efficiency_tracking

efficiency_tracking

EnergyEfficiencyEvents

EnergyEfficiencyEvents(
    dataframe: DataFrame,
    *,
    event_uuid: str = "energy:efficiency",
    time_column: str = "systime"
)

Bases: Base

Energy: Efficiency Tracking

Track energy efficiency metrics against production and machine state.

Methods: - efficiency_trend: Rolling efficiency metric over time. - idle_energy_waste: Detect energy consumption during idle periods. - specific_energy_consumption: Energy per unit output trend. - efficiency_comparison: Compare efficiency across shifts or periods.

efficiency_trend

efficiency_trend(
    meter_uuid: str,
    counter_uuid: str,
    *,
    energy_column: str = "value_double",
    counter_column: str = "value_integer",
    window: str = "1h",
    trend_window: int = 24
) -> pd.DataFrame

Rolling energy efficiency trend (units produced per kWh).

Parameters:

Name	Type	Description	Default
meter_uuid	str	UUID of the energy meter signal.	required
counter_uuid	str	UUID of the production counter signal.	required
energy_column	str	Column with energy readings.	'value_double'
counter_column	str	Column with counter readings.	'value_integer'
window	str	Time window for aggregation.	'1h'
trend_window	int	Number of windows for rolling average.	24

Returns:

Name	Type	Description
DataFrame	DataFrame	window_start, uuid, source_uuid, is_delta, energy, units, efficiency, rolling_avg_efficiency, trend_direction

idle_energy_waste

idle_energy_waste(
    meter_uuid: str,
    state_uuid: str,
    *,
    energy_column: str = "value_double",
    state_column: str = "value_bool",
    window: str = "15min",
    idle_threshold: float = 0.0
) -> pd.DataFrame

Detect energy consumed during idle periods (waste).

Compares energy consumption with machine run/idle state to find windows where the machine is idle but still consuming energy.

Parameters:

Name	Type	Description	Default
meter_uuid	str	UUID of the energy meter signal.	required
state_uuid	str	UUID of the boolean machine state signal (True=run).	required
energy_column	str	Column with energy readings.	'value_double'
state_column	str	Column with boolean state.	'value_bool'
window	str	Time window for analysis.	'15min'
idle_threshold	float	Energy above this during idle is waste.	0.0

Returns:

Name	Type	Description
DataFrame	DataFrame	window_start, uuid, source_uuid, is_delta, energy_consumed, machine_running_pct, is_idle_waste, waste_energy

specific_energy_consumption

specific_energy_consumption(
    meter_uuid: str,
    counter_uuid: str,
    *,
    energy_column: str = "value_double",
    counter_column: str = "value_integer",
    window: str = "1D"
) -> pd.DataFrame

Daily/periodic specific energy consumption (SEC = energy / output).

Lower SEC indicates better efficiency.

Parameters:

Name	Type	Description	Default
meter_uuid	str	UUID of the energy meter signal.	required
counter_uuid	str	UUID of the production counter.	required
energy_column	str	Column with energy readings.	'value_double'
counter_column	str	Column with counter readings.	'value_integer'
window	str	Time window (default daily).	'1D'

Returns:

Name	Type	Description
DataFrame	DataFrame	window_start, uuid, source_uuid, is_delta, total_energy, total_output, sec, sec_trend

efficiency_comparison

efficiency_comparison(
    meter_uuid: str,
    counter_uuid: str,
    *,
    energy_column: str = "value_double",
    counter_column: str = "value_integer",
    shift_definitions: Optional[Dict[str, tuple]] = None
) -> pd.DataFrame

Compare energy efficiency across shifts.

Parameters:

Name	Type	Description	Default
meter_uuid	str	UUID of the energy meter signal.	required
counter_uuid	str	UUID of the production counter.	required
energy_column	str	Column with energy readings.	'value_double'
counter_column	str	Column with counter readings.	'value_integer'
shift_definitions	Optional[Dict[str, tuple]]	Dict mapping shift name to (start_time, end_time) strings. Default: 3-shift operation.	None

Returns:

Name	Type	Description
DataFrame	DataFrame	shift, avg_energy, avg_output, avg_efficiency, total_energy, total_output