Many modern power networks are partitioned in nature, with disjoint components of the overall network controlled by competing operators. The problem of solving the Optimal Power Flow (OPF) problem in a distributed manner is therefore of significant interest. For networks in which the high-level structure has tree topology, we analyze a dual decomposition approach to solving a recent convex relaxation of the OPF problem for the overall network in a distributed manner. Incorporating higher-order dynamics in terms of local auxiliary variables, we prove a result of guaranteed convergence to the solution set for sufficiently small values of the step size. ©2013 IEEE
Optimal power flow (OPF) is an important problem for power generation and it is in general non-conve...
Optimal power flow (OPF) is a well known challenging optimization problem for power sys-tems enginee...
Abstract — The optimal power flow (OPF) problem is funda-mental in power system operations and plann...
This paper presents a distributed approach to optimal power flow (OPF) in an electrical network, sui...
Abstract—The optimal power flow (OPF) problem determines a network operating point that minimizes a ...
The optimal power flow (OPF) problem determines a network operating point that minimizes a certain o...
Abstract—Optimal power flow (OPF) is an important problem for power generation and it is in general ...
The optimal power flow (OPF) problem, which playsa central role in operating electrical networks is ...
The optimal power flow (OPF) problem seeks to control power generation/demand to optimize certain ob...
The optimal power flow (OPF) problem determines a network operating point that minimizes a certain o...
We have recently observed and justified that the optimal power flow (OPF) problem with a quadratic c...
The optimal power flow (OPF) problem is generally nonconvex. Recently a second-order cone relaxation...
The optimal power flow (OPF) problem seeks to control power generation/demand to optimize certain ob...
Abstract—The optimal power flow (OPF) problem minimizes the power loss in an electrical network by o...
The optimal power flow (OPF) problem minimizes the power loss in an electrical network by optimizing...
Optimal power flow (OPF) is an important problem for power generation and it is in general non-conve...
Optimal power flow (OPF) is a well known challenging optimization problem for power sys-tems enginee...
Abstract — The optimal power flow (OPF) problem is funda-mental in power system operations and plann...
This paper presents a distributed approach to optimal power flow (OPF) in an electrical network, sui...
Abstract—The optimal power flow (OPF) problem determines a network operating point that minimizes a ...
The optimal power flow (OPF) problem determines a network operating point that minimizes a certain o...
Abstract—Optimal power flow (OPF) is an important problem for power generation and it is in general ...
The optimal power flow (OPF) problem, which playsa central role in operating electrical networks is ...
The optimal power flow (OPF) problem seeks to control power generation/demand to optimize certain ob...
The optimal power flow (OPF) problem determines a network operating point that minimizes a certain o...
We have recently observed and justified that the optimal power flow (OPF) problem with a quadratic c...
The optimal power flow (OPF) problem is generally nonconvex. Recently a second-order cone relaxation...
The optimal power flow (OPF) problem seeks to control power generation/demand to optimize certain ob...
Abstract—The optimal power flow (OPF) problem minimizes the power loss in an electrical network by o...
The optimal power flow (OPF) problem minimizes the power loss in an electrical network by optimizing...
Optimal power flow (OPF) is an important problem for power generation and it is in general non-conve...
Optimal power flow (OPF) is a well known challenging optimization problem for power sys-tems enginee...
Abstract — The optimal power flow (OPF) problem is funda-mental in power system operations and plann...