A Case for Nonconvex Distributed Optimization in Large-Scale Power Systems

Distributed optimization for solving nonconvex optimal power flow (OPF) problems in power systems has attracted considerable attention in the last decade. Most studies are based on the geographical decomposition of the IEEE test systems for verifying the feasibility of the proposed approaches. However, it is not clear if one can extrapolate from these studies that similar approaches can also be applied to very large-scale real-world systems. In this paper, we show, for the first time, that distributed optimization can be effectively applied to a large-scale real transmission network, namely, the Polish 2383-bus system for which no predefined partitions exist, by using a recently developed partitioning technique. More specifically, the problem solved is the ac OPF problem with geographical decomposition of the network using the alternating direction method of multipliers (ADMM) method in conjunction with the partitioning technique. Through extensive simulations and analytical studies, we show that with the presented partitioning technique the convergence performance of the ADMM method can be improved substantially, which enables the application of distributed approaches to very large-scale systems.