cobre-sddp

Stochastic Dual Dynamic Programming (SDDP) algorithm for the Cobre power systems ecosystem.

Implements the SDDP algorithm (Pereira & Pinto, 1991) for long-term hydrothermal dispatch and energy planning. The crate covers the full solve cycle: forward pass scenario simulation, backward pass Benders cut generation, cut management with cut selection (Level-1, LML1, and dominated-cut pruning), CVaR risk measures, convergence monitoring, policy warm-start and resume from checkpoint, and annual discount rate support. Designed for hybrid MPI + thread-level parallelism via ferrompi.

When to Use

Use cobre-sddp when you need programmatic access to the SDDP algorithm — embedding it in a custom orchestration layer, running parameter sweeps, or integrating the solver into a larger application. For single-study command-line use, prefer cobre-cli, which wraps this crate.

Key Types

• TrainingConfig — algorithm parameters: iteration budget, forward scenario count, checkpoint cadence, warm-start cut count, and cut selection strategy
• TrainingContext — runtime state shared across all iterations of the training loop (cut pools, workspaces, convergence monitor)
• CutPool — pre-allocated storage for Benders cuts with active/inactive bookkeeping
• CutSelectionStrategy — enum controlling cut pool pruning: Level1 (activity threshold), Lml1 (memory window), and Dominated (geometric dominance at visited states)
• SimulationConfig — parameters for the post-training simulation run
• ConvergenceMonitor — tracks lower bound, statistical upper bound, and gap closure across iterations

Links

Status

Alpha — API is functional but not yet stable. See the main repository for the current release.

License

Apache-2.0