Tight Piecewise Convex Relaxations for Global Optimization of Optimal Power Flow

@article{Lu2018TightPC,
  title={Tight Piecewise Convex Relaxations for Global Optimization of Optimal Power Flow},
  author={Mowen Lu and Harsha Nagarajan and R. Bent and S. Eksioglu and S. Mason},
  journal={2018 Power Systems Computation Conference (PSCC)},
  year={2018},
  pages={1-7}
}
Since the alternating current optimal power flow (ACOPF) problem was introduced in 1962, developing efficient solution algorithms for the problem has been an active field of research. In recent years, there has been increasing interest in convex relaxations-based solution approaches that are often tight in practice. Based on these approaches, we develop tight piecewise convex relaxations with convex-hull representations, an adaptive, multivariate partitioning algorithm with bound tightening… Expand
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