im PublikationsserverTitelangaben
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 S.
Volltext
![[img]](https://epub.uni-bayreuth.de/style/images/fileicons/application_pdf.png) |
PDF
Braun_Gruene_et_al_DistributedOptimizationAlgorithm_2015.pdf - Preprint Available under License Deutsches Urheberrechtsgesetz . Download (535kB) |
Angaben zu Projekten
| Projekttitel: |
|
||||||
|---|---|---|---|---|---|---|---|
| Projektfinanzierung: |
Deutsche Forschungsgemeinschaft |
Abstract
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.
Download-Statistik
Download-Statistik
