ST Schedule Stochastic Method

Units:	-
Default Value:	1
Validation Rule:	In (0,1,2,3)
Description:	Stochastic optimization method for ST Schedule
Detail:

ST Schedule Stochastic Method sets the method used in ST Schedule to resolve multi-sample data (defined by Variable objects), where the number of samples is set by the Stochastic Risk Sample Count. The attribute can take the following values:

Deterministic (value = 0): The expected value is used for sample data. For variables using endogenous sampling this means that the Profile value is used, and for variables that read their sample values from multi-band input, the first band is used (the assumption is that the first band is the expected value).
Sequential Monte Carlo (value = 1): ST Schedule runs S times, one time for each sample, choosing the appropriate values for each. This yields S complete unit commitment and dispatch solutions.
Parallel Monte Carlo (value = 3): As above but the independent samples are executed in parallel i.e. all samples are executed at the same time on separate threads.
Stochastic (value = 2): ST Schedule runs a single optimization incorporating all S samples into a two-stage stochastic optimization, and yielding a single optimal set of unit commitment decisions and S dispatch solutions. See the Generator Unit Commitment Non-anticipativity topic for details.