Jorge Cortés
Professor
Cymer Corporation Endowed Chair
A scheduled-asynchronous distributed optimization algorithm
for the optimal power flow problem
C.-Y. Chang,
J. Cortés, S. Martínez
Proceedings of the American Control Conference, Seattle, Washington, USA, 2017, pp. 3968-3973
Abstract
Optimal power flow (OPF) problems are non-convex and large-scale
optimization problems. Finding an optimal solution for the OPF
problem in real time is challenging and important in various
applications. Recent studies show that a wide class of OPF problems
have an exact semidefinite programming (SDP) convex
relaxation. However, only few works have considered distributed
algorithms to solve these. In this paper, we propose a
scheduled-asynchronous algorithm with this objective. The proposed
algorithm follows an ADMM-like iteration for every edge in the
electrical network and is asynchronous in the sense that the agents
do not simultaneously update their local variables, but only do so
when they have received fresh information from all of their
neighbors. In addition, if the electrical network topology is
bipartite, the proposed algorithm has a convergence rate of
O(1/n), where n is the iteration per agent. The asynchronous
property and fast convergence rate make the proposed algorithm
suitable for the OPF problem. Simulation studies demonstrate that
the proposed algorithm is scalable with the number of buses and
robust to network effects including delays and packet drops.
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Mechanical and Aerospace Engineering,
University of California, San Diego
9500 Gilman Dr,
La Jolla, California, 92093-0411
Ph: 1-858-822-7930
Fax: 1-858-822-3107
cortes at ucsd.edu
Skype id:
jorgilliyo