Answers are grounded in this paper and cite their sources.
This letter introduces a deterministic global optimization methods for unit commitment (UC) problem based on outer approximation method (OAM). The proposed Multi-cuts OAM (MCs-OAM) decomposes the UC problem into a mixed integer linear programming (MILP) master problem and several nonlinear programming (NLP) subproblems, whereas only one NLP in classic OAM. After elaborately designing the terminating criterion for solving the bigger but tighter MILP master problems, MCs-OAM can obtained higher quality solutions with fewer main iterations and less total CPU times, although solving more NLPs consumes more CPU times than OAM. The numerical results on 42 test systems of up to 200 units show that the MCs-OAM is very promising for large scale UC problems because that it can obtain high-quality solutions in reasonable time.
No takes yet. Share an insight, caveat, or question.
Yang et al. (2016) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: