This paper proposes a reformulation of the scenario-based two-stage unitcommitment problem under uncertainty that allows finding unit-commitment plansthat perform reasonably well both in expectation and for the worst caserealization of the uncertainties. The proposed reformulation is based onpartitioning the sample space of the uncertain factors by clustering thescenarios that approximate their probability distributions. It is, furthermore,very amenable to decomposition and parallelization using acolumn-and-constraint generation procedure.
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- Stochastic and robust unit commitment
- Columnand- constraint generation
- Parallel computing
- Scenario reduction