rdtools.availability.AvailabilityAnalysis.run

AvailabilityAnalysis.run(low_threshold=None, relative_sizes=None, power_system_limit=None, quantiles=(0.01, 0.99), rollup_period='M')

Run the availability analysis.

Parameters

  • low_threshold (float or pandas.Series, optional) -- An optional threshold used to naively classify subsystems as online. If the threshold is a scalar, it will be used for all subsystems. For subsystems with different capacities, a pandas Series may be passed with index values matching the columns in power_subsystem. Units must match power_subsystem and power_system. If omitted, the limit is calculated for each subsystem independently as 0.001 times the 99th percentile of its power data.

  • relative_sizes (dict or pandas.Series, optional) -- The production capacity of each subsystem, normalized by the mean subsystem capacity. If not specified, it will be estimated from power data.

  • power_system_limit (float or pandas.Series, optional) -- Maximum allowable system power in the same units as the input power timeseries. This parameter is used to account for cases where online subsystems can partially mitigate the loss of an offline subsystem, for example a system with a plant controller and dynamic inverter setpoints. This constraint is only applied to the subsystem loss calculation.

  • quantiles (tuple, default (0.01, 0.99)) -- (lower, upper) quantiles of the error distribution used for the expected energy confidence interval. The lower bound is used to classify outages as either (1) a simple communication interruption with no production loss or (2) a power outage with an associated production loss estimate.

  • rollup_period (pandas.tseries.offsets.DateOffset or alias, default 'M') -- The period on which to roll up losses and calculate availability.