus": {
"lines_or_id": [1]
}}) # i switch the bus of the origin of powerline 1
action.update({"set_bus": {
"lines_or_id": [(1, 1)]
}}) # i set the origin of powerline 1 to bus 1
try:
action()
raise RuntimeError(
"This should hav thrown an InvalidBusStatus error")
except InvalidBusStatus as e:
pass
def test_ambiguity_line_status_when_set_and_change(self):
self._skipMissingKey('set_line_status')
self._skipMissingKey('change_line_status')
arr = np.zeros(self.helper_action.n_line)
arr[1] = -1
action = self.helper_action(
{"set_line_status":
arr}) # i switch set the status of powerline 1 to "disconnected"
action.update({"change_line_status":
[1]}) # i asked to change this status
try:
action()
raise RuntimeError(
"This should hav thrown an InvalidBusStatus error")
except InvalidLineStatus as e:
pass
def test_ambiguity_line_reconnected_without_bus(self):
self._skipMissingKey('set_line_status')
arr = np.zeros(self.helper_action.n_line)
arr[1] = 1
action = self.helper_action(
{"set_line_status":
arr}) # i switch set the status of powerline 1 to "connected"
# and i don't say on which bus to connect it
if issubclass(self.helper_action.actionClass, PowerLineSet):
# this is a legal action for powerlineSet
action()
else:
try:
action()
raise RuntimeError(
"This should have thrown an InvalidBusStatus error for {}"
"".format(self.helper_action.actionClass))
except InvalidLineStatus as e:
pass
def test_set_status_and_setbus_isambiguous(self):
"""
:return:
"""
self._skipMissingKey('set_bus')
arr = np.array([1, 1, 1, 2, 2, 2], dtype=np.int)
id_ = 2
action = self.helper_action(
{"set_bus": {
"substations_id": [(1, arr)]
}})
arr2 = np.zeros(self.helper_action.n_line)
arr2[id_] = -1
action.update({"set_line_status": arr2})
try:
action()
raise RuntimeError(
"This should have thrown an InvalidBusStatus error")
except InvalidLineStatus as e:
pass
def test_hazard_overides_setbus(self):
"""
:return:
"""
self._skipMissingKey('set_bus')
self._skipMissingKey('hazards')
arr = np.array([1, 1, 1, 2, 2, 2], dtype=np.int)
id_ = 2
action = self.helper_action(
{"set_bus": {
"substations_id": [(1, arr)]
}})
assert action.effect_on(
line_id=id_)["set_bus_or"] == 1, "fail for {}".format(
self.helper_action.actionClass)
action.update({"hazards": [id_]})
assert action.effect_on(
line_id=id_)["set_bus_or"] == 0, "fail for {}".format(
self.helper_action.actionClass)
assert action.effect_on(
line_id=id_)["set_line_status"] == -1, "fail for {}".format(
self.helper_action.actionClass)
assert action.effect_on(
line_id=id_)["set_bus_ex"] == 0, "fail for {}".format(
self.helper_action.actionClass)
def test_action_str(self):
self._skipMissingKey('set_bus')
self._skipMissingKey('change_bus')
arr1 = np.array([False, False, False, True, True, True], dtype=np.bool)
arr2 = np.array([1, 1, 2, 2], dtype=np.int)
id_1 = 1
id_2 = 12
action = self.helper_action({
"change_bus": {
"substations_id": [(id_1, arr1)]
},
"set_bus": {
"substations_id": [(id_2, arr2)]
}
})
res = action.__str__()
act_str = 'This action will:\n\t - NOT change anything to the injections\n\t - NOT perform any redispatching ' \
'action\n\t - NOT force any line status\n\t - NOT switch any line status\n\t - Change the bus of the ' \
'following element:\n\t \t - switch bus of line (origin) 4 [on substation 1]\n\t \t - switch bus of ' \
'load 0 [on substation 1]\n\t \t - switch bus of generator 1 [on substation 1]\n\t - Set the bus of ' \
'the following element:\n\t \t - assign bus 1 to line (extremity) 18 [on substation 12]\n\t \t - ' \
'assign bus 1 to line (origin) 19 [on substation 12]\n\t \t - assign bus 2 to load 9 ' \
'[on substation 12]\n\t \t - assign bus 2 to line (extremity) 12 [on substation 12]'
assert res == act_str
def test_to_vect(self):
self._skipMissingKey('set_bus')
arr1 = np.array([False, False, False, True, True, True], dtype=np.bool)
arr2 = np.array([1, 1, 2, 2], dtype=np.int)
id_1 = 1
id_2 = 12
action = self.helper_action({
"change_bus": {
"substations_id": [(id_1, arr1)]
},
"set_bus": {
"substations_id": [(id_2, arr2)]
}
})
res = action.to_vect()
tmp = np.zeros(self.size_act)
# compute the "set_bus" vect
id_set = np.where(
np.array(action.attr_list_vect) == "_set_topo_vect")[0][0]
size_before = 0
for el in action.attr_list_vect[:id_set]:
arr_ = action._get_array_from_attr_name(el)
size_before += arr_.shape[0]
tmp[size_before:(size_before + action.dim_topo)] = np.array([
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 1, 2, 2, 0, 0, 0
])
id_change = np.where(
np.array(action.attr_list_vect) == "_change_bus_vect")[0][0]
size_before = 0
for el in action.attr_list_vect[:id_change]:
arr_ = action._get_array_from_attr_name(el)
size_before += arr_.shape[0]
tmp[size_before:(size_before + action.dim_topo)] = 1.0 * np.array([
False, False, False, False, False, False, True, True, True, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False
])
assert np.all(res[np.isfinite(tmp)] == tmp[np.isfinite(tmp)])
assert np.all(np.isfinite(res) == np.isfinite(tmp))
def test__eq__(self):
self._skipMissingKey('set_bus')
self._skipMissingKey('change_bus')
arr1 = np.array([False, False, False, True, True, True], dtype=np.bool)
arr2 = np.array([1, 1, 2, 2], dtype=np.int)
id_1 = 1
id_2 = 12
action1 = self.helper_action({
"change_bus": {
"substations_id": [(id_1, arr1)]
},
"set_bus": {
"substations_id": [(id_2, arr2)]
}
})
action2 = self.helper_action({
"change_bus": {
"substations_id": [(id_1, arr1)]
},
"set_bus": {
"substations_id": [(id_2, arr2)]
}
})
action3 = self.helper_action()
assert action1 == action2
assert action1 != action3
def test_from_vect(self):
self._skipMissingKey('set_bus')
self._skipMissingKey('change_bus')
arr1 = np.array([False, False, False, True, True, True], dtype=np.bool)
arr2 = np.array([1, 1, 2, 2], dtype=np.int)
id_1 = 1
id_2 = 12
action1 = self.helper_action({
"change_bus": {
"substations_id": [(id_1, arr1)]
},
"set_bus": {
"substations_id": [(id_2, arr2)]
}
})
action2 = self.helper_action({})
vect_act1 = action1.to_vect()
action2.from_vect(vect_act1)
# if i load an action with from_vect it's equal to the original one
assert action1 == action2
vect_act2 = action2.to_vect()
# if i convert it back to a vector, it's equal to the original converted vector
assert np.all(vect_act1[np.isfinite(vect_act2)] == vect_act2[
np.isfinite(vect_act2)])
assert np.all(np.isfinite(vect_act1) == np.isfinite(vect_act2))
def test_call_change_set(self):
self._skipMissingKey('set_bus')
self._skipMissingKey('change_bus')
self._skipMissingKey('set_line_status')
self._skipMissingKey('change_line_status')
self._skipMissingKey('injection')
arr1 = np.array([False, False, False, True, True, True], dtype=np.bool)
arr2 = np.array([1, 1, 2, 2], dtype=np.int)
id_1 = 1
id_2 = 12
new_vect = np.random.randn(self.helper_action.n_load)
new_vect2 = np.random.randn(self.helper_action.n_load)
change_status_orig = np.random.randint(
0, 2, self.helper_action.n_line).astype(np.bool)
set_status_orig = np.random.randint(-1, 2, self.helper_action.n_line)
set_status_orig[change_status_orig] = 0
change_topo_vect_orig = np.random.randint(
0, 2, self.helper_action.dim_topo).astype(np.bool)
# powerline that are set to be reconnected, can't be moved to another bus
change_topo_vect_orig[self.helper_action.line_or_pos_topo_vect[
set_status_orig == 1]] = False
change_topo_vect_orig[self.helper_action.line_ex_pos_topo_vect[
set_status_orig == 1]] = False
# powerline that are disconnected, can't be moved to the other bus
change_topo_vect_orig[self.helper_action.line_or_pos_topo_vect[
set_status_orig == -1]] = False
change_topo_vect_orig[self.helper_action.line_ex_pos_topo_vect[
set_status_orig == -1]] = False
set_topo_vect_orig = np.random.randint(0, 3,
self.helper_action.dim_topo)
set_topo_vect_orig[
change_topo_vect_orig] = 0 # don't both change and set
# I need to make sure powerlines that are reconnected are indeed reconnected to a bus
set_topo_vect_orig[self.helper_action.line_or_pos_topo_vect[
set_status_orig == 1]] = 1
set_topo_vect_orig[self.helper_action.line_ex_pos_topo_vect[
set_status_orig == 1]] = 1
# I need to make sure powerlines that are disconnected are not assigned to a bus
set_topo_vect_orig[self.helper_action.line_or_pos_topo_vect[
set_status_orig == -1]] = 0
set_topo_vect_orig[self.helper_action.line_ex_pos_topo_vect[
set_status_orig == -1]] = 0
action = self.helper_action({
"change_bus": change_topo_vect_orig,
"set_bus": set_topo_vect_orig,
"injection": {
"load_p": new_vect,
"load_q": new_vect2
},
"change_line_status": change_status_orig,
"set_line_status": set_status_orig
})
dict_injection, set_status, change_status, set_topo_vect, switcth_topo_vect, redispatching, shunts = action(
)
assert "load_p" in dict_injection
assert np.all(dict_injection["load_p"] == new_vect)
assert "load_q" in dict_injection
assert np.all(dict_injection["load_q"] == new_vect2)
assert np.all(set_status == set_status_orig)
assert np.all(change_status == change_status_orig)
assert np.all(set_topo_vect == set_topo_vect_orig)
assert np.all(switcth_topo_vect == change_topo_vect_orig)
def test_get_topological_impact(self):
self._skipMissingKey('set_bus')
self._skipMissingKey('change_bus')
self._skipMissingKey('set_line_status')
self._skipMissingKey('change_line_status')
id_1 = 1
id_2 = 12
id_line = 17
id_line2 = 15
arr1 = np.array([False, False, False, True, True, True], dtype=np.bool)
arr2 = np.array([1, 1, 2, 2], dtype=np.int)
arr_line1 = np.full(self.helper_action.n_line,
fill_value=False,
dtype=np.bool)
arr_line1[id_line] = True
arr_line2 = np.full(self.helper_action.n_line,
fill_value=0,
dtype=np.int)
arr_line2[id_line2] = 2
do_nothing = self.helper_action({})
aff_lines, aff_subs = do_nothing.get_topological_impact()
assert np.sum(aff_lines) == 0
assert np.sum(aff_subs) == 0
act_sub1 = self.helper_action(
{"change_bus": {
"substations_id": [(id_1, arr1)]
}})
aff_lines, aff_subs = act_sub1.get_topological_impact()
assert np.sum(aff_lines) == 0
assert np.sum(aff_subs) == 1
assert aff_subs[id_1]
act_sub1_sub12 = self.helper_action({
"change_bus": {
"substations_id": [(id_1, arr1)]
},
"set_bus": {
"substations_id": [(id_2, arr2)]
}
})
aff_lines, aff_subs = act_sub1_sub12.get_topological_impact()
assert np.sum(aff_lines) == 0
assert np.sum(aff_subs) == 2
assert aff_subs[id_1]
assert aff_subs[id_2]
act_sub1_sub12_line1 = self.helper_action({
"change_bus": {
"substations_id": [(id_1, arr1)]
},
"set_bus": {
"substations_id": [(id_2, arr2)]
},
"change_line_status":
arr_line1
})
aff_lines, aff_subs = act_sub1_sub12_line1.get_topological_impact()
assert np.sum(aff_lines) == 1
assert aff_lines[id_line] == 1
assert np.sum(aff_subs) == 2
assert aff_subs[id_1]
assert aff_subs[id_2]
act_sub1_sub12_line1_line2 = self.helper_action({
"change_bus": {
"substations_id": [(id_1, arr1)]
},
"set_bus": {
"substations_id": [(id_2, arr2)]
},
"change_line_status":
arr_line1,
"set_line_status":
arr_line2
})
aff_lines, aff_subs = act_sub1_sub12_line1_line2.get_topological_impact(
)
assert np.sum(aff_lines) == 2
assert aff_lines[id_line] == 1
assert aff_lines[id_line2] == 1
assert np.sum(aff_subs) == 2
assert aff_subs[id_1]
assert aff_subs[id_2]
def test_to_dict(self):
dict_ = self.helper_action.to_dict()
assert dict_ == self.res
def test_from_dict(self):
res = ActionSpace.from_dict(self.res)
assert np.all(res.name_gen == self.helper_action.name_gen)
assert np.all(res.name_load == self.helper_action.name_load)
assert np.all(res.name_line == self.helper_action.name_line)
assert np.all(res.sub_info == self.helper_action.sub_info)
assert np.all(res.load_to_subid == self.helper_action.load_to_subid)
assert np.all(res.gen_to_subid == self.helper_action.gen_to_subid)
assert np.all(
res.line_or_to_subid == self.helper_action.line_or_to_subid)
assert np.all(
res.line_ex_to_subid == self.helper_action.line_ex_to_subid)
assert np.all(
res.load_to_sub_pos == self.helper_action.load_to_sub_pos)
assert np.all(res.gen_to_sub_pos == self.helper_action.gen_to_sub_pos)
assert np.all(
res.line_or_to_sub_pos == self.helper_action.line_or_to_sub_pos)
assert np.all(
res.line_ex_to_sub_pos == self.helper_action.line_ex_to_sub_pos)
assert np.all(
res.load_pos_topo_vect == self.helper_action.load_pos_topo_vect)
assert np.all(
res.gen_pos_topo_vect == self.helper_action.gen_pos_topo_vect)
assert np.all(res.line_or_pos_topo_vect ==
self.helper_action.line_or_pos_topo_vect)
assert np.all(res.line_ex_pos_topo_vect ==
self.helper_action.line_ex_pos_topo_vect)
# pdb.set_trace()
assert np.all(res.actionClass == self.helper_action.actionClass)
def test_json_serializable(self):
dict_ = self.helper_action.to_dict()
res = json.dumps(obj=dict_, indent=4, sort_keys=True)
def test_json_loadable(self):
dict_ = self.helper_action.to_dict()
tmp = json.dumps(obj=dict_, indent=4, sort_keys=True)
res = ActionSpace.from_dict(json.loads(tmp))
assert np.all(res.name_gen == self.helper_action.name_gen)
assert np.all(res.name_load == self.helper_action.name_load)
assert np.all(res.name_line == self.helper_action.name_line)
assert np.all(res.sub_info == self.helper_action.sub_info)
assert np.all(res.load_to_subid == self.helper_action.load_to_subid)
assert np.all(res.gen_to_subid == self.helper_action.gen_to_subid)
assert np.all(
res.line_or_to_subid == self.helper_action.line_or_to_subid)
assert np.all(
res.line_ex_to_subid == self.helper_action.line_ex_to_subid)
assert np.all(
res.load_to_sub_pos == self.helper_action.load_to_sub_pos)
assert np.all(res.gen_to_sub_pos == self.helper_action.gen_to_sub_pos)
assert np.all(
res.line_or_to_sub_pos == self.helper_action.line_or_to_sub_pos)
assert np.all(
res.line_ex_to_sub_pos == self.helper_action.line_ex_to_sub_pos)
assert np.all(
res.load_pos_topo_vect == self.helper_action.load_pos_topo_vect)
assert np.all(
res.gen_pos_topo_vect == self.helper_action.gen_pos_topo_vect)
assert np.all(res.line_or_pos_topo_vect ==
self.helper_action.line_or_pos_topo_vect)
assert np.all(res.line_ex_pos_topo_vect ==
self.helper_action.line_ex_pos_topo_vect)
assert np.all(res.actionClass == self.helper_action.actionClass)
def test_as_dict(self):
act = self.helper_action({})
dict_ = act.as_dict()
assert dict_ == {}
def test_to_from_vect_action(self):
act = self.helper_action({})
vect_ = act.to_vect()
act2 = self.helper_action.from_vect(vect_)
assert act == act2
def test_sum_shape_equal_size(self):
act = self.helper_action({})
assert act.size() == np.sum(act.shape())
def test_shape_correct(self):
act = self.helper_action({})
assert act.shape().shape == act.dtype().shape
def test_redispatching(self):
self._skipMissingKey('redispatch')
act = self.helper_action({"redispatch": [1, 10]})
act = self.helper_action({"redispatch": [(1, 10), (2, 100)]})
act = self.helper_action(
{"redispatch": np.array([10, 20, 30, 40, 50])})
def test_possibility_reconnect_powerlines(self):
self._skipMissingKey('set_line_status')
self._skipMissingKey('set_bus')
self.helper_action.legal_action = DefaultRules()
act = self.helper_action.reconnect_powerline(line_id=1,
bus_or=1,
bus_ex=1)
line_impact, sub_impact = act.get_topological_impact()
assert np.sum(line_impact) == 1
assert np.sum(sub_impact) == 0
act = self.helper_action.reconnect_powerline(line_id=1,
bus_or=1,
bus_ex=1)
act.update({"set_bus": {"generators_id": [(1, 2)]}})
line_impact, sub_impact = act.get_topological_impact()
assert np.sum(line_impact) == 1
assert np.all(sub_impact == [False, True] + [False for _ in range(12)])
act = self.helper_action.reconnect_powerline(line_id=1,
bus_or=1,
bus_ex=1)
act.update({"set_bus": {"generators_id": [(0, 2)]}})
line_impact, sub_impact = act.get_topological_impact()
assert np.sum(line_impact) == 1
assert np.all(sub_impact == [True] + [False for _ in range(13)])
# there were a bug that occurred when updating an action, some vectors were not reset
act = self.helper_action.reconnect_powerline(line_id=1,
bus_or=1,
bus_ex=1)
line_impact, sub_impact = act.get_topological_impact()
assert np.sum(line_impact) == 1
assert np.sum(sub_impact) == 0
act.update({"set_bus": {"generators_id": [(1, 2)]}})
line_impact, sub_impact = act.get_topological_impact()
assert np.sum(line_impact) == 1
assert np.all(sub_impact == [False, True] + [False for _ in range(12)])
def __init__(self,
parameters,
thermal_limit_a=None,
epsilon_poly=1e-2,
tol_poly=1e-6,
other_rewards={}):
GridObjects.__init__(self)
# specific to power system
if not isinstance(parameters, Parameters):
raise Grid2OpException(
"Parameter \"parameters\" used to build the Environment should derived form the "
"grid2op.Parameters class, type provided is \"{}\"".format(
type(parameters)))
self.parameters = parameters
# some timers
self._time_apply_act = 0
self._time_powerflow = 0
self._time_extract_obs = 0
self._time_opponent = 0
# data relative to interpolation
self._epsilon_poly = epsilon_poly
self._tol_poly = tol_poly
# define logger
self.logger = None
# and calendar data
self.time_stamp = None
self.nb_time_step = 0
# observation
self.current_obs = None
# type of power flow to play
# if True, then it will not disconnect lines above their thermal limits
self.no_overflow_disconnection = self.parameters.NO_OVERFLOW_DISCONNECTION
self.timestep_overflow = None
self.nb_timestep_overflow_allowed = None
# store actions "cooldown"
self.times_before_line_status_actionable = None
self.max_timestep_line_status_deactivated = self.parameters.NB_TIMESTEP_LINE_STATUS_REMODIF
self.times_before_topology_actionable = None
self.max_timestep_topology_deactivated = self.parameters.NB_TIMESTEP_TOPOLOGY_REMODIF
# for maintenance operation
self.time_next_maintenance = None
self.duration_next_maintenance = None
# hazard (not used outside of this class, information is given in `time_remaining_before_line_reconnection`
self._hazard_duration = None
# hard overflow part
self.hard_overflow_threshold = self.parameters.HARD_OVERFLOW_THRESHOLD
self.time_remaining_before_line_reconnection = None
self.env_dc = self.parameters.ENV_DC
# redispatching data
self.target_dispatch = None
self.actual_dispatch = None
self.gen_uptime = None
self.gen_downtime = None
self.gen_activeprod_t = None
self._thermal_limit_a = thermal_limit_a
# maintenance / hazards
self.time_next_maintenance = None
self.duration_next_maintenance = None
self.time_remaining_before_reconnection = None
# store environment modifications
self._injection = None
self._maintenance = None
self._hazards = None
self.env_modification = None
# to use the data
self.done = False
self.current_reward = None
self.helper_action_env = None
self.chronics_handler = None
self.game_rules = None
self.helper_action_player = None
self.rewardClass = None
self.actionClass = None
self.observationClass = None
self.legalActClass = None
self.helper_observation = None
self.names_chronics_to_backend = None
self.reward_helper = None
self.reward_range = None, None
# other rewards
self.other_rewards = {}
for k, v in other_rewards.items():
if not issubclass(v, BaseReward):
raise Grid2OpException(
"All keys of \"rewards\" key word argument should be classes that inherit from "
"\"grid2op.BaseReward\"")
self.other_rewards[k] = RewardHelper(v)
# opponent
self.opponent_action_class = DontAct # class of the action of the opponent
self.opponent_class = BaseOpponent # class of the opponent
self.opponent_init_budget = 0
## below initialized by _create_env, above: need to be called
self.opponent_action_space = None # ActionSpace(gridobj=)
self.compute_opp_budg = None # UnlimitedBudget(self.opponent_act_space)
self.opponent = None # OpponentSpace()
self.oppSpace = None
# voltage
self.voltage_controler = None
# backend
self.init_grid_path = None
# specific to Basic Env, do not change
self.backend = None
self.__is_init = False
def __init__(self,
observation_space,
substation_layout=None,
radius_sub=20.,
load_prod_dist=70.,
bus_radius=6.):
if substation_layout is None:
if observation_space.grid_layout is None:
# if no layout is provided, and observation_space has no layout, then it fails
raise PlotError(
"Impossible to use plotting abilities without specifying a layout (coordinates) "
"of the substations.")
# if no layout is provided, use the one in the observation_space
substation_layout = []
for el in observation_space.name_sub:
substation_layout.append(observation_space.grid_layout[el])
if len(substation_layout) != observation_space.n_sub:
raise PlotError(
"You provided a layout with {} elements while there are {} substations on the powergrid. "
"Your layout is invalid".format(len(substation_layout),
observation_space.n_sub))
GridObjects.__init__(self)
self.init_grid(observation_space)
self.observation_space = observation_space
self._layout = {}
self._layout["substations"] = self._get_sub_layout(substation_layout)
self.radius_sub = radius_sub
self.load_prod_dist = load_prod_dist # distance between load and generator to the center of the substation
self.bus_radius = bus_radius
self.subs_elements = [None for _ in self.observation_space.sub_info]
# get the element in each substation
for sub_id in range(self.observation_space.sub_info.shape[0]):
this_sub = {}
objs = self.observation_space.get_obj_connect_to(
substation_id=sub_id)
for c_id in objs["loads_id"]:
c_nm = self._get_load_name(sub_id, c_id)
this_load = {}
this_load["type"] = "load"
this_load["sub_pos"] = self.observation_space.load_to_sub_pos[
c_id]
this_sub[c_nm] = this_load
for g_id in objs["generators_id"]:
g_nm = self._get_gen_name(sub_id, g_id)
this_gen = {}
this_gen["type"] = "gen"
this_gen["sub_pos"] = self.observation_space.gen_to_sub_pos[
g_id]
this_sub[g_nm] = this_gen
for lor_id in objs["lines_or_id"]:
ext_id = self.observation_space.line_ex_to_subid[lor_id]
l_nm = self._get_line_name(sub_id, ext_id, lor_id)
this_line = {}
this_line["type"] = "line"
this_line[
"sub_pos"] = self.observation_space.line_or_to_sub_pos[
lor_id]
this_sub[l_nm] = this_line
for lex_id in objs["lines_ex_id"]:
or_id = self.observation_space.line_or_to_subid[lex_id]
l_nm = self._get_line_name(or_id, sub_id, lex_id)
this_line = {}
this_line["type"] = "line"
this_line[
"sub_pos"] = self.observation_space.line_ex_to_sub_pos[
lex_id]
this_sub[l_nm] = this_line
self.subs_elements[sub_id] = this_sub
self._compute_layout()
def __init__(self,
obs_env=None,
action_helper=None,
seed=None):
GridObjects.__init__(self)
self.action_helper = action_helper
# time stamp information
self.year = 1970
self.month = 0
self.day = 0
self.hour_of_day = 0
self.minute_of_hour = 0
self.day_of_week = 0
# for non deterministic observation that would not use default np.random module
self.seed = None
# handles the forecasts here
self._forecasted_grid_act = {}
self._forecasted_inj = []
self._obs_env = obs_env
self.timestep_overflow = np.zeros(shape=(self.n_line,), dtype=dt_int)
# 0. (line is disconnected) / 1. (line is connected)
self.line_status = np.ones(shape=self.n_line, dtype=dt_bool)
# topological vector
self.topo_vect = np.zeros(shape=self.dim_topo, dtype=dt_int)
# generators information
self.prod_p = np.full(shape=self.n_gen, dtype=dt_float, fill_value=np.NaN)
self.prod_q = 1.0 * self.prod_p
self.prod_v = 1.0 * self.prod_p
# loads information
self.load_p = np.full(shape=self.n_load, dtype=dt_float, fill_value=np.NaN)
self.load_q = 1.0 * self.load_p
self.load_v = 1.0 * self.load_p
# lines origin information
self.p_or = np.full(shape=self.n_line, dtype=dt_float, fill_value=np.NaN)
self.q_or = 1.0 * self.p_or
self.v_or = 1.0 * self.p_or
self.a_or = 1.0 * self.p_or
# lines extremity information
self.p_ex = 1.0 * self.p_or
self.q_ex = 1.0 * self.p_or
self.v_ex = 1.0 * self.p_or
self.a_ex = 1.0 * self.p_or
# lines relative flows
self.rho = 1.0 * self.p_or
# cool down and reconnection time after hard overflow, soft overflow or cascading failure
self.time_before_cooldown_line = np.full(shape=self.n_line, dtype=dt_int, fill_value=-1)
self.time_before_cooldown_sub = np.full(shape=self.n_sub, dtype=dt_int, fill_value=-1)
self.time_next_maintenance = 1 * self.time_before_cooldown_line
self.duration_next_maintenance = 1 * self.time_before_cooldown_line
# calendar data
self.year = dt_int(1970)
self.month = dt_int(0)
self.day = dt_int(0)
self.hour_of_day = dt_int(0)
self.minute_of_hour = dt_int(0)
self.day_of_week = dt_int(0)
# redispatching
self.target_dispatch = 1.0 * self.prod_p
self.actual_dispatch = 1.0 * self.prod_p
# to save some computation time
self._connectivity_matrix_ = None
self._bus_connectivity_matrix_ = None
self._dictionnarized = None
# for shunt (these are not stored!)
if self.shunts_data_available:
self._shunt_p = np.full(shape=self.n_shunt, dtype=dt_float, fill_value=np.NaN)
self._shunt_q = 1.0 * self._shunt_p
self._shunt_v = 1.0 * self._shunt_p
self._shunt_bus = np.full(shape=self.n_shunt, dtype=dt_int, fill_value=1)
def __init__(self, gridobj, obs_env=None, action_helper=None, seed=None):
GridObjects.__init__(self)
self.init_grid(gridobj)
self.action_helper = action_helper
# time stamp information
self.year = 1970
self.month = 0
self.day = 0
self.hour_of_day = 0
self.minute_of_hour = 0
self.day_of_week = 0
# for non deterministic observation that would not use default np.random module
self.seed = None
# handles the forecasts here
self._forecasted_grid = []
self._forecasted_inj = []
self._obs_env = obs_env
self.timestep_overflow = None
# 0. (line is disconnected) / 1. (line is connected)
self.line_status = None
# topological vector
self.topo_vect = None
# generators information
self.prod_p = None
self.prod_q = None
self.prod_v = None
# loads information
self.load_p = None
self.load_q = None
self.load_v = None
# lines origin information
self.p_or = None
self.q_or = None
self.v_or = None
self.a_or = None
# lines extremity information
self.p_ex = None
self.q_ex = None
self.v_ex = None
self.a_ex = None
# lines relative flows
self.rho = None
# cool down and reconnection time after hard overflow, soft overflow or cascading failure
self.time_before_cooldown_line = None
self.time_before_cooldown_sub = None
self.time_before_line_reconnectable = None
self.time_next_maintenance = None
self.duration_next_maintenance = None
# matrices
self.connectivity_matrix_ = None
self.bus_connectivity_matrix_ = None
self.vectorized = None
# redispatching
self.target_dispatch = None
self.actual_dispatch = None
# value to assess if two observations are equal
self._tol_equal = 5e-1
self.attr_list_vect = None
self.reset()
def __init__(
self,
envs_dir,
experimental_read_from_local_dir=False,
_add_to_name="", # internal, for test only, do not use !
_compat_glop_version=None, # internal, for test only, do not use !
_test=False,
**kwargs):
GridObjects.__init__(self)
RandomObject.__init__(self)
self.current_env = None
self.env_index = None
self.mix_envs = []
self._env_dir = os.path.abspath(envs_dir)
# Special case handling for backend
# TODO: with backend.copy() instead !
backendClass = None
if "backend" in kwargs:
backendClass = type(kwargs["backend"])
del kwargs["backend"]
# Inline import to prevent cyclical import
from grid2op.MakeEnv.Make import make
# TODO reuse same observation_space and action_space in all the envs maybe ?
try:
for env_dir in sorted(os.listdir(envs_dir)):
env_path = os.path.join(envs_dir, env_dir)
if not os.path.isdir(env_path):
continue
# Special case for backend
if backendClass is not None:
env = make(env_path,
backend=backendClass(),
_add_to_name=_add_to_name,
_compat_glop_version=_compat_glop_version,
test=_test,
experimental_read_from_local_dir=
experimental_read_from_local_dir,
**kwargs)
else:
env = make(env_path,
_add_to_name=_add_to_name,
_compat_glop_version=_compat_glop_version,
test=_test,
experimental_read_from_local_dir=
experimental_read_from_local_dir,
**kwargs)
self.mix_envs.append(env)
except Exception as exc_:
err_msg = "MultiMix environment creation failed: {}".format(exc_)
raise EnvError(err_msg)
if len(self.mix_envs) == 0:
err_msg = "MultiMix envs_dir did not contain any valid env"
raise EnvError(err_msg)
self.env_index = 0
self.current_env = self.mix_envs[self.env_index]
# Make sure GridObject class attributes are set from first env
# Should be fine since the grid is the same for all envs
multi_env_name = os.path.basename(
os.path.abspath(envs_dir)) + _add_to_name
save_env_name = self.current_env.env_name
self.current_env.env_name = multi_env_name
self.__class__ = self.init_grid(self.current_env)
self.current_env.env_name = save_env_name
