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