Units: | $ |
Mode: | Input Only |
Multi-band: | False |
Default Value: | 0 |
Validation Rule: | Any Value |
Key Property: | No |
Description: | Price for violating non-anticipativity constraints in scenario-wise decomposition mode |
Generator Generation Non-anticipativity applies to multi-sample simulations with the Stochastic Method "Stochastic" i.e. stochastic optimization using scenario-wise decomposition. It is used to identify the non-anticipative Generation decisions, and can optionally be set in combination with Generation Non-anticipativity Time.
For all stochastic optimization problems, except SDDP, defining the property adds the following constraints to the formulation:
Generation(s,t) = Generation(s+1,t) ∀s < S
where:
s is the sample number
S = Stochastic
Risk Sample Count
The property is commonly used in medium or long-term Rolling Horizon models to ensure that generation decisions do not anticipate future information e.g. hydro inflows. Note that is generally not necessary to define this for the SDDP stochastic algorithm.
Generator | Property | Value | Units |
A | Units | 1 | - |
A | Max Capacity | 200 | MW |
A | Generation Non-anticipativity | -1 | $ |
A | Generation Non-anticipativity Time | 12 | h |
B | Units | 1 | - |
B | Max Capacity | 100 | MW |
B | Generation Non-anticipativity | 10000 | $ |
For the example in Table 1 Generator "A" Generation is a non-anticipative (or first-stage in a two-stage stochastic optimization) decision for the first 12 hours and a recourse (second-stage) decision after that time, whereas Generator "B" is a non-anticipative decision for all periods but with a penalty of $10,000 if the constraint is violated.
See also: