Distributed Economic Dispatch of Embedded ...
Type de document :
Article dans une revue scientifique: Article original
URL permanente :
Titre :
Distributed Economic Dispatch of Embedded Generation in Smart Grids
Auteur(s) :
DIBANGOYE, jille [Auteur]
Institut National des Sciences Appliquées de Lyon [INSA Lyon]
Doniec, Arnaud [Auteur]
Fakham, Hicham [Auteur]
13338|||Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
Colas, Frederic [Auteur]
13338|||Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
Guillaud, Xavier [Auteur]
13338|||Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
Institut National des Sciences Appliquées de Lyon [INSA Lyon]
Doniec, Arnaud [Auteur]
Fakham, Hicham [Auteur]
13338|||Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
Colas, Frederic [Auteur]
13338|||Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
Guillaud, Xavier [Auteur]
13338|||Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
Titre de la revue :
Engineering Applications of Artificial Intelligence
Numéro :
44
Pagination :
64-78
Éditeur :
Elsevier
Date de publication :
2015
ISSN :
0952-1976
Mot(s)-clé(s) :
Smart grid
Multi Agent Planning
Distributed Stochastic Unit Commitment Problem
Multi Agent Planning
Distributed Stochastic Unit Commitment Problem
Mot(s)-clé(s) en anglais :
Smart grid
Distributed stochastic unit commitment problem
Multi-agent planning
Information preserving
Distributed stochastic unit commitment problem
Multi-agent planning
Information preserving
Discipline(s) HAL :
Informatique [cs]/Intelligence artificielle [cs.AI]
Sciences de l'ingénieur [physics]/Energie électrique
Sciences de l'ingénieur [physics]/Energie électrique
Résumé en anglais : [en]
In a smart grid context, the increasing penetration of embedded generation units leads to a greater complexity in the management of production units. In this paper, we focus on the impact of the introduction of decentralized ...
Lire la suite >In a smart grid context, the increasing penetration of embedded generation units leads to a greater complexity in the management of production units. In this paper, we focus on the impact of the introduction of decentralized generation for the unit commitment (UC) problem. Unit commitment problems consist in finding the optimal schedules and amounts of power to be generated by a set of generating units in response to an electricity demand forecast. While this problem has received a significant amount of attention, classical approaches assume that these problems are centralized and deterministic. However, these two assumptions are not realistic in a smart grid context. Indeed, finding the optimal schedules and amounts of power to be generated by multiple distributed generator units is not trivial since it requires to deal with distributed computation, privacy, stochastic planning, etc. In this paper, we focus on smart grid scenarios where the main source of complexity comes from the proliferation of distributed generating units. In solving this issue, we consider distributed stochastic unit commitment problems. We introduce a novel distributed gradient descent algorithm which allows us to circumvent classical assumptions. This algorithm is evaluated through a set of experiments on real-time power grid simulator.Lire moins >
Lire la suite >In a smart grid context, the increasing penetration of embedded generation units leads to a greater complexity in the management of production units. In this paper, we focus on the impact of the introduction of decentralized generation for the unit commitment (UC) problem. Unit commitment problems consist in finding the optimal schedules and amounts of power to be generated by a set of generating units in response to an electricity demand forecast. While this problem has received a significant amount of attention, classical approaches assume that these problems are centralized and deterministic. However, these two assumptions are not realistic in a smart grid context. Indeed, finding the optimal schedules and amounts of power to be generated by multiple distributed generator units is not trivial since it requires to deal with distributed computation, privacy, stochastic planning, etc. In this paper, we focus on smart grid scenarios where the main source of complexity comes from the proliferation of distributed generating units. In solving this issue, we consider distributed stochastic unit commitment problems. We introduce a novel distributed gradient descent algorithm which allows us to circumvent classical assumptions. This algorithm is evaluated through a set of experiments on real-time power grid simulator.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Commentaire :
https://hal.archives-ouvertes.fr/hal-01890396v1
Équipe(s) de recherche :
Équipe Réseaux
Date de dépôt :
2020-05-15T13:26:50Z
2022-02-11T08:04:50Z
2022-02-11T08:21:02Z
2022-02-11T08:04:50Z
2022-02-11T08:21:02Z
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