| Units: | - |
| Default Value: | 0 |
| Validation Rule: | In (0,1,2,3) |
| Description: | Stochastic optimization method for LT Plan |
LT Plan Stochastic Method sets the algorithm used in LT Plan 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)
- LT Plan runs S times, one time for each sample, choosing the appropriate values for each. This yields S complete capacity expansion and production solutions. These independent samples are executed in sequence.
- 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)
- LT Plan runs a single optimization incorporating all S samples into a stochastic optimization. If a scenario tree is defined, via the Global settings, a multi-stage stochastic optimization is performed e.g. to optimize the expansion solution with respect to uncertainty in hydro inflows (see Storage Trajectory Non-anticipativity ). In the absence of a scenario tree, a two-stage stochastic optimization is performed yielding a single optimal set of capacity expansion decisions and S production solutions.
See also: