Source code for grid2op.Chronics.handlers.load_q_from_p_handler

# Copyright (c) 2019-2023, RTE (
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at
# SPDX-License-Identifier: MPL-2.0
# This file is part of Grid2Op, Grid2Op a testbed platform to model sequential decision making in power systems.

import numpy as np

from grid2op.Exceptions import (

from grid2op.dtypes import  dt_float
from grid2op.Chronics.handlers.baseHandler import BaseHandler

[docs]class LoadQFromPHandler(BaseHandler): """This handler is specific for "load_q" type of data. You can use it for both "forecast" ("load_q_forecasted") and for environment data ("load_q"). It will generate load_q based on a "q over p" ratio provided as input. Basically, whenever called, it will return (when possible): `load_q = ratio * load_p` .. note:: Its current implementation heavily relies on the fact that when the "load_q" / "load_q_forecasted" handlers are called the "load_p" / "load_p_forecasted" data are already computed and known. """ def __init__(self, array_name="load_q", qp_ratio: float=0.7, max_iter=-1): super().__init__(array_name, max_iter) if isinstance(qp_ratio, np.ndarray): self._qp_ratio = (1.0 * qp_ratio).astype(dt_float) else: self._qp_ratio = dt_float(qp_ratio)
[docs] def done(self): # this is never done as long as there is a "load_p" return False
[docs] def load_next(self, dict_): if "load_p" in dict_ and not "prod_p" in dict_ and not "prod_v" in dict_: if dict_["load_p"] is not None: return self._qp_ratio * dict_["load_p"] return None
[docs] def initialize(self, order_backend_prods, names_chronics_to_backend): # nothing to do for this particular handler pass
[docs] def check_validity(self, backend): if isinstance(self._qp_ratio, np.ndarray): if backend.n_load != self._qp_ratio.shape[0]: raise HandlerError(f"{self.array_name}: qp_ratio should either be a single float " "or a numpy array with as many loads as there are loads on the grid. " f"You provided {self._qp_ratio.shape[0]} ratios but there are " f"{backend.n_load} loads on the grid.")
[docs] def load_next_maintenance(self): raise HandlerError(f"load_next_maintenance {self.array_name}: You should only " "use this class for ENVIRONMENT data, and not for FORECAST data nor MAINTENANCE data. " )
def load_next_hazard(self): raise HandlerError(f"load_next_hazard {self.array_name}: You should only use " "this class for ENVIRONMENT data, and not for FORECAST ")
[docs] def forecast(self, forecast_horizon_id, inj_dict_env, inj_dict_previous_forecast, # eg gen_p_handler if this is set to gen_p_for_handler: env_handler, # list of the 4 env handlers: (load_p_handler, load_q_handler, gen_p_handler, gen_v_handler) env_handlers): return self.load_next(inj_dict_previous_forecast)