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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 S.
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Project information
| Project title: |
Project's official title Project'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 Fellowship FT1101000746 |
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| Project financing: |
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.
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