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Distributed economic dispatch of embedded generation in smart grids

Jilles Steeve Dibangoye 1 Arnaud Doniec 2 Hicham Fakham 3 Frédéric Colas 3 Xavier Guillaud 4
1 CHROMA - Robots coopératifs et adaptés à la présence humaine en environnements dynamiques
Inria Grenoble - Rhône-Alpes, CITI - CITI Centre of Innovation in Telecommunications and Integration of services
4 L2EP - Équipe Réseaux
L2EP - Laboratoire d’Électrotechnique et d’Électronique de Puissance
Abstract : 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.
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Contributor : Jilles Steeve Dibangoye <>
Submitted on : Monday, August 31, 2015 - 12:04:30 AM
Last modification on : Wednesday, July 8, 2020 - 12:43:50 PM

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Jilles Steeve Dibangoye, Arnaud Doniec, Hicham Fakham, Frédéric Colas, Xavier Guillaud. Distributed economic dispatch of embedded generation in smart grids. Engineering Applications of Artificial Intelligence, Elsevier, 2015, 44, pp.64-78. ⟨10.1016/j.engappai.2015.05.007⟩. ⟨hal-01188482⟩



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