Titlebar

Export bibliographic data
Literature by the same author
plus on the publication server
plus at Google Scholar

 

A distributed optimization algorithm for the predictive control of smart grids

Title data

Braun, Philipp ; Grüne, Lars ; Kellett, Christopher M. ; Weller, Steven R. ; Worthmann, Karl:
A distributed optimization algorithm for the predictive control of smart grids.
Department of Mathematics, University of Bayreuth; School of Electrical Engineering and Computer Science, University of Newcastle, Australia; Technische Universität Ilmenau
Bayreuth , 2015 . - 12 p.

WarningThere is a more recent version of this item available.

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
DFG Priority Program 1305 "Control theory for digitally networked dynamical systems", Project "Performance Analysis for Distributed and Multiobjective Model Predictive Control"GR1569/13-1
ARC Future FellowshipFT1101000746

Project financing: Deutsche Forschungsgemeinschaft

Abstract in another language

In this paper, we present a hierarchical, iterative distributed optimization algorithm, and show that the algorithm converges to the solution of a particular global optimization problem. The motivation for the distributed optimization problem is the predictive control of a smart grid, in which the states of charge of a network of residential-scale batteries are optimally coordinated so as to minimize variability in the aggregated power supplied to/from the grid by the residential network. The distributed algorithm developed in this paper calls for communication between a central entity and an optimizing agent associated with each battery, but does not require communication between agents. The distributed algorithm is shown to achieve the performance of a large-scale centralized optimization algorithm, but with greatly reduced communication overhead and computational burden. A numerical case study using data from an Australian electricity distribution network is presented to demonstrate the performance of the distributed optimization algorithm.

Further data

Item Type: Preprint, postprint, working paper, discussion paper
Additional notes: Accepted for Publication in IEEE Transactions on Automatic Control
Keywords: distributed optimization; model predictive control; smart grid
Institutions of the University: Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics)
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics) > Chair Mathematics V (Applied Mathematics) - Univ.-Prof. Dr. Lars Grüne)
Profile Fields
Profile Fields > Advanced Fields
Profile Fields > Advanced Fields > Nonlinear Dynamics
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 510 Mathematics
Date Deposited: 27 Jun 2015 21:00
Last Modified: 29 Jan 2016 08:25
URI: https://eref.uni-bayreuth.de/id/eprint/15446

Available Versions of this Item