On the Tightness of the Lagrangian Dual Bound for Alternating Current Optimal Power Flow


Abstract:

We study tightness properties of a Lagrangian dual (LD) bound for the nonconvex alternating current optimal power flow (ACOPF) problem. We show that the LD bound that can be computed in a parallel, decentralized manner. The proposed approach partitions the network into a set of subnetworks, dualizes the coupling constraints (giving the LD function), and maximizes the LD function with respect to the dual variables of the coupling constraints (giving the desired LD bound). The dual variables that maximize the LD are obtained by using a proximal bundle method. We show that the bound is less tight than the popular semidefinite programming relaxation but is as tight as the second-order cone programming relaxation. We demonstrate our developments using PGLib-OPF test instances.

Año de publicación:

2022

Keywords:

  • alternating current optimal power flow
  • Distributed Optimization
  • Lagrangian duality

Fuente:

scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Energía
  • Optimización matemática

Áreas temáticas:

  • Física aplicada