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Upgrade to version 1.7.0 #309
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Few byg fixes for the gym_compat module
Few bug fixes
Some improvments, mainly for gym_compat
Improvment of gym compat module
…eavy curtailment is performed
…ching easier [skip ci]
Merge recent developments
Retrieve new developments
fix a bug when limiting the action automatically in the env
Fix an issue with the new parameters to limit the action
New redisp routine, fix notebooks with up to date information
Final notebook modifications before release + different redispatching starting point
This was
linked to
issues
Apr 29, 2022
This was
linked to
issues
Apr 29, 2022
Fix the "env.generate_classes()" function
Fix "env.generate_classes()" and add basic tests for this function
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This release introduces some new functionalities, such as the compatibility to generate data "on the fly" or add more data to an environment.
It also adds some useful features for the curtailment and storage units (some new attributes of the observation) and a first version of the environment used for l2rpn WCCI 2022 competition.
Python 3.6 support has been dropped.
Breaking changes
L2RPNSandBoxScore
,RedispReward
andEconomicReward
now properly computes the cost of the grid(there was an error between the conversion from MWh - cost is given in $ / MWh - and MW). This impacts also
ScoreICAPS2021
andScoreL2RPN2020
.for dimension the number of dispatchable generators (as opposed to all generators
before) this was mandatory to fix issue Bug in the "BoxGymActSpace" when curtailment is allowed #282
case of gym compatibility has also been adjusted to be consistent with curtailment.
Before it has the size of
env.n_gen
nownp.sum(env.gen_redispatchable)
._ObsEnv
module toEnvironment
(was before inObservation
).curtailment_limit_effective
in the observation converted to gym. This changesthe sizes of the gym observation.
Fixed issues
backend.update_from_obs
when there are shunts on the grid forPandapowerBackend
MultifolderWithCache
andRunner
(see issue MultifolderWithCache does not work well with Runner #285)env.train_val_split_random
where sometimes some wrong chronicsname were sampled.
max
value of the observation space is now 1.3 * pmax to account for the slack bus (it was1.01 of pmax before and was not sufficient in some cases)
env.step(...)
(previously it was only a string) when redispatching was illegal.
env.train_val_split_random
when some non chronics files where present in the"chronics" folder of the environment.
was not and in some others it did not detect when it while it was infeasible. This was mainly the case
when curtailment and storage units were heavily modified.
FromNPY
chronixcs even if the "chronics" folder is absent.max_iter
andRunner
in case of max_iter being larger than the number of steps in theenvironment and
nb_episode
>= 2.were not taken into account in the hash).
obs.as_dict()
method.New features
normalize_attr
allowing to easily scale some data for theBoxGymObsSpace
andBoxGymActSpace
self.infos
for the BaseEnv that contains the "info" return value ofenv.step(...)
GymEnv
(the default behavior is now to shuffle them)obs.gen_margin_up
andobs.gen_margin_down
make(...)
command(see
act.limit_curtail_storage(...)
)a single environment)
l2rpn_wcci_2022
environment.in the action space (see
act_space.get_all_unitary_line_set_simple()
)Improvements
env_path
andgrid_path
in environments.PandaPowerBackend
every controllable turned-on generators to mitigate it. This should increase the possibility to act on the
curtailment and storage units without "breaking" the environment.
defined in the "conf.py" file (to make possible the use of different
grid2op version transparently)
change even if you don't apply any, for no obvious reasons. This has been addressed, though it's not perfect.