225,202 research outputs found
Constrained distributed optimization : A population dynamics approach
Large-scale network systems involve a large number of states, which makes the design of real-time controllers a challenging task. A distributed controller design allows to reduce computational requirements since tasks are divided into different systems, allowing real-time processing. This paper proposes a novel methodology for solving constrained optimization problems in a distributed way inspired by population dynamics. This methodology consists of an extension of a population dynamics equation and the introduction of a mass dynamics equation. The proposed methodology divides the problem into smaller sub-problems, whose feasible regions vary over time achieving an agreement to solve the global problem. The methodology also guarantees attraction to the feasible region and allows to have few changes in the decision-making design when a network suffers the addition/removal of nodes/edges. Then, distributed controllers are designed with the proposed methodology and applied to the large-scale Barcelona Drinking Water Network (BDWN). Some simulations are presented and discussed in order to illustrate the control performance.Peer ReviewedPostprint (author's final draft
Chance Constrained Optimal Power Flow Using the Inner-Outer Approximation Approach
In recent years, there has been a huge trend to penetrate renewable energy
sources into energy networks. However, these sources introduce uncertain power
generation depending on environmental conditions. Therefore, finding 'optimal'
and 'feasible' operation strategies is still a big challenge for network
operators and thus, an appropriate optimization approach is of utmost
importance. In this paper, we formulate the optimal power flow (OPF) with
uncertainties as a chance constrained optimization problem. Since uncertainties
in the network are usually 'non-Gaussian' distributed random variables, the
chance constraints cannot be directly converted to deterministic constraints.
Therefore, in this paper we use the recently-developed approach of inner-outer
approximation to approximately solve the chance constrained OPF. The
effectiveness of the approach is shown using DC OPF incorporating uncertain
non-Gaussian distributed wind power
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