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Proceedings ArticleDOI

A distributed wardrop control algorithm for load balancing in smart grids

TLDR
A distributed strategy for load balancing in a smart grid, modeling demand and supply as a networked dynamical system, is presented, which is proven to converge to a Wardrop equilibrium.
Abstract
This paper presents a distributed strategy for load balancing in a smart grid, modeling demand and supply as a networked dynamical system. The algorithm, which is characterized by point-to-point communications among agents implemented at the level of local energy management systems, is proven to converge to a Wardrop equilibrium. Numerical simulations of realistic scenarios are reported to show the effectiveness of the proposed approach.

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Citations
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Journal ArticleDOI

A Framework for Automatic Initialization of Multi-Agent Production Systems Using Semantic Web Technologies

TL;DR: This work proposes to automatically initialize every agent with a knowledge base created a priori using semantic web technologies (SWT) to reduce both the communication and computational load necessary at runtime for agent-based CPSoS.
Journal ArticleDOI

Lyapunov-Based Design of a Distributed Wardrop Load-Balancing Algorithm With Application to Software-Defined Networking

TL;DR: An original discrete-time, distributed, noncooperative load-balancing algorithm, based on mean field game theory, which does not require explicit communications, is presented and proven to converge to an arbitrarily small neighborhood of a specific equilibrium among the loads of the providers, known as Wardrop equilibrium.
Journal ArticleDOI

A sufficient descent nonlinear conjugate gradient method for solving M-tensor equations

TL;DR: A sufficient descent nonlinear conjugate gradient method with inexact line search is proposed for solving the transformed unconstrained optimization problem and the global convergence of the proposed method is proved.
Journal ArticleDOI

Human-swarm Interactions for Formation Control Using Interpreters

TL;DR: A novel interpreter system is proposed, which acts as an intermediary between the user and the swarm to simplify the roles of both, and employs machine learning, estimation and optimal control techniques to translate the users intention into swarm control parameters.
Journal ArticleDOI

Lyapunov-based Triggering Mechanisms for Event-triggered Control

TL;DR: It is proven that, compared with the dynamic event-triggering mechanism reported in the literature, this new scheme can ensure a larger minimum interevent time with the same decay rate of the trajectory of the resultant closed-loop system.
References
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Journal ArticleDOI

Game-Theoretic Methods for the Smart Grid: An Overview of Microgrid Systems, Demand-Side Management, and Smart Grid Communications

TL;DR: An overview on the potential of applying game theory for addressing relevant and timely open problems in three emerging areas that pertain to the smart grid: microgrid systems, demand-side management, and communications is provided.
Journal ArticleDOI

Game-Theoretic Demand-Side Management With Storage Devices for the Future Smart Grid

TL;DR: The Stackelberg game is shown to be the general case of the minimum Peak-to-Average power ratio (PAR) problem and to have a unique Nash equilibrium, that is also the global system optimal point.
Journal ArticleDOI

A Cooperative Game Theoretical Technique for Joint Optimization of Energy Consumption and Response Time in Computational Grids

TL;DR: This paper studies the problem of allocation of tasks onto a computational grid with the aim to simultaneously minimize the energy consumption and the makespan subject to the constraints of deadlines and tasks' architectural requirements and proposes a solution from cooperative game theory based on the concept of Nash bargaining solution.
Journal ArticleDOI

A Game Theory Strategy to Integrate Distributed Agent-Based Functions in Smart Grids

TL;DR: A strategy to solve the conflicting interests in order to achieve overall optimal performance in the electricity supply system is proposed and results show the effectiveness of the approach in optimally harmonizing functions of power routing and matching.
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