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Motivated by broad applications in various fields of engineering, we study network resource allocation problems where the goal is to optimally allocate a fixed portion of resources over a network of nodes. In these problems, due to the large scale of the network and complicated interconnections between nodes, any solution must be implemented in parallel and based only on local data resulting in a...
This paper addresses the distributed resource allocation problem for a network of multiple agents with directed and time-varying communication topologies. Suppose that the total amount of resources is a constant, represented by an equality constraint, and that the amount of resources allocated to each agent is subject to an inequality constraint, called the state constraint. We then aim to solve it...
In a smart grid, the economic dispatch problem is an optimization problem whose objective is to reduce the total generation cost, subject to some constraints. The Incremental Cost Consensus (ICC) algorithm and Leaderless Incremental Cost Consensus (LICC) resolve the economic dispatch problem in a distributed fashion. Unlike prior work that implements ICC and LICC in simulation, in this paper, we implement...
Distributed optimization problems are generally described as the minimization of a global objective function in a system, where each agent can get information only from a neighborhood defined by a network topology. To solve this problem, we present a local strategy based on population dynamics (i.e., the local replicator equation (LRE)), to define functions and tasks assigned to each node in a system...
The energy management problem in smart grid is a complex optimization problem of a Cyber-Physical System. Distributed cooperative energy management algorithms have great potential to solve this class of problems. In addition to the synchronous distributed algorithms, asynchronous distributed algorithms are more flexible, robust to packet loss and do not require global clock synchronization. In this...
In a smart grid, effective distributed control algorithms could be embedded in distributed controllers to properly allocate electrical power among connected buses autonomously. By selecting the incremental cost of each generation unit as the consensus variable, the Incremental Cost Consensus (ICC) algorithm can solve the economic dispatch problem in a distributed manner instead of using conventional...
In a next generation power system, effective distributed control algorithms could be embedded in distributed controllers to properly allocate electrical power among connected buses autonomously. In this paper, we present a novel approach to solve the economic dispatch problem. By selecting the incremental cost of each generation unit as the consensus variable, the algorithm is able to solve the conventional...
(N-1) contingency planning has been object of study in the area of distribution networks of several decades. Energy distribution companies have to reconnect areas affected by an outage within a very short time, and observe operational constraints, to avoid the possibility of severe financial penalties by regulatory bodies. Distribution networks are often operated with a radial topology, but, ideally,...
Lots of growing neural network models have been proposed to tackle the incremental learning problem, but they also bring about the problem of fast growing complex structure. In this paper, we present a combinational Neural Network of SOM (Self-Organizing Maps) and RBF (Radial Basis Function) based on incremental learning method. The experiment of acoustic fault sources identification of underwater...
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