Distributed Optimal Power Flow Algorithms Over Time-Varying Communication Networks

TL;DR

This paper introduces distributed algorithms for optimal power flow in distribution systems that operate over time-varying networks, achieving geometric convergence and solving SOCP relaxations.

Contribution

The paper presents novel distributed algorithms capable of handling time-varying communication networks for solving the OPF problem with proven convergence rates.

Findings

Algorithms achieve geometric convergence.

Effective in solving SOCP relaxations.

Supported by numerical simulations.

Abstract

In this paper, we consider the problem of optimally coordinating the response of a group of distributed energy resources (DERs) in distribution systems by solving the so-called optimal power flow (OPF) problem. The OPF problem is concerned with determining an optimal operating point, at which some cost function, e.g., generation cost or power losses, is minimized, and operational constraints are satisfied. To solve the OPF problem, we propose distributed algorithms that are able to operate over time-varying communication networks and have geometric convergence rate. We solve the second-order cone program (SOCP) relaxation of the OPF problem for radial distribution systems, which is formulated using the so-called DistFlow model. Theoretical results are further supported by the numerical simulations.