Abstract-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. Index Terms-Control over communications, optimization algorithms, predictive control for linear systems, smart grid.
In REF , a predictive control algorithm is developed for a single distribution optimization problem.
A Distributed Optimization Algorithm for the Predictive Control of Smart Grids
IEEE Transactions on Automatic Control
IEEE Transactions on Automatic Control
Computer Science