edisgo.flex_opt.charging_strategies
¶
Module Contents¶
Functions¶
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Applies charging strategy to set EV charging time series at charging parks. |
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Harmonizes the charging processes to prevent differences in the energy |
- edisgo.flex_opt.charging_strategies.charging_strategy(edisgo_obj: edisgo.EDisGo, strategy: str = 'dumb', timestamp_share_threshold: numbers.Number = 0.2, minimum_charging_capacity_factor: numbers.Number = 0.1)[source]¶
Applies charging strategy to set EV charging time series at charging parks.
See
apply_charging_strategy
for more information.- Parameters
edisgo_obj (
EDisGo
) –strategy (str) – Defines the charging strategy to apply. See strategy parameter
apply_charging_strategy
for more information. Default: ‘dumb’.timestamp_share_threshold (float) – Percental threshold of the time required at a time step for charging the vehicle. See timestamp_share_threshold parameter
apply_charging_strategy
for more information. Default: 0.2.minimum_charging_capacity_factor (float) – Technical minimum charging power of charging points in p.u. used in case of charging strategy ‘reduced’. See minimum_charging_capacity_factor parameter
apply_charging_strategy
for more information. Default: 0.1.
- edisgo.flex_opt.charging_strategies.harmonize_charging_processes_df(df, edisgo_obj, len_ts, timestamp_share_threshold, strategy=None, minimum_charging_capacity_factor=0.1, eta_cp=1.0)[source]¶
Harmonizes the charging processes to prevent differences in the energy demand per charging strategy.
- Parameters
df (pandas.DataFrame) – Charging processes DataFrame.
len_ts (int) – Length of the timeseries.
timestamp_share_threshold (float) – See description in
charging_strategy()
.strategy (str) – See description in
charging_strategy()
.minimum_charging_capacity_factor (float) – See description in
charging_strategy()
. Default: 0.1.eta_cp (float) – Charging point efficiency. Default: 1.0.