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Coopérative énergétique intelligente

Abstract : Currently, energy management strategies in smart grids are mostly limited to the interest of a subsystem. As a general rule, each actor is autonomously managed regardless of whether it is integrated into a nearby power grid. For example, a building energy management system aims to provide the desired level of service to occupants and does not care about its impact on the system unless it has to meet certain constraints.This way of managing can of course lead to a given equilibrium but the resultant will be only a set of optimized subsystems that will rarely lead to an overall optimum in the pocket to which they belong.In view of what has been said above, and in view of a rapidly evolving distribution system architecture; The physical and algorithmic restructuring in physical or virtual sub networks will allow to answer efficiently the problems related to:- Security of supply- Massive integration of renewable energy- The quality of energy- The appearance of new unconventional loads- System servicesIn the literature, aspects of microgrid energy control and management are treated separately, and intelligent network interaction is simply proposed.To meet these challenges, the concept of smart grids has emerged over the last decade. It builds on the capabilities of modern communication systems that enable the continuous flow of data between the players in an intelligent network and the scalable computing capabilities to implement advanced large-scale energy management strategies ladder.This thesis proposes to carry out a systemic study of the control of microgrid which control aims at an optimized management of the energy in connection with a structure of what is commonly called "intelligent network", while optimizing the local power under a model Predictive control (MPC).The MPC stands out among advanced network control strategies for several reasons. Firstly, it makes it possible to easily handle multi-variable systems which are subjected to multiple constraints. Secondly, it is able to anticipate future events by taking into account forecasts (for example, weather forecasts, forecast loads, etc.). For these reasons, part of this thesis is dedicated to MPC algorithms which aim to coordinate optimally a large number of actors in a microgrid (PV, Batteries, Wind, loads ...). The idea is to have a local MPC controller for each microgrid and above it, an MPC management controller coordinator that influences the local controller in such a way that the overall optimality of the intelligent network is respected. The objective of maximizing local consumption of locally produced energy is considered. This objective is a step towards the energy independence of the local microgrids with respect to the main network, which however can intervene to buy the excess power of all microgrids of the cooperative.This thesis was prepared in co-supervision between the Gipsa-Lab of the Grenoble-Alpes University (UGA) and the PREEA of the Lebanese-French University of Technology and Applied Sciences in the application of the PARADISE project.This project aims, through its contributions, to optimize distribution networks that are portable in the presence of a high rate of intermittent production based on renewable energy; And this, by physical architectures and incremental algorithm.
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Submitted on : Friday, February 9, 2018 - 11:35:08 AM
Last modification on : Wednesday, October 14, 2020 - 4:17:10 AM


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  • HAL Id : tel-01705263, version 1



Khaled Hajar. Coopérative énergétique intelligente. Energie électrique. Université de technologie et des sciences appliquées Libano-française, 2017. Français. ⟨NNT : 2017GREAT028⟩. ⟨tel-01705263⟩



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