982 research outputs found
A Coordinate-Descent Algorithm for Tracking Solutions in Time-Varying Optimal Power Flows
Consider a polynomial optimisation problem, whose instances vary continuously
over time. We propose to use a coordinate-descent algorithm for solving such
time-varying optimisation problems. In particular, we focus on relaxations of
transmission-constrained problems in power systems.
On the example of the alternating-current optimal power flows (ACOPF), we
bound the difference between the current approximate optimal cost generated by
our algorithm and the optimal cost for a relaxation using the most recent data
from above by a function of the properties of the instance and the rate of
change to the instance over time. We also bound the number of floating-point
operations that need to be performed between two updates in order to guarantee
the error is bounded from above by a given constant
Networked signal and information processing
The article reviews significant advances in networked signal and information processing, which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments of distributed agents. As these interacting agents cooperate, new collective behaviors emerge from local decisions and actions. Moreover, and significantly, theory and applications show that networked agents, through cooperation and sharing, are able to match the performance of cloud or federated solutions, while offering the potential for improved privacy, increasing resilience, and saving resources
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