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A Distributed Optimization Algorithm for the Predictive Control of Smart Grids
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DOI：10.1109/TAC.2016.2525808.png)
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摘要
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In this paper, we present a hierarchical, iterative distributed optimization algorithm and show that the algorithm converges to the global solution of a particular 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.
Keyword:
Control over communications
optimization algorithms
predictive control for linear systems
smart grid
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IF:
7
论文数:
1.3W
被引数:
6.7W
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