/
config.py
51 lines (50 loc) · 2.7 KB
/
config.py
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from grid2op.Action import PlayableAction, PowerlineSetAction
from grid2op.Reward import AlarmReward
from grid2op.Rules import DefaultRules
from grid2op.Chronics import Multifolder
from grid2op.Chronics import GridStateFromFileWithForecasts
from grid2op.Backend import PandaPowerBackend
from grid2op.Opponent import WeightedRandomOpponent, BaseActionBudget
from grid2op.operator_attention import LinearAttentionBudget
lines_attacked = ["62_58_180", "62_63_160", "48_50_136", "48_53_141", "41_48_131", "39_41_121",
"43_44_125", "44_45_126", "34_35_110", "54_58_154"]
rho_normalization = [0.45, 0.45, 0.6, 0.35, 0.3, 0.2,
0.55, 0.3, 0.45, 0.55]
opponent_attack_cooldown = 12*24 # 24 hours, 1 hour being 12 time steps
opponent_attack_duration = 12*4 # 4 hours
opponent_budget_per_ts = 0.16667 # opponent_attack_duration / opponent_attack_cooldown + epsilon
opponent_init_budget = 144. # no need to attack straightfully, it can attack starting at midday the first day
config = {
"backend": PandaPowerBackend,
"action_class": PlayableAction,
"observation_class": None,
"reward_class": AlarmReward,
"gamerules_class": DefaultRules,
"chronics_class": Multifolder,
"grid_value_class": GridStateFromFileWithForecasts,
"volagecontroler_class": None,
"names_chronics_to_grid": None,
"thermal_limits": [60.9, 231.9, 272.6, 212.8, 749.2, 332.4, 348., 414.4, 310.1,
371.4, 401.2, 124.3, 298.5, 86.4, 213.9, 160.8, 112.2, 291.4,
489., 489., 124.6, 196.7, 191.9, 238.4, 174.2, 105.6, 143.7,
293.4, 288.9, 107.7, 415.5, 148.2, 124.2, 154.4, 85.9, 106.5,
142., 124., 130.2, 86.2, 278.1, 182., 592.1, 173.1, 249.8,
441., 344.2, 722.8, 494.6, 494.6, 196.7, 151.8, 263.4, 364.1,
327., 370.5, 441., 300.3, 656.2],
"opponent_attack_cooldown": opponent_attack_cooldown,
"opponent_attack_duration": opponent_attack_duration,
"opponent_budget_per_ts": opponent_budget_per_ts,
"opponent_init_budget": opponent_init_budget,
"opponent_action_class": PowerlineSetAction,
"opponent_class": WeightedRandomOpponent,
"opponent_budget_class": BaseActionBudget,
'kwargs_opponent': {"lines_attacked": lines_attacked,
"rho_normalization": rho_normalization,
"attack_period": opponent_attack_cooldown},
"has_attention_budget": True,
"attention_budget_class": LinearAttentionBudget,
"kwargs_attention_budget": {"max_budget": 5.,
"budget_per_ts": 1. / (12.*8),
"alarm_cost": 1.,
"init_budget": 3.}
}