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grid2op.Chronics.handlers

Time Series Handlers

1.9.0 This module is new in version 1.9.0

The goal of this module is to allow some fine-grain manipulation over the generation of the "time series" data of the environment.

You might want to first read doc_timeseries to get familiar with what are these time series and how they are used.

With these "handlers" you can generate the data used by the environment independantly for each type. To use this you have to provide :

  • one handler for "load_p"
  • one handler for "load_q"
  • one handler for "prod_p"
  • one handler for "prod_v"
  • (optional) one handler for the "maintenance"
  • (optional) one handler for "load_p_forecasted"
  • (optional) one handler for "load_q_forecasted"
  • (optional) one handler for "prod_p_forecasted"
  • (optional) one handler for "prod_v_forecasted"

Warning

I will not write "with great power comes great ..." (close enough, you got it) but not every handlers are compatible with every others and depending on the options that you set (e.g "chunk_size") you might end up with different results.

If you use handlers you need at least to understand the basics of what you are doing.

Interests of "handlers"

The main interest (at time of writing) of handlers is to be able to use some "approximation" of "multi steps ahead forecasts" in already available environment.

You can do that by using the PerfectForecastHandler or NoisyForecastHandler for "load_p_forecasted", "load_q_forecasted", "prod_p_forecasted" or "prod_v_forecasted".

For example, for the environment l2rpn_wcci_2022 this gives:

import grid2op
from grid2op.Chronics import FromHandlers
from grid2op.Chronics.handlers import PerfectForecastHandler, CSVHandler, DoNothingHandler
env_name = "l2rpn_wcci_2022"
forecasts_horizons = [5, 10, 15, 20, 25, 30]

env = grid2op.make(env_name,
                   data_feeding_kwargs={"gridvalueClass": FromHandlers,
                                        "gen_p_handler": CSVHandler("prod_p"),
                                        "load_p_handler": CSVHandler("load_p"),
                                        "gen_v_handler": DoNothingHandler("prod_v"),
                                        "load_q_handler": CSVHandler("load_q"),
                                        "h_forecast": forecasts_horizons,
                                        "gen_p_for_handler": PerfectForecastHandler("prod_p_forecasted"),
                                        "load_p_for_handler": PerfectForecastHandler("load_p_forecasted"),
                                        "load_q_for_handler": PerfectForecastHandler("load_q_forecasted"),
                                       }
                  )

obs = env.reset()

# all works
obs.simulate(env.action_space(), 1)
obs.simulate(env.action_space(), 2)
obs.simulate(env.action_space(), 6)

sim_obs1, *_ = obs.simulate(env.action_space())
sim_obs2, *_ = sim_obs1.simulate(env.action_space())
sim_obs3, *_ = sim_obs2.simulate(env.action_space())

# and even this
f_env = obs.get_forecast_env()
obs = f_env.reset()
obs.max_step == 7  # initial state + 6 steps ahead forecast

This was not possible with the intial environment (and its default data_feeding_kwargs)

Note

Above, the forecast are "perfect" meaning the agent sees what will be the exact load and geenration a few hours in advance. If you want to add some noise, you can use the NoisyForecastHandler

Standard data generation and equivalent handlers

For each type of data generation, you can use "handler" to retrieve the same results. It has little interest to make the handlers if you want to get the default behaviour of course (more verbose and slower) but it might allow to use different data (for example removing the maintenance, or increasing the forecast horizons etc.)

  • grid2op.Chronics.ChangeNothing:
    • "load_p_handler" : DoNothingHandler
    • "load_q_handler" : DoNothingHandler
    • "gen_p_handler" : DoNothingHandler
    • "gen_v_handler" : DoNothingHandler
  • grid2op.Chronics.GridStateFromFile:
    • "load_p_handler" : CSVHandler
    • "load_q_handler" : CSVHandler
    • "gen_p_handler" : CSVHandler
    • "gen_v_handler" : CSVHandler
    • "maintenance_handler" : CSVMaintenanceHandler
  • grid2op.Chronics.GridStateFromFileWithForecasts:
    • "load_p_handler" : CSVHandler
    • "load_q_handler" : CSVHandler
    • "gen_p_handler" : CSVHandler
    • "gen_v_handler" : CSVHandler
    • "maintenance_handler" : CSVMaintenanceHandler
    • "load_p_for_handler" : CSVForecastHandler
    • "load_q_for_handler" : CSVForecastHandler
    • "gen_p_for_handler" : CSVForecastHandler
    • "gen_v_for_handler" : CSVForecastHandler
  • grid2op.Chronics.GridStateFromFileWithForecastsWithMaintenance:
    • "load_p_handler" : CSVHandler
    • "load_q_handler" : CSVHandler
    • "gen_p_handler" : CSVHandler
    • "gen_v_handler" : CSVHandler
    • "maintenance_handler" : JSONMaintenanceHandler
    • "load_p_for_handler" : CSVForecastHandler
    • "load_q_for_handler" : CSVForecastHandler
    • "gen_p_for_handler" : CSVForecastHandler
    • "gen_v_for_handler" : CSVForecastHandler
  • grid2op.Chronics.GridStateFromFileWithForecastsWithoutMaintenance:
    • "load_p_handler" : CSVHandler
    • "load_q_handler" : CSVHandler
    • "gen_p_handler" : CSVHandler
    • "gen_v_handler" : CSVHandler
    • "maintenance_handler" : DoNothingHandler (or more simply None)
    • "load_p_for_handler" : CSVForecastHandler
    • "load_q_for_handler" : CSVForecastHandler
    • "gen_p_for_handler" : CSVForecastHandler
    • "gen_v_for_handler" : CSVForecastHandler

For example instead of having (imports are removed for clarity):

env = grid2op.make(env_name, 
                   data_feeding_kwargs={"gridvalueClass": GridStateFromFileWithForecasts,}
                  )

You can write, to have similar results:

env = grid2op.make(env_name, 
                   data_feeding_kwargs={"gridvalueClass": FromHandlers,
                                        "gen_p_handler": CSVHandler("prod_p"),
                                        "load_p_handler": CSVHandler("load_p"),
                                        "gen_v_handler": CSVHandler("prod_v"),
                                        "load_q_handler": CSVHandler("load_q"),
                                        "maintenance_handler": CSVMaintenanceHandler(),
                                        "gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
                                        "load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
                                        "load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
                                       }
)

Warning

The behaviour is not exactly the same between the "GridStateFromFileXXX" and the "FromHandlers" especially in the case of stochastic maintenance (grid2op.Chronics.GridStateFromFileWithForecastsWithMaintenance). Indeed when you call env.seed(XXX) the maintenance generated by GridStateFromFileWithForecastsWithMaintenance will not be the same as the one generated by JSONMaintenanceHandler (because the underlying pseudo random number generator) will not be seeded the same way.

Use with standard environments

In this section we write the "handlers" version you can use to reproduce the behaviour of some grid2op environments.

l2rpn_case14_sandbox

The setting for the "l2rpn_case14_sandbox" is:

import grid2op
from grid2op.Chronics import FromHandlers
from grid2op.Chronics.handlers import CSVHandler, CSVForecastHandler

env_name = "l2rpn_case14_sandbox"
env = grid2op.make(env_name, 
                    data_feeding_kwargs={"gridvalueClass": FromHandlers,
                                        "gen_p_handler": CSVHandler("prod_p"),
                                        "load_p_handler": CSVHandler("load_p"),
                                        "gen_v_handler": CSVHandler("prod_v"),
                                        "load_q_handler": CSVHandler("load_q"),
                                        "gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
                                        "load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
                                        "load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
                                        }
                    )
obs = env.reset()
# continue like you would normally ...

You can now tweak it to add more forecast or add / remove some maintenance by modifying the XXX_for_handler or by adding the maintenance_handler for example.

l2rpn_wcci_2022

The setting for the "l2rpn_wcci_2022" is:

import grid2op
from grid2op.Chronics import FromHandlers
from grid2op.Chronics.handlers import CSVHandler, JSONMaintenanceHandler, CSVForecastHandler, DoNothingHandler

env_name = "l2rpn_wcci_2022"
env = grid2op.make(env_name, 
                    data_feeding_kwargs={"gridvalueClass": FromHandlers,
                                        "gen_p_handler": CSVHandler("prod_p"),
                                        "load_p_handler": CSVHandler("load_p"),
                                        "gen_v_handler": DoNothingHandler("prod_v"),
                                        "load_q_handler": CSVHandler("load_q"),
                                        "maintenance_handler": JSONMaintenanceHandler(),
                                        "gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
                                        "load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
                                        "load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
                                        }
                    )
obs = env.reset()
# continue like you would normally ...

You can now tweak it to add more forecast or add / remove some maintenance by modifying the XXX_for_handler or by removing the maintenance_handler for example.

l2rpn_icaps_2021

The setting for the "l2rpn_icaps_2021" is:

import grid2op
from grid2op.Chronics import FromHandlers
from grid2op.Chronics.handlers import CSVHandler, JSONMaintenanceHandler, CSVForecastHandler

env_name = "l2rpn_icaps_2021_small"  # or "l2rpn_icaps_2021_large"
env = grid2op.make(env_name, 
                    data_feeding_kwargs={"gridvalueClass": FromHandlers,
                                        "gen_p_handler": CSVHandler("prod_p"),
                                        "load_p_handler": CSVHandler("load_p"),
                                        "gen_v_handler": CSVHandler("prod_v"),
                                        "load_q_handler": CSVHandler("load_q"),
                                        "maintenance_handler": JSONMaintenanceHandler(),
                                        "gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
                                        "load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
                                        "load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
                                        }
                    )
obs = env.reset()
# continue like you would normally ...

You can now tweak it to add more forecast or add / remove some maintenance by modifying the XXX_for_handler or by removing the maintenance_handler for example.

l2rpn_neurips_2020_track1

The setting for the "l2rpn_neurips_2020_track1" is:

import grid2op
from grid2op.Chronics import FromHandlers
from grid2op.Chronics.handlers import CSVHandler, JSONMaintenanceHandler, CSVForecastHandler

env_name = "l2rpn_neurips_2020_track1_small"  # or "l2rpn_neurips_2020_track1_large"
env = grid2op.make(env_name, 
                    data_feeding_kwargs={"gridvalueClass": FromHandlers,
                                        "gen_p_handler": CSVHandler("prod_p"),
                                        "load_p_handler": CSVHandler("load_p"),
                                        "gen_v_handler": CSVHandler("prod_v"),
                                        "load_q_handler": CSVHandler("load_q"),
                                        "maintenance_handler": JSONMaintenanceHandler(),
                                        "gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
                                        "load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
                                        "load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
                                        }
                    )
obs = env.reset()
# continue like you would normally ...

You can now tweak it to add more forecast or add / remove some maintenance by modifying the XXX_for_handler or by removing the maintenance_handler for example.

l2rpn_neurips_2020_track1

The setting for the "l2rpn_neurips_2020_track2" is:

import grid2op
from grid2op.Chronics import FromHandlers
from grid2op.Chronics.handlers import CSVHandler, JSONMaintenanceHandler, CSVForecastHandler

env_name = "l2rpn_neurips_2020_track2_small"  # or "l2rpn_neurips_2020_track2_large"
env = grid2op.make(env_name, 
                    data_feeding_kwargs={"gridvalueClass": FromHandlers,
                                        "gen_p_handler": CSVHandler("prod_p"),
                                        "load_p_handler": CSVHandler("load_p"),
                                        "gen_v_handler": CSVHandler("prod_v"),
                                        "load_q_handler": CSVHandler("load_q"),
                                        "maintenance_handler": JSONMaintenanceHandler(),
                                        "gen_p_for_handler": CSVForecastHandler("prod_p_forecasted"),
                                        "load_p_for_handler": CSVForecastHandler("load_p_forecasted"),
                                        "load_q_for_handler": CSVForecastHandler("load_q_forecasted"),
                                        }
                    )
obs = env.reset()
# continue like you would normally ...

You can now tweak it to add more forecast or add / remove some maintenance by modifying the XXX_for_handler or by removing the maintenance_handler for example.

Detailed Documentation by class

grid2op.Chronics.handlers