AC Optimal Power Flow: a strengthened SDP relaxation and an iterative MILP scheme for global optimization

Antoine Oustry (1, 2)

1 LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
2 ENPC - École des Ponts ParisTech

We address the issue of computing a global minimizer of the AC Optimal Power Flow problem. We introduce valid inequalities to strengthen the Semidefinite Programming relaxation, yielding a novel Conic Programming relaxation. Leveraging these Conic Programming constraints, we dynamically generate Mixed-Integer Linear Programming (MILP) relaxations, whose solutions asymptotically converge to global minimizers of the AC Optimal Power Flow problem. We apply this iterative MILP scheme on the IEEE PES PGLib benchmark and compare the results with two recent Global Optimization approaches.

Mots clés: ACOPF; semidefinite programming; mixed; integer linear programming

Domaines: Recherche opérationnelle [math.OC]; Combinatoire [math.CO]

Antoine Oustry. AC Optimal Power Flow: a strengthened SDP relaxation and an iterative MILP scheme for global optimization. Open Journal of Mathematical Optimization, 2022, 3 (6), pp.19. ⟨10.5802/ojmo.17⟩. ⟨hal-03595227v2⟩