Dissertations / Theses on the topic 'Réseau intelligent d'énergie'
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Chabaud, Aurélie. "Micro-réseau intelligent pour la gestion des ressources énergétiques." Perpignan, 2014. https://hal-univ-perp.archives-ouvertes.fr/tel-01260201.
Hajar, Khaled. "Coopérative énergétique intelligente." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAT028/document.
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
Ayari, Baligh. "Analyse du système de chauffage urbain dans une perspective de transformation en un réseau intelligent : application au démonstrateur SUNRISE "Ville intelligente et durable." Thesis, Lille 1, 2014. http://www.theses.fr/2014LIL10191.
The thesis is part of the SunRise project "Demonstrator of the Smart and Sustainable City", which aim to turn the Campus of the University Lille1 in a demonstrator of the Smart and Sustainable city. The study focuses on the district-heating component. It aims at (i) building an information system on the heating network by the integration of all the information concerning the heating in a Geographic Information System (ii) analyzing the heating consumption. This is the first phase of the construction, of the Smart Heating network. The work involves four parts. The first includes a literature review of works conducted on urban development, energy consumption, district heating technology and its place in the energy consumption. The second part presents the Campus of the University Lille1, which serves as support for the demonstrator SunRise with a particular focus on the heating system (production, transport, heat exchange stations, secondary network), and buildings (heated surfaces, energy efficiency, clustering in geographic or operational areas). Information on the heating system has been integrated into a Geographic Information System (GIS). The 3rd part presents the annual consumption of the campus buildings together with a comparison them with their "DPE" (Diagnostic de Performance énergétique). This chapter provides a good understanding of the heating consumption of different buildings of the Campus. The last part presents a detailed analysis of the heat consumption of the building M1. The analysis is performed at different scales: monthly, daily and hourly
Ali, Sadaqat. "Energy management of multi-source DC microgrid systems for residential applications." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0159.
Compared to the alternating current (AC) electrical grid, the direct current (DC) electrical grid has demonstrated numerous advantages, such as its natural interface with renewable energy sources (RES), energy storage systems, and DC loads. It offers superior efficiency with fewer conversion steps, simpler control without skin effect or reactive power considerations. DC microgrids remain a relatively new technology, and their network architectures, control strategies, and stabilization techniques require significant research efforts. In this context, this thesis focuses on energy management issues in a multi-source DC electrical grid dedicated to residential applications. The DC electrical grid consists of distributed generators (solar panels), a hybrid energy storage system (HESS) with batteries and a supercapacitor (SC), and DC loads interconnected via DC/DC power converters. The primary objective of this research is to develop an advanced energy management strategy (EMS) to enhance the operational efficiency of the system while improving its reliability and sustainability. A hierarchical simulation platform of the DC electrical grid has been developed using MATLAB/Simulink. It comprises two layers with different time scales: a local control layer (time scale of a few seconds to minutes due to converter switching behavior) for controlling local components, and a system-level control layer (time scale of a few days to months with accelerated testing) for long-term validation and performance evaluation of the EMS. In the local control layer, solar panels, batteries, and the supercapacitor have been modeled and controlled separately. Various control modes, such as current control, voltage control, and maximum power point tracking (MPPT), have been implemented. A low-pass filter (LPF) has been applied to divide the total HESS power into low and high frequencies for the batteries and supercapacitor. Different LPF cutoff frequencies for power sharing have also been studied. A combined hybrid bi-level EMS and automatic sizing have been proposed and validated. It mainly covers five operational scenarios, including solar panel production reduction, load reduction, and three scenarios involving HESS control combined with supercapacitor state of charge (SOC) control retention. An objective function that considers both capital expenditure (CAPEX) and operating costs (OPEX) has been designed for EMS performance evaluation. The interaction between the HESS and EMS has been jointly studied based on an open dataset of residential electrical consumption profiles covering both summer and winter seasons. Finally, an experimental platform of a multi-source DC electrical grid has been developed to validate the EMS in real-time. It comprises four lithium-ion batteries, a supercapacitor, a programmable DC power supply, a programmable DC load, corresponding DC/DC converters, and a real-time controller (dSPACE/Microlabbox). Accelerated tests have been conducted to verify the proposed EMS in different operational scenarios by integrating real solar panels and load consumption profiles. The hierarchical simulation and experimental DC electrical grid platforms can be generally used to verify and evaluate various EMS
Courchelle, Inès de. "Vers une meilleure utilisation des énergies renouvelables : application à des bâtiments scientifiques." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30196/document.
The work of this thesis deals with the optimization of energy and computer flows in an intelligent network aiming to supply a data center via renewable energies. In this thesis are treated the problems related to the pooling of energy and computer information in a strong reactivity constraint through the creation of an architecture for an intelligent network. The modeling of such a network must allow the decision making in a dynamic and autonomous way. The objective of this modeling, via an intelligent network, is the optimization of renewable resources in order to reduce the ecological footprint
Dahmane, Yassir. "Gestion d'énergie optimisée étendue véhicules infrastructures." Thesis, Ecole centrale de Nantes, 2020. http://www.theses.fr/2020ECDN0047.
This PhD thesis is part of the Renault/Centrale Nantes chair on improving the performance of electric vehicles (EV/PHEV). It is dedicated to the problem of the charging management of electric vehicles, using optimization algorithms and smart charging strategies. In this framework, several contributions have been proposed on the topics of smart charging of an EV and the smart energy management of an EV fleet, considering the mobility constraints (desired SOC at the end of the charging and departure time), the temperature of the Li-ion bat teries, the charging infrastructures, and the power grid. On the subject of smart charging of an EV, the contributions focused on the development of embedded algorithms allowing the scheduling of the charging power profile in order to reduce the charging cost. The proposed algorithms take into account the mobility needs of electric vehicle users, and the effect of temperature on the charging power of Li-ion batteries. On the subject of fleet energy management, the contributions focus on centralized algorithms in electric vehicle charging stations. An unidirectional recharging algorithm has been proposed in or der to evaluate the optimal number of electric vehicles to be recharged with a good level of satisfaction of mobility constraints and without any infrastructure reinforcement. The switch to the bidirectional algorithm is due to the exploitation of the V2G functionality, which will allow the participation of electric vehicles in frequency regulation. The proposed contributions on the first topic have the advantage of increasing the estimation accuracy of final SOC in very low temperature, and to be embedded on the EV due to the low computational capacity of the algorithms and the speed of execution. On the other hand, the EV fleet charging manage ment algorithms allow the possibility of large-scale integration of electric vehicles on the grid and show the potential of EVs in contributing to the stability of the power grid by offering ancillary services such as frequency regulation. The algorithms and strategies developed have been tested in simulation and will be tested on an EV charging system. The results obtained have highlighted the benefits of smart charg ing on cost reduction and grid benefits and the importance of electric vehicle fleet charging management in the development of grid services
Lefort, Antoine. "A smart grid ready building energy management system based on a hierarchical model predictive control." Thesis, Supélec, 2014. http://www.theses.fr/2014SUPL0010/document.
Electrical system is under a hard constraint: production and consumption must be equal. The production has to integrate non-controllable energy resources and to consider variability of local productions. While buildings are one of the most important energy consumers, the emergence of information and communication technologies (ICT) in the building integrates them in smart-grid as important consumer-actor players. Indeed, they have at their disposal various storage capacities: thermal storage, hot-water tank and also electrical battery. In our work we develop an hierarchical and distributed Building Energy Management Systems based on model predictive control in order to enable to shift, to reduce or even to store energy according to grid informations. The anticipation enables to plan the energy consumption in order to optimize the operating cost values, while the hierarchical architecture enables to treat the high resolution problem complexity and the distributed aspect enables to ensure the control modularity bringing adaptability to the controller
Hennane, Youssef. "Réseaux électriques en présence de génération d'énergies distribuée." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0183.
Microgrids play an important role in the electrification of rural and remote areas because they can operate in islanded mode without being dependent on the main grid, thus facilitating access to electricity for these areas.Microgrids operating in island mode require high energy and power storage elements to ensure reliable power supply of loads due to the intermittent nature of renewable energy sources. This problem is more difficult to solve in microgrids with simple topologies in which sources and loads are connected to a single common point of connection via power lines (single-PCC microgrids). A solution to ensure a higher availability of energy, with smaller storage elements and therefore lower cost, is the implementation of microgrids with mesh structure topologies with several distributed sources of different natures connected to its different connection points (multi-PCC microgrids). One of the challenges for mesh microgrids is to synchronize and connect all the distributed generators while ensuring "plug and play" functionality and respecting the active and reactive power sharing between the different distributed generation units. The most widely used methods to achieve DG active and reactive power sharing are applied at the primary level of microgrid control and are designed based on "Droop control" approaches. However, most of these methods are only effective in single-PCC microgrids and not in multi-PCC mesh microgrids. Another problem is that using Droop control-based methods to control microgrids at the primary level can cause the microgrid voltage and frequency to deviate from their nominal values, affecting the power quality and proper operation of the microgrid.The thesis is divided into three parts. The first part presents the concept of microgrids and a review of the literature on their control strategies. In the second part, we propose a new nonlinear droop control strategy for distributed generators of mesh microgrids, whether they operate in islanded or grid-connected modes. This strategy ensures the secure synchronization of the distributed sources and the accurate power sharing between them. This strategy allows compensating voltage and frequency deviations of an islanded microgrid by deploying an additional secondary control for each of its generators using a single information on the voltage of a pilot node. This control method also allows a smooth transition from islanded to grid-connected mode without affecting the active and reactive power sharing of its sources during synchronization, as well as the control of active and reactive power exchanged with the main grid in grid-connected mode. The third part proposes a consensus-based distributed nonlinear Droop control for accurate sharing of active and reactive powers between distributed sources as well as for frequency and voltage restoration in reconfigurable islanded mesh microgrids. The controllers for primary and secondary controls are locally adjusted and do not require knowledge of the microgrid structure. The efficiency of the proposed controls proposed in this thesis as well as their robustness are proved by simulation using Simscape and are validated by HIL tests. Also, the stability of the systems is studied based on the developed mathematical model of two different mesh microgrids controlled by both proposed distributed controls
Gladkikh, Egor. "Optimisation de l'architecture des réseaux de distribution d'énergie électrique." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAT055/document.
To cope with the changes in the energy landscape, electrical distribution networks are submitted to operational requirements in order to guarantee reliability indices. In the coming years, big investments are planned for the construction of flexible, consistent and effective electrical networks, based on the new architectures, innovative technical solutions and in response to the development of renewable energy. Taking into account the industrial needs of the development of future distribution networks, we propose in this thesis an approach based on the graph theory and combinatorial optimization for the design of new architectures for distribution networks. Our approach is to study the general problem of finding an optimal architecture which respects a set of topological (redundancy) and electrical (maximum current, voltage plan) constraints according to precise optimization criteria: minimization of operating cost (OPEX) and minimization of investment (CAPEX). Thus, the two families of combinatorial problems (and their relaxations) were explored to propose effective resolutions (exact or approximate) of the distribution network planning problem using an adapted formulation. We are particularly interested in 2-connected graphs and the arborescent flow problem with minimum quadratic losses. The comparative results of tests on the network instances (fictional and real) for the proposed methods were presented
Le, Ky. "Gestion optimale des consommations d'énergie dans les bâtiments." Phd thesis, Grenoble INPG, 2008. http://tel.archives-ouvertes.fr/tel-00301368.
Amicarelli, Elvira. "Stratégies de gestion des réseaux électriques intelligents à fort taux de production renouvelable distribuée." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAT056/document.
In 2007 with the renewable energy directive, the European Union established the development of a low-carbon economy. This directive aims to decrease greenhouse gas emissions by increasing the energy produced by renewable energy. Already today, the massive diffusion of renewable systems is tangible in the European electricity mix. However, in spite of their potential benefits, their large-scale integration leads to new technical and regulatory questions. Consequently, new management strategies need to be developed and applied in order to ensure a reliable and economical operation of the system. Microgrids are considered to be one of the most effective and flexible solutions able to meet these new needs.The main goals of this thesis are the conceptualization, development and implementation of different management strategies for microgrids. The algorithms developed aim to facilitate the massive integration of renewables and at the same time lead to an effective and economic operation of the systems. A new architecture of distribution grids based on cluster of microgrids was proposed. Each microgrid is composed of a number of renewable-based and conventional generation systems, storage systems and consumption. An optimal and distributed energy management strategy was then defined and developed. This strategy allows to manage the short-term energy management and real-time control of microgrids by using the connected sources in a smart and cost-efficient way. A multi-agent system and the mixed integer linear optimization technique were used for the implementation of this strategy.From a global point of view, each microgrid is seen as a coherent entity, which can support network operation by using its flexible and aggregated sources. Hence, the second part of this thesis aims to understand how distribution grids can exploit these cluster of microgrids and their properties. Different mechanisms for the active management of distribution grids are conceptualized from the technical and economical point of view. A new strategy based on hierarchical management of different smart levels allow to reduce the complexity of the system and to implement a more flexible and extensible system, thanks to a more local use of model knowledge and users behaviour. On the end, the theoretical work were tested on an experimental test-bed in order to show the effectiveness of the proposed theories
Alsalloum, Hala. "Gestion décentralisée des interactions complexes entre producteurs et consommateurs d'énergie électrique." Thesis, Troyes, 2021. http://www.theses.fr/2021TROY0008.
This thesis focuses on the proposal of a decentralized approach for managing energy demand in the context of smart grids. The main objective is to promote energy savings and the use of clean energy resources, while encouraging users to actively participate in demand management. In this regard, controlling energy consumption becomes a priority. It applies at several levels from the neighborhood to the city. The work presented in this thesis falls within this framework. We first present a modeling of the various behaviors of the agents present within the energy market, based on game theory while taking into account several constraints such as the heterogeneity of producers and consumers present, and the spatial and temporal constraints. Then, we try to meet their needs by: (1) optimizing the demand for energy (from consumers’ side who themselves become energy producers through the integration of renewable energies) and (2) its price (from producers’ side). Finally, we propose distributed algorithms shared between players to achieve a stable state of the game. Comparisons with conventional scenarios known in this field have shown the effectiveness of our contributions
Bouallaga, Anouar. "Gestion énergétique d’une infrastructure de charge intelligente de véhicules électriques dans un réseau de distribution intégrant des énergies renouvelables." Thesis, Lille 1, 2015. http://www.theses.fr/2015LIL10043/document.
Energy and environmental crisis have prompted the government to take strong measures to stimulate energy transition and accelerate green growth. In this context, electric vehicles (EVs) are considered as a real solution to deal with the current problems. Their integration into the electrical system promotes distribution system operators to develop smart solutions in this field. Concerning the Smart Grids concept, the present work aims to provide answers to a wide range of questions for demand side management program using plug-in EVs charging strategies. The first section of this PhD project, presents a methodology to assess technical and economic impacts of EVs charging on Medium and Low voltage distribution networks. Afterwards, analyses about the competitive EVs load management ancillary services are conducted in the third chapter. By comparing potential and opportunities of each ones, three ancillary services for electricity market contribution were selected. In this context, a methodology for designing energy management strategies is proposed. The latter is applied to the selected ancillary services to assess the financial contribution of the developed strategies. Environmental aspects and Wind-to-Vehicle concept are also evaluated. Furthermore, thanks to a co-simulation interface, the interactions between supervision strategies and real distribution networks are analyzed. The last section presents a Hardware-in-the-loop demonstrator using a real time simulator, smart meters and EVs charging stations. Through experiments, communication constraints and Smart Grids principles are evaluated and validated
Sardouk, Ahmad. "Agrégation de données dans les réseaux de capteurs sans fil à base d'agents coopératifs." Troyes, 2010. http://www.theses.fr/2010TROY0013.
The main role of Wireless Sensor Network is to collect information from the environment by a high number of Sensor Nodes (SNs). The SNs have a lifetime limited by their batteries. Hence, SNs that ran out of battery will be out of the network and may create serious network partitioning and information loss problems. Thus, in order to maximize the WSN lifetime, it is important to minimize the power consumption of each SN and better manage the consumption of nodes that are in critical positions of the network. As the radio communication is the main power consumer, we propose a multi-agent based data aggregation solution, which reduces the amount of communicated information and hence reduces the power consumption of the SNs. We propose to implement in each node an agent that manages optimally the SN, processes locally its information and estimates their importance. The implemented agents cooperate together to eliminate the inter-SN redundancy and the useless information and to create a message summarizing the network’s important information. The agent manages the power consumption of each node according to its position in the network, the nodes density in its coverage zone, its residual battery and the importance of its current information. This management aims to balance the power consumption of the SNs and to maximize the life-time of SNs in critical positions to avoid the network partitioning
Gougeon, Adrien. "Optimisation d’un réseau dynamique et efficace en énergie servant à piloter la grille électrique." Electronic Thesis or Diss., Université de Rennes (2023-....), 2023. https://tel.archives-ouvertes.fr/tel-04086397.
In front of the challenges concerning the energy and environmental sectors, the electrical grid faces some limitations. A major issue of the current power network is the lack of communication and coordination between its actors to fully exploit its potential.To overcome those limitations, and offer new services to the actors of the electrical grid, we are moving toward the Smart Grid. The deployment of an additional infrastructure is necessary to enable the Smart Grid. This infrastructure, known as the Advanced Metering Infrastructure (AMI), aims to enhance the monitoring and communication capabilities of the actors of the electrical grid.The goal of this thesis is to quantify the performance degradation of some new services of the Smart Grid, due to the quality of service of the AMI. We explore several parameters of the communication infrastructure and observe through co-simulation how those parameters influence the efficiency of those services. One of the main objectives of the Smart Grid is to reduce energy consumption.In a second stage, we model the end-to-end energy consumption of an AMI at a large scale to assess its own consumption.The proposed co-simulation framework and consumption models are all license free
Sakr, Daniel. "Smart Grid deployment and use in a large-scale demonstrator of the Smart and Sustainable City (SunRise) : comprehensive analysis of the electrical consumption." Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10088/document.
The Smart City and Smart Grids constitute a great opportunity to meet the environmental challenges and to build inclusive cities that focus on the quality of life of citizens. However, these concepts are complex and recent. Their implementation requires learning from large experimentations. This work concerns this issue. It is carried within the large-scale demonstrator of the Smart City (SunRise) which is conducted at the Scientific Campus of the University of Lille. It includes three parts:The first part focuses on literature review of researches and achievements in the field of the Smart City and Smart Grids. It presents the city challenges such as the population growth, energy consumption, greenhouse emission and climate change. Then it discusses the digital mutation and its potential role in transforming the City into a Smart City and the conventional Electrical Grid into a Smart Grid. The second part describes the Electrical Grid of the Scientific Campus. It presents the project SunRise, that consists in the construction of a demonstrator of smart urban networks at the Scientific Campus, which is equivalent of a town with around 25 000 inhabitants. Then, it presents the electrical system of the campus as well as its management.The last part concerns analysis of the electrical consumption of the campus. It presents the methodology developed for data analysis including (i) record of the electrical consumption and transmission to the server, (ii) Data transmission, (iii) Data cleaning, (iv) construction of buildings’ consumption profiles and consumption analysis. This methodology is applied for analysis of the global consumption of the campus and three buildings
Moulichon, Audrey. "Conception d'un système adaptatif dynamique de "générateur synchrone virtuel" pour la stabilisation des micro-réseaux électriques à fort taux de pénétration d'énergie renouvelable." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT064.
The classical distributed energy resources (DER) supplying energy to microgrids (usually diesel generator-sets) are progressively supplanted by supplier based on renewable energy sources (RES). However, the intermittency of RES leads to major stability issues, especially in the context of microgrids, notably because these sources usually decrease the available inertia of the grid. Hence, the traditional control strategies for inverters, interfacing the various DERs connected to the microgrid, needs adapting.The virtual synchronous generator (VSG) is one of the most popular solution that can participate in increasing the microgrids inertia and that could be integrated into traditional stability studies because it presents similarities with a synchronous machine. As the VSG is still a recent concept, mostly considered for the DER integration in microgrid, various problematics remain unresolved (some of which are addressed in this manuscript). In addition, the different solutions that can be found in the literature do not consider the industrial and practical aspect of its development (also considered in this industrial thesis).This thesis is dedicated to the VSG-based inverters and their integration in microgrids with a high level of variable renewable energy penetration. This PhD have been carried out thanks to the cooperation between two laboratories, G2Elab and Gipsa-Lab, in collaboration with Schneider Electric and its R&D team, Power Conversion
Albu, Roxana. "Architecture de communication pour les réseaux d'instrumentation sans fil." Phd thesis, Institut National Polytechnique de Toulouse - INPT, 2011. http://tel.archives-ouvertes.fr/tel-00619443.
Vincent, Rémy. "Energy management strategies applied to photovoltaic-based residential microgrids for flexibility services purposes." Thesis, Nantes, 2020. http://www.theses.fr/2020NANT4025.
The rising share of renewable sources, residential consumers as well as novel energy transition policies call for new energy management strategies to deal with renewable energy sources uncertainty issues and to provide cost-competitive flexibility services. This thesis focuses on flexibility related usecases applied to residential microgrids. Presented sizing approach uses both mono and multiobjective particle swarm optimization to optimize both solar generation and storage taking into account cost competitiveness, user comfort and renewable energy penetration while respecting local regulations. First energy management approach compares 24 and 48h time-horizons for energy arbitrage and assess extended possibilities provided by a wider horizon. Second energy arbitrage approach focuses on energy injection accuracy in a bid-based market context. A novel auto-regressive short term solar irradiation forecast method suitable for peninsular weather is proposed and compared with a reference method. Regarding the sizing optimization, results showed that proposed optimization can generate bill savings for households. Nevertheless, due to current storage cost, off-grid operation is still an unreliable option regarding cost-competitiveness. Both presented energy management strategies showed profitability gains compared to their respective reference. To conclude, strategies showed costcompetitive operation and ability to mitigate supply and demand imbalances. Association of renewable energy and microgrids abilities for communities is an excellent opportunity for cleaner, more reliable and cheaper energy
N'Goran, Arnold. "Contrôle optimal et gestion énergétique d'une station d'énergie autonome par optimisation robuste." Thesis, Université Paris sciences et lettres, 2020. http://www.theses.fr/2020UPSLM050.
Power microgrid control involves solving a complex optimisation problem when it must deal with the intermittent, poorly forecasted production of renewable energy sources and with the short-term dynamics of the storage devices used to address intermittency issue. This thesis aims to shed light on the compared practical performance of optimization methods in control with the implementation of different strategies, exact or approximated, analytical or numerical, deterministic, stochastic or robust
Ali, Zazou Abdelkrim. "Conception d'un outil d'optimisation dynamique du schéma d'exploitation du réseau de distribution d'électricité de SRD." Thesis, Chasseneuil-du-Poitou, Ecole nationale supérieure de mécanique et d'aérotechnique, 2017. http://www.theses.fr/2017ESMA0010.
The French electrical distribution network was originally built to bring electricity from very large producers to consumers, but it has now become a place of multi-directional energy flows that rely on local production and consumption. Because of this new situation, the way of operating electrical networks needs to be renewed. In light of this, the local Distribution System Operator (SRO) of the French department Vienne and the different teams of the LIAS laboratory have worked together on the development of a distribution network configuration optimization tool. In this thesis the majority of the work was focused on the modeling part of the problem rather than on the development of new optimization methods. The industrial root of this project gave the opportunity to be very close to the reality of the available network data. Based on those observations,it was more consistent to use exact and precise optimization methods to solved simplified versions of the complex electrical network models.Thus a simple optimization model based on the minimum cost flow problem was developed, and a comparative study between the developed model and state of the art more complex one was led. This simple model was reformulated to become convex and quadratic and to reach better resolution time performances with the same solutions. This optimization problem was developed to take into account a time horizon factor into the optimization of the operation planning of the distribution network. The time horizon factor aim to represent the production and consumption variation over a selected period. Finally. because this model has to be integrated into a decision making helping tool that will be used by the DSO SRD several operational constraints were added into the optimization model. Several state of the art case studies arc presented to validate the model accuracy regarding existing methods. Simulation experiments were done on real networks data to show the applicability of the proposed optimization model over large scale case studies which correspond to the DSO SRO reality
Sbai, Hugo. "Système de vidéosurveillance intelligent et adaptatif, dans un environnement de type Fog/Cloud." Thesis, Lille, 2018. http://www.theses.fr/2018LIL1I018.
CCTV systems use sophisticated cameras (network cameras, smart cameras) and computer servers for video recording in a fully digital system. They often integrate hundreds of cameras generating a huge amount of data, far beyond human agent monitoring capabilities. One of the most important and modern challenges, in this field, is to scale an existing cloud-based video surveillance system with multiple heterogeneous smart cameras and adapt it to a Fog / Cloud architecture to improve performance without a significant cost overhead. Recently, FPGAs are becoming more and more present in FCIoT (FoG-Cloud-IoT) platform architectures. These components are characterized by dynamic and partial configuration modes, allowing platforms to quickly adapt themselves to changes resulting from an event, while increasing the available computing power. Today, such platforms present a certain number of serious scientific challenges, particularly in terms of deployment and positioning of FoGs. This thesis proposes a video surveillance model composed of plug & play smart cameras, equipped with dynamically reconfigurable FPGAs on a hierarchical FOG / CLOUD basis. In this highly dynamic and scalable system, both in terms of intelligent cameras (resources) and in terms of targets to track, we propose an automatic and optimized approach for camera authentication and their dynamic association with the FOG components of the system. The proposed approach also includes a methodology for an optimal allocation of hardware trackers to the electronic resources available in the system to maximize performance and minimize power consumption. All contributions have been validated with a real size prototype
Wu, Hongwei. "Étude et analyse globale de l’efficacité énergétique d’un micro-réseau urbain à courant continu." Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2386/document.
The object of the thesis is to study the power losses in an urbain DC microgrid in order to improve the energy efficiency. Noted that such a multi-source microgrid consist of several sources whose nature is different one from another, the static power converters are essential but they brings power losses. The power losses are quite variable in particular with the renewable energy source such as the photovoltaic panels. In the litteral works the converter efficiency is often treated as a constant, but experimental tests are carried out to show its variation. For the sake of study the power loss thoroughly, a state of art of the static converter is studied to develop a simple and fast estimation methode of power losses. Aiming at the tradeoff between the estimation accurancy and the calculation time, an averaged energy model is developped on the basis of the component datasheet. The experimental tests are carried out to validate the application of the model on the DC/DC and DC/AC converters used in the microgrid. Due to its simplicity, the model can be implemented in the real-time system. Thus the energy management strategies are proposed to interact with the variable efficiency on the high and low level control. These strategies are capable of shedding the powers in the microgrid with flexibility and accelerating the the convergency spped of control through the knowledge of power losses of each converter. The results show that the energy cost has decreased and the microgrid global efficiency is slightly improved
Correa, Florez Carlos Adrian. "Optimisation des flexibilités des « consommacteurs » dans le contexte des marchés d’électricité." Thesis, Paris Sciences et Lettres (ComUE), 2019. http://www.theses.fr/2019PSLEM011.
This thesis presents an optimization framework under uncertainty for the case in which an aggregator manages residential storage devices and renewable energy as sources of flexibility, participating directly in the day-ahead energy market and offering services to minimize operational costs. Residential flexibility assets are composed by batteries, electric water heaters and PV panels, which are optimally managed and controlled by an aggregator. The optimization model also considers battery’s cycling aging cost which allows capturing the non-linear relation between depth of discharge and total life cycling. The following sources of uncertainty are considered: electrical and thermal demand, PV production and energy prices. These uncertainties are included in the mathematical model by means of robust optimization theory and a methodology based on Pareto-optimality is proposed to detect the solutions with the best trade-off between cost and risk. In addition, this thesis presents a local flexibility management strategy, which is based on two products: 1) flexibility bids into a local market; and 2) local constraint support for the Distribution System Operator (DSO) in the form of maximum allowed net power and net ramping rate. An adjustable robust optimization model is proposed for coordinated management of resources and allows to demonstrate that the strategic bidding framework is robust enough to enable coordinated participation in three different marketplaces: energy, local flexibility and bilateral trading with the DSO
Bridier, Laurent. "Modélisation et optimisation d'un système de stockage couplé à une production électrique renouvelable intermittente." Thesis, La Réunion, 2016. http://www.theses.fr/2016LARE0038/document.
This thesis aims at presenting an optimal management and sizing of an Energy Storage System (ESS) paired up with Intermittent Renewable Energy Sources (IReN). Firstly, wedeveloped a technico-economic model of the system which is associated with three typical scenarios of utility grid power supply: hourly smoothing based on a one-day-ahead forecast (S1), guaranteed power supply (S2) and combined scenarios (S3). This model takes the form of a large-scale non-linear optimization program. Secondly, four heuristic strategies are assessed and lead to an optimized management of the power output with storage according to the reliability, productivity, efficiency and profitability criteria. This ESS optimized management is called “Adaptive Storage Operation” (ASO). When compared to a mixed integer linear program (MILP), this optimized operation that is practicable under operational conditions gives rapidly near-optimal results. Finally, we use the ASO in ESS optimal sizing for each renewable energy: wind, wave and solar (PV). We determine the minimal sizing that complies with each scenario, by inferring the failure rate, the viable feed-in tariff of the energy, and the corresponding compliant, lost or missing energies. We also perform sensitivity analysis which highlights the importance of the ESS efficiency and of the forecasting accuracy and the strong influence of the hybridization of renewables on ESS technico-economic sizing
Nasr, Sarah. "Optimisation d’un réseau ferroviaire à l’aide de solutions smart-grids." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLC026/document.
Increasing energy efficiency is nowadays a requirement in all technical fields. The reduction of global consumption, thus carbon footprint, has become the world's priority, as for example, the climate and energy package of the European Union.Railways' share of energy consumption is one of the highest. Electrical solutions are developed in order to reduce these systems' losses, optimize their consumption and reduce global energy bill. Given their diversity, two main categories are considered in this study. The first one consists of urban lines that are characterized by a DC electrification and a relatively dense traffic. In this case, braking energy burned in trains' rheostats represents the main share of losses. The proposed solution is to recuperate this energy using a DC micro-grid implemented in a passengers' station. It allows an interaction with the non-railway electrical environment, for example, re-using this energy in charging electric hybrid buses parked nearby. The excess of braking energy is recuperated using a DC/DC converter and injected into a DC busbar. A second DC/DC converter will store it in a hybrid storage system. It will then serve to charge the buses connected to the DC busbar. The micro-grid is also connected to the grid using a low power AC/DC converter. A power management system ensures optimizing power flow between different components. An energy evaluation showed that this solution is a good Investment especially because no contract is needed with the energy provider. The system's stability is studied and a stabilizing command, the backstepping, is applied. This new smart station allows railways to communicate, energetically, with its evolving environment.The second category is suburban and high speed lines that are AC electrified. Contrarily to the previous case, braking energy is reinjected to the upper grid through substations. Therefore, a second solution is to reduce global energy consumption by optimizing trains' speed profiles and timetable's synchronization. It is done using a differential evolution algorithm. Each speed profile is divided into zones to which are associated driving parameters. The optimization of the latter allowed generating new optimal speed profiles and a less-consuming timetable. Simulation results showed that it is possible to make important energy savings while respecting train's punctuality
Saez, de ibarra martinez de contrasta Andoni. "Dimensionnement et contrôle-commande optimisé des systèmes de stockage énergétique pour la participation au marché de l'électricité des parcs photovoltaïques intelligents." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAT057/document.
The present PhD deals with the integration of intelligent photovoltaic (IPV) power plants in the electricity markets in an environment subject to free competition. The IPV power plants are those that include energy storage systems to reduce the variability and to provide the entire group a controllability increase. These technical objectives are obtained thanks to the bidirectional exchanging and storing capability that the storage system contributes to, in this case, battery energy storage system (BESS). In order to obtain the maximum profitability of the BESS, the sizing must be optimized together with the control strategy that the BESS will be operated with. In the present PhD, once the most performing battery energy storage technology has been selected, the lithium-ion technology, an innovative IPV power plant electricity market participation process is proposed which optimizes both the sizing and the energy management strategy in the same optimization step. This optimization process together with the electricity market participation has been applied in a real case study, confirming that this procedure permits to maximize the economic profitability of this type of generation
Mohamed, Amgad. "Modélisation et contrôle des turbines hydrauliques pour l'intégration des sources d'énergies renouvelabless." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT027.
Recently, renewable energy resources such as, wind and solar energy, have become integral parts of electric grids as clean energy alternatives to fossil fuels. However, the quality of production of such resources of energy depends on different uncertain factors, for instance, weather conditions. Therefore, dealing with the intermittent nature of renewable energy resources is one of the main challenges when using them on a larger scale.A possible solution to reduce the effects of energy resources intermittency on energy production and grid's stability, is to use energy storage technologies. Pumped storage power plants (PSPs) seem to be the unique clean storage method that can be used to counteract the intermittent nature of wind and solar energy. PSPs make use of pumps-turbines which are capable of working as pumps to store excess electric energy in the grid, and as turbines to generate electric energy, when more electric energy is needed. Thus, PSPs help in stabilizing the grid in the presence of intermittent renewable energy resources.The emphasis in this work is on turbine start-up operating mode for PSPs. In PSPs, the start-up operating mode is usually visited multiple times, as a result of switching back and forth between pumping and turbine modes. Thus, enhancing the performance of the speed governors used for starting-up becomes more important when dealing with PSPs to enable a rapid voltage recovery.This PhD thesis is part of the multidisciplinary INNOVHYDRO project that includes different laboratories and enterprises such as, GIPSA-lab where this thesis was prepared, G2Elab, GE and EDF.In this thesis, a controller architecture that takes into account the computational limitations of existing microcontrollers in use at GE, is proposed. It provides a solution to the problem of fast turbine start-up, while avoiding the excitation of sharp pressure oscillations. In addition, torque constraints are easily integrated to achieve smoother start-up, which reduces the fatigue of the mechanical components, resulting from repetitive start-up of turbines.Different approaches are proposed to tune the controller gains, while taking into account the nonlinear dynamics of the actuator used at GE. To begin with, a tuning methodology is outlined to guarantee the asymptotic stability and the closed-loop performance, while minimizing the guaranteed upper bound on the output tracking error. In addition, a systematic optimization approach is developed to select the controller gains to minimize time needed to get a stable start-up, while respecting maximum torque constraints. Moreover, randomized algorithms are used to choose the controller parameters such that robustness certificates are obtained on the resulting controller.Furthermore, a simulator has been developed for hydraulic power plants and used to test the proposed controller. The simulator constitutes of a system of continuous differential equations, which systematically model the behavior of the different components of the hydraulic power plant such as, penstocks, tunnels, reservoirs and surge tanks. In addition, the nonlinear behavior and unstable regions 'S-characteristics' of hydraulic turbines, usually modeled by Hill charts, are successfully taken into consideration. Moreover, the actuator's nonlinear dynamics are included in the overall mathematical model
HU, Zheng. "Auto-configuration, supervision et contrôle d'entités physiques par l'intermédiaire de réseaux de capteurs et actionneurs." Phd thesis, Université Claude Bernard - Lyon I, 2014. http://tel.archives-ouvertes.fr/tel-00948995.
Amaripadath, Deepak. "Development of Tools for Accurate Study of Supraharmonic Emissions in Smart Grids." Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCA016.
As the worldwide concern for the climate change and its effects are growing, the governments are forced to make strong decisions in favour of the implementation of the smart electrical grids. However, the success of these actions strongly depends on meeting the certain requirements of the electricity system raised by the quality of the energy supplied and the means to assess it. The smart electrical networks have to tackle the challenges raised by the increasing uptake of the renewable energy sources, such as the photovoltaic (PV), wind, etc. and the equipment, such as photovoltaic inverters (PVI), electric vehicle chargers (EVC), etc. This introduces a complex dynamic operating environment for the distribution system. The distortions coming from the new generation and load equipment are generally larger and less regular than those due to the traditional generation and load equipment, making the power and energy measurements difficult to perform.In this context, the thesis aims to quantify and reproduce the supraharmonic emissions in the frequency range of 2 to 150 kHz. Therefore, the existing literature on the supraharmonic emissions in the frequency range of 2 to 150 kHz is studied. The 4-channel measurement system is designed and implemented for the measurement of the fundamental and supraharmonic components of the voltage and current waveforms in the frequency range of 2 to 150 kHz in the electrical network. The measurements are carried out in the Concept Grid platform. The individual equipment characterization and electrical network tests are carried out here. The waveforms acquired during the measurement campaigns are processed mathematically using the fast Fourier transform (FFT) algorithm and statistically using the analysis of variance (ANOVA) algorithm. The mathematical and statistical processing of the acquired waveforms helps to determine the individual effects and interactions of the different parameters in the generation of the supraharmonic emissions in the electrical network. The various parameters, such as the primary and secondary emissions, effects of the cable length, effects of the sudden addition and removal of the load equipment are also studied.The thesis describes the design of the complex waveform platform, which can be used for the laboratory testing and the characterization of the power quality analyzers (PQA) in the frequency range of 2 to 150 kHz. In the electrical networks, the waveform platform can be used to measure the supraharmonic emissions in the frequency range of 2 to 150 kHz. The software architecture of the waveform platform is described here. In addition, the paper explains the hardware design of the waveform platform. It also includes the laboratory and electrical network applications of the waveform platform. The laboratory setup for the characterization of the PQA and the measurement schema for the electrical network waveforms are also depicted here. The uncertainty budget for the waveform platform is calculated considering the various factors, such as the cable length, noise, etc. are discussed in the thesis. Finally, the PQA is characterized in the frequency range of 2 to 150 kHz with respect to the waveform platform for varying emission amplitudes
Ben, Romdhane Lamia. "A Multi-Agent Architecture Framework for Energy Systems Design." Electronic Thesis or Diss., université Paris-Saclay, 2020. http://www.theses.fr/2020UPASS141.
In recent years, multi-agent systems (MAS) have emerged as one of the most promising technologies for the design and development of intelligent energy systems, also known as Smart-Grid. However, the use of agent technology in systems engineering to model, control and simulate energy system’ behavior still faces many challenges: methodological; technical (generally related to MAS engineering); standardization and architectural exploration (specifically related to the Smart Grid domain). This thesis proposes an architectural framework in accordance with ISO 42010, containing all the conventions, principles and practices for the description of multi-agent architectures established in the field of Smart-Grids, as an adequate solution to solve the problems mentioned above. The architectural framework relies on Model Driven Engineering (MDE) to solve technical and methodological problems. This framework is supported by a methodology that adheres the use of agent and energy standards in the MAS analysis and design phases. The framework is based on a multi-agent architecture style evaluation approach to select the most appropriate style to meet non-functional requirements related to a specific application domain. In addition, a platform-independent agent modeling language was proposed to model MASs and analyze the developed models to verify their compliance with the selected MAS architecture style. The approach was prototyped in a Model Driven Engineering environment and evaluated on a representative application case from the Smarts-Grids domain
Hu, Zheng. "Auto-configuration, supervision et contrôle d'entités physiques par l'intermédiaire de réseaux de capteurs et actionneurs." Thesis, Lyon 1, 2014. http://www.theses.fr/2014LYO10001/document.
The physical entities which are taken into account by Machine to Machine (M2M) telecom applications are more and more heterogeneous. The challenge addressed by our research is the automatic integration and configuration of all these types of physical entities in M2M systems, with a homogeneous solution that generalizes self-configuration approaches used for networked digital devices. This thesis presents a general theoretical framework and basic mechanisms for the identification and configuration of such physical entity models in distributed embedded information systems. Our approach deals jointly with equipment and space entities encompassing the ”Internet of Things” (IoT) and ”interactive environment” viewpoints in a renewed interpretation of ambient intelligence. This work has been motivated initially by home energy management applications, trying to integrate into the Home Area Network all home entities that play a role in energy management, but do not have a networked interface of their own. This corresponds to a qualitative extension of the perimeter of the Home Area Network. This integration is achieved in a way similar to what is done for state of the art digital devices, through a spontaneous discovery and configuration mechanism, with the following stages: detection of the presence of a physical entity by analyzing the coincidence of significant events detected by sensors; selection of the first generic model corresponding to the detected physical entity from a reference ontology, on the basis of received sensors data; creation of a software component representing the detected physical entity, based on the selected model, associated with relevant sensors and actuators; provision of application interface for monitoring and control of the target entity through this intermediate software component; iterative update of the identified entity model on the basis of data from associated sensors. The proposed approach has been validated and implemented in home environments, but it is intended to be generalized and expanded to environments such as buildings or cities, offering a similarly shared infrastructure for all M2M applications in these environments
Julian, Maya. "Evaluation and Optimization of Strategies to introduce Renewable Energy into Electricity Generation for Housing." Electronic Thesis or Diss., Université de Lorraine, 2021. http://www.theses.fr/2021LORR0365.
Nowadays where oil prices become considerably expensive and CO2 emissions increase rapidly, grid operation is becoming even more multidimensional given the environmental policies that are enforced. Given the set of goals stemming from the Kyoto agreement and initiatives like the 20/20/20 European agreement, tight schedules and boundaries are dictated, for all the participating countries in order to consistently reduce their Greenhouse Gas (GHG) emissions while integrating more renewable energy and substituting older and pollutant heavy production technologies with newer and more eco-friendly ones. Thus, the whole restructuring of the energy systems are focused in two fronts in order to achieve the mentioned goals, 'cleaner' energy integration and energy efficiency. In order to achieve cleaner energy, attention has been drawn to the highly promising RES, Combined Heat and Power (CHP) units and alternative fuels like natural gas units and Fuel Cells (FC). The installation of more and more units of Dispersed Generation-DG (PV, WT, FC, Micro_CHP, etc.) close to consumers leads to a new era for the Energy Systems. Microgrids could come into play to aid the network through CO2 emission reduction while increasing their efficiency through local generation. Microgrids are defined as Low Voltage (LV), or in some cases Medium Voltage (MV), networks with DG sources, together with storage devices and controllable loads (e.g. water heaters, air conditioning) with a total installed capacity in the range of few kWs to couple of MWs. The unique feature of Microgrids is that, although they operate mostly interconnected to the upper level voltage distribution network, they can be automatically transferred to islanded mode in case of faults in the upstream network. This doctoral thesis aims to develop methodologies and analysis techniques for the quantification of the DG’s advantages in Microgrids scheme, giving emphasis in environmental issues and constraints (e.g. various carbon tax rates, CO2, SO2, NOx constraints, emission factors of production units, e.t.c.). Moreover, suitable calculation software for minimizing the operational cost in the Microgrid (in which variations in the pricing policies are applied) will also be developed. So, by evaluating comparable scenarios, the environmental and pricing policies that contain greater viability and realization potentiality will be presented. In addition, given the above parameters, an economic-environmental hourly dispatch problem is formulated in order to optimally produce the hourly generation schedules of the Microgrid's DG. Matlab software will be used to perform the proposed simulations (Lagrange Method – fmincon function)
Gouin, Victor. "Évaluation de l’impact du Smart Grid sur les pratiques de planification en cas d’insertion de production décentralisée et de charges flexibles." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAT097/document.
The Smart Grids are the combination of electrical networks and new information and communication technologies. They deal with a change of paradigms that are the insertion of distributed generation and the development of new forms of consumption, such as electric vehicles and prosumers. These changes induce many constraints on networks both aging and historically not sized for this context. This thesis studies the impact of these paradigms on the rules for electrical distribution networks planning. A first tool using an adapted simulated annealing algorithm and methods from graph theory was developed to size the networks at low cost, according to the usual rules for planning. Secondly, a methodology combining a Monte Carlo approach and the construction of annual load profiles was proposed to analyze the impact of distributed generation and electric vehicles in an environment subject to uncertainties. The third stage of the work was to implement advanced distribution automations as an alternative to reinforcement, which is very expensive. This part is focused on demand side management. Finally, a new operational planning combining the previous developed tools was created to move towards the planning of the Smart Grids
Nguyen, Ngac Ky. "Approches neuromimétiques pour l'identification et la commande des systèmes électriques : application au filtrage actif et aux actionneurs synchrones." Phd thesis, Université de Haute Alsace - Mulhouse, 2010. http://tel.archives-ouvertes.fr/tel-00615491.
Bai, Wenshuai. "DC Microgrid optimized energy management and real-time control of power systems for grid-connected and off-grid operating modes." Thesis, Compiègne, 2021. http://www.theses.fr/2021COMP2586.
This thesis focus on the research of the DC microgrid following two operation models: grid-connected mode, and off-grid mode including the islanded and isolated modes. The aim of this thesis is to propose a DC microgrid combining the advantages of the grid-connected or the off-grid mode, which named full DC microgrid. ln the full DC microgrid, the renewable energy sources, storage, and public grid are included, and the back-up sources also applied to reduce the load shedding. ln the full DC microgrid, a supervisory system is proposed to manage the power. The real-time power management in the operational layer of the supervisory system can keep the power balance. ln the optimization layer of the supervisory system, the day-ahead optimization is proposed to achieve the global minimal operation cost. The simulation results show that the full DC microgrid combines both advantages of the grid-connected and the off-grid mode to minimize the operating cost. Then, the supervisory system considers the dynamic efficiency of the converter to solve the problem that the power quality of the microgrid is degraded due to the unstable DC bus voltage caused by the inaccurate power control. The simulation results show that considering the dynamic efficiency of the converter in the operational layer of the supervisory system, the fluctuation of the DC bus voltage can be reduced. Regarding the importance of the PV prediction for the day-ahead optimization, two prediction modes are studied and compared to give a robust PV prediction power. The results are that the two models almost have the same results
Lefort, Romain. "Contribution des technologies CPL et sans fil à la supervision des réseaux de distribution d'électricité." Thesis, Poitiers, 2015. http://www.theses.fr/2015POIT2253/document.
Establishing a supervisory infrastructure allows a better smart management than an expensive strengthening of distribution network to respond to new constraints at the energies control (Consumption, REN, EV ...). To transmit data, Power Line Communication (PLC) technologies present an advantage in this context. In fact, it enables a superposition of High Frequency (HF) signals on electrical signal 50/60 Hz. However, electric networks have not been developed to this application because of difficult propagation conditions. This research work makes a contribution to develop a simulation platform in objective to transmit data to 1 MHz. In first time, each network element is studied singly and in second time, together, to estimate "Outdoor PLC" transmission performance. The first element studied is the networks variation in function of frequency and time. Several 24h disturbance measurements on LV customers are presented. The second element is the transformers which established connection between Medium Voltage (MV) and Low Voltage (LV). The proposed modeling method is based on a "lumped model" and a "black box model". These models are applied to a 100 kVA H61 transformer most commonly used by French distribution system operator in rural and suburban networks. The third element is the power line used in MV and LV networks. The proposed modeling method is based on a "cascaded model" from the theory of transmission line. This model is applied to one power line used in LV underground network. Each model is obtained from various impedance measurements. To complete, an introductory study on mobile radio communication is performed to remote network distribution
Sa'ad, Aisha. "Developing integrated maintenance strategies for renewable energy sources based on analytical methods and artificial intelligence (AI) : comparisons and case study." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0080.
The development of renewable energy, especially solar and wind energy, over the recent years has gained global attention as an alternative method of generating energy experiencing exceptional growth in its production. In The Global Energy report, global solar energy is expected to have reached a cumulative capacity of 1TW while the wind energy is expected to have multiplied up to 3 to 4 times from mega production in the year 2020. This increase in the solar and wind power implies very significant financial investments. However, with this huge investment potential and significant increase in generation capacity, there is an additional, often overlooked responsibility: managing the power plants to ensure the lowest total life cycle cost (Life Cycle Cost). Like any standard production system, renewable energy (solar and wind energy in our case) generation components are subject to random failure, which interrupts production and supply of demand. Maintenance is identified as a major cause of accidents, lack of technical know-how of an equipment and the absence of a good maintenance routine plan. As part of the efforts to improve the efficiency and performance of renewable energy power plants, we propose models to optimize the power production and maintenance of our selected case studies (Sokoto solar plant and Katsina wind farm). In this regard, we developed new integrated maintenance policies integrated with production of the energy production from solar and wind energy systems. The preventive maintenance strategy adopted in this thesis is perfect maintenance strategy on the selected components for maintenance and an imperfect selective maintenance on the system (solar PV and wind turbine). Battery shortage in case of under-production and maintenance losses are challenges considered in this study. The methodology we developed entails solving the problem of energy production and maintenance optimization by using the theoretical method as well as machine learning method (ANN and SVM) in order to satisfy a random demand of energy during a finite horizon. We also studied the influence of environmental and operational condition of the systems and then validated the models by numerical examples and sensitivity studies proving the robustness of the developed models
Desta, Alemayehu. "Energy Supply and Demand Side Management in Industrial Microgrid Context." Thesis, Paris Est, 2017. http://www.theses.fr/2017PESC1234/document.
Due to increased energy costs and environmental concerns such as elevated carbon footprints, centralized power generation systems are restructuring themselves to reap benefits of distributed generation in order to meet the ever growing energy demands. Microgrids are considered as a possible solution to deploy distributed generation which includes Distributed Energy Resources (DERs) (e.g., solar, wind, battery, etc). In this thesis, we are interested in addressing energy management challenges in an industrial microgrid where energy loads consist of industrial processes. Our plan of attack is to divide the microgrid energy management into supply and demand sides.In supply side, the challenges include modeling of power generations and smoothing out fluctuations of the DERs. To model power generations, we propose amodel based on service curve concepts of Network Calculus (NC). Using this mathematical tool, we determine a minimum amount of power the DERs can generate and aggregating them will give us total power production in the microgrid. After that, if there is an imbalance between energy supply and demand, we put forward different strategies to minimize energy procurement costs. Based on real power consumption data of an industrial site located in France, significant cost savings can be made by adopting the strategies. In this thesis, we also study how to mitigate the effects of power fluctuations of DERs in conjunction with Energy Storage Systems (ESSs). For this purpose, we propose a Gaussian-based smoothing algorithm and compare it with state-of-the-art smoothing algorithms. We found out that the proposed algorithm uses less battery size for smoothing purposes when compared to other algorithms. To this end, we are also interested in investigating effects of allowable range of fluctuations on battery sizes.In demand side, the aim is to reduce energy costs through Demand Side Management (DSM) approaches such as Demand Response (DR) and Energy Efficiency (EE). As industrial processes are power-hungry consumers, a small power consumption reduction using the DSM approaches could translate into crucial savings. This thesis focuses on DR approach that can leverage time varying electricity prices to move energy demands from peak to off-peak hours. To attain this goal, we rely on a queuing theory-based model to characterize temporal behaviors (arrival and departure of jobs) of a manufacturing system. After defining job arrival and departure processes, an effective utilization function is used to predict workstation’s (or machine’s) behavior in temporal domain that can show its status (working or idle) at any time. Taking the status of every machine in a production line as an input, we also propose a DR scheduling algorithm that adapts power consumption of a production line to available power and production rate constraints. The algorithm is coded using Deterministic Finite State Machine (DFSM) in which state transitions happen by inserting a job (or not inserting) at conveyor input. We provide conditions for existence of feasible schedules and conditions to accept DR requests positively.To verify analytical computations on the queuing part, we have enhanced Objective Modular Network Testbed in C++ (OMNET++) discrete event simulator for fitting it to our needs. We modified various libraries in OMNET++ to add machine and conveyor modules. In this thesis, we also setup a testbed to experiment with a smart DR protocol called Open Automated Demand Response (OpenADR) that enables energy providers (e.g., utility grid) to ask consumers to reduce their power consumption for a given time. The objective is to explore how to implement our DR scheduling algorithm on top of OpenADR
Morales, jadan Diego. "Développement de la gestion optimale de l'énergie électrique dans les îles Galápagos vers les Reséaux Intelligents." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAT106/document.
The Galápagos Islands are an archipelago of volcanic islands located in the Pacific Ocean, 926 km west of continental Ecuador, of which they are a part. Since 1978, Galapagos Islands are accepted as Heritage World, due to the growth of the population, there are several social, economic and environmental problems, which endanger the environment conservation of the Islands.In this context, the Ecuadorian government desires to preserve its ecological heritage. Hence, with the participation of several stakeholders mainly the Ministry of Energy and Renewable Energy, it is releasing a lot of initiatives. In order to improve the general services that are provided in the islands, this goal will be achieved by means of reducing fossil fuel consumption and therefore CO2 emissions. Thus, this thesis has analyzed the impact of new services on the grid such as the mandatory replacement of conventional vehicles and cookers for efficient ones and to propose solutions for reducing negative issues originated on the network. Also, a strong integration of distributed generation is considered in the analysis.In addition, innovative solutions for both low and medium voltage have been designed and tested for improving the electrical service without affecting the environment and conserving this world heritage. For instance, a smart DSM program composed of Time of Use scheme combined with Demand Response has shown interesting results, the installation of a Battery Energy Storage System has been studied as well; the results in Medium Voltage are promising. An Automatic Phase Switching system is adapted like a solution for reducing unbalance in low voltage with impressive results. The deployment of reclosers has demonstrated a considerable improvement in the reliability with a Return on Investment very short.Considering the Information and Communication Technologies a key piece to deploy Smart Grids, the communication architecture of the Neighbor, Field and Home Area Networks is addressed. As last, an Energy Management System for performing optimal energy management within Galapagos is designed. All these studies have a significant challenge: the optimal management of electricity of isolated grid with zero fossil energy
Leukam, Lako Franklin. "Protection des données à caractère personnel pour les services énergétiques." Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAS004.
Smart grids are important bricks in the fight against climate change. Smart grids allow the massive introduction of renewable energies, which are intermittent, while guaranteeing grid stability, i.e., ensuring a real-time balance between demand and production in the power grid. The management of grid stability is possible thanks to smart meters installed in households, allowing the distribution system operator to collect consumption/production data from consumers/producers at a time step of up to 10 min in France. This real-time consumption data enables to provide new energy services, such as customer consumption forecasts or demand response. Demand response services help to avoid consumption peaks in a neighborhood by ensuring that, at all times, users' consumption does not exceed the maximum power of the local grid. However, the collection of users' consumptions is a key privacy concern. Indeed, individual consumption data reflect the use of all electric appliances by inhabitants in a household over time, and enable to deduce the behaviors, activities, age or preferences of the inhabitants. This thesis aims to propose new energy services, while protecting the privacy of consumers. We propose five contributions that relate to two themes:1- The transformation of a demand response algorithm by making it privacy friendly. This transformation uses secure multiparty computation, allowing to compute an aggregate, such as a sum of users’ consumption, without disclosing any individual consumption.2- The publication of sum of users' consumption while preserving privacy and good utility. This publication uses differential privacy, ensuring that the publication of the sum does not indirectly reveal individual users' consumption. Among other energy services, these sums of consumption enable to perform consumption forecasts
Attoue, Nivine. "Use of Smart Technology for heating energy optimization in buildings : experimental and numerical developments for indoor temperature forecasting." Thesis, Lille 1, 2019. http://www.theses.fr/2019LIL1I021/document.
With the highly developing concerns about the future of energy resources, the optimization of energy consumption becomes a must in all sectors. A lot of research was dedicated to buildings regarding that they constitute the highest energy consuming sector mainly because of their heating needs. Technologies have been improved and several methods are proposed for energy consumption optimization. Energy saving procedures can be applied through innovative control and management strategies. The objective of this thesis is to introduce the smart concept in the building system to reduce the energy consumption, as well as to improve comfort conditions and users’ satisfaction. The study aims to develop a model that makes it possible to predict thermal behavior of buildings. The thesis proposes a methodology based on the selection of pertinent input parameters, after a relevance analysis of a large set of input parameters, for the development of a simplified artificial neural network (ANN) model, used for indoor temperature forecasting. This model can be easily used in the optimal regulation of buildings’ energy devices. The smart domain needs an automated process to understand the buildings’ dynamics and to describe its characteristics. Such strategies are well described using reduced thermal models. Thus, the thesis presents a preliminary study for the generation of an automated process to determine short term indoor temperature prediction and buildings characteristics based on grey-box modeling. This study is based on a methodology capable of finding the most reliable set of data that describes the best the building’s dynamics. The study shows that the most performant order for reduced-models is governed by the dynamics of the collected data used
Buzila, Petronela-Valeria. "Gestion énergétique optimale des installations fixes de traction électrique ferroviaire hybrides." Thesis, Lille 1, 2015. http://www.theses.fr/2015LIL10084/document.
In railway traffic increasing and electricity market liberalization context, railway actors are determined to consider innovative solutions to handle the increasing energy demand for electrical traction. One of the solution concerns the integration of decentralized production and energy storage systems in the railway power substations (RPS). The present research work aims to contribute to the design of a sizing and intelligent energy management tool for the hybrid RPS (HRPS). In the first part of the dissertation, a methodology for the techno-economical design of the HRPS is described. From a HRPS generic architecture, an optimization approach is proposed by considering cycles of dimensional and system control variables. Furthermore, an energy flow model permits to apply the optimization methodology on a study case and to compare different optimization scenarios in order to analyze the sizing and optimal planning of electrical sources and loads for a typical day. After sizing the HRPS, an energy management methodology is developed in order to achieve energy, economic and environmental objectives at different time levels of HRPS supervision. Several energy management scenarios are evaluated in simulation through adapted system gain indicators. An optimization study of the supervision parameters provides additional answers concerning the influence of the system design on its management strategy. Eventually, the HRPS energy management robustness is analyzed during an experimental setup phase at laboratory power scale
Zayene, Mariem. "Cooperative data exchange for wireless networks : Delay-aware and energy-efficient approaches." Thesis, Limoges, 2019. http://www.theses.fr/2019LIMO0033/document.
With significantly growing number of smart low-power devices during recent years, the issue of energy efficiency has taken an increasingly essential role in the communication systems’ design. This thesis aims at designing distributed and energy efficient transmission schemes for wireless networks using game theory and instantly decodable network coding (IDNC) which is a promising network coding subclass. We study the cooperative data exchange (CDE) scenario in which all devices cooperate with each other by exchanging network coded packets until all of them receive all the required information. In fact, enabling the IDNC-based CDE setting brings several challenges such us how to extend the network lifetime and how to reduce the number of transmissions in order to satisfy urgent delay requirements. Therefore, unlike most of existing works concerning IDNC, we focus not only on the decoding delay, but also the consumed energy. First, we investigate the IDNC-based CDE problem within small fully connected networks across energy-constrained devices and model the problem using the cooperative game theory in partition form. We propose a distributed merge-and-split algorithm to allow the wireless nodes to self-organize into independent disjoint coalitions in a distributed manner. The proposed algorithm guarantees reduced energy consumption and minimizes the delay in the resulting clustered network structure. We do not only consider the transmission energy, but also the computational energy consumption. Furthermore, we focus on the mobility issue and we analyse how, in the proposed framework, nodes can adapt to the dynamic topology of the network. Thereafter, we study the IDNC-based CDE problem within large-scale partially connected networks. We considerate that each player uses no longer his maximum transmission power, rather, he controls his transmission range dynamically. In fact, we investigate multi-hop CDE using the IDNC at decentralized wireless nodes. In such model, we focus on how these wireless nodes can cooperate in limited transmission ranges without increasing the IDNC delay nor their energy consumption. For that purpose, we model the problem using a two-stage game theoretical framework. We first model the power control problem using non-cooperative game theory where users jointly choose their desired transmission power selfishly in order to reduce their energy consumption and their IDNC delay. The optimal solution of this game allows the players at the next stage to cooperate with each other through limited transmission ranges using cooperative game theory in partition form. Thereafter, a distributed multihop merge-and-split algorithm is defined to form coalitions where players maximize their utilities in terms of decoding delays and energy consumption. The solution of the proposed framework determines a stable feasible partition for the wireless nodes with reduced interference and reasonable complexity. We demonstrate that the co-operation between nodes in the multihop cooperative scheme achieves a significant minimization of the energy consumption with respect to the most stable cooperative scheme in maximum transmission range without hurting the IDNC delay
Yassuda, Yamashita Damiela. "Hierarchical Control for Building Microgrids." Thesis, Poitiers, 2021. http://www.theses.fr/2021POIT2267.
Representing more than one-third of global electricity consumption, buildings undergo the most important sector capable of reducing greenhouse gas emissions and promote the share of Renewable Energy Sources (RES). The integrated RES and electric energy storage system in buildings can assist the energy transition toward a low-carbon electricity system while allowing end-energy consumers to benefit from clean energy. Despite its valuable advantages, this innovative distributed Building Microgrids (BM) topology requires significant changes in the current electric grid, which is highly dependent on grid energy policies and technology breakthroughs.The complexity of designing a robust Energy Management System (EMS) capable of managing all electric components inside the microgrid efficiently without harming the main grid stability is one of the greatest challenge in the development of BM. To mitigate the harmful effects of unpredictable grid actors, the concept of self-consumption has been increasingly adopted. Nonetheless, further technical-economic analysis is needed to optimally manage the energy storage systems to attain higher marks of self-consumption.Faceing these issues, the purpose of this doctoral thesis is to propose a complete framework for designing a building EMS for microgrids installed in buildings capable of maximising the self-consumption rate at minimum operating cost. Among all possible control architectures, the hierarchical structure has proved effective to handle conflicting goals that are not in the same timeframe. Hence, a Hierarchical Model Predictive (HMPC) control structure was adopted to address the uncertainties in the power imbalance as well as the trade-off between costs and compliance with the French grid code.Considering that buildings are not homogeneous and require solutions tailored to their specific conditions, the proposed controller was enhanced by two data-driven modules. The first data-driven algorithm is to handle inaccuracies in HMPC internal models. Without needing to tune any parameter, this algorithm can enhance the accuracy of the battery model up to three times and improve up to ten times the precision of the hydrogen storage model. This makes the building EMS more flexible and less dependent on pre-modelling steps.The second data-oriented algorithm determines autonomously adequate parameters to HMPC to relieve the trade-off between economic and energy aspects. Relying only on power imbalance data analysis and local measurements, the proposed hierarchical controller determines which energy storage device must run daily based on the estimation of the annual self-consumption rate and the annual microgrid operating cost. These estimations decrease microgrid expenditure because it avoids grid penalties regarding the requirements of annual self-consumption and reduces the degradation and maintenance of energy storage devices.The proposed EMS also demonstrated being capable of exploiting the potentials of shifting in time the charging of batteries of plug-in electric vehicles. The simulation confirmed that the proposed controller preferably charges electric vehicles’ batteries at periods of energy surplus and discharges them during periods of energy deficit, leading the building microgrid to reduce grid energy exchange. The results also showed that electric vehicle batteries' contribution depends on the size of the vehicle parking, their arrival and departure time, and the building’s net power imbalance profile. In conclusion, through simulations using the dataset of both public and residential buildings, the proposed hierarchical building EMS proved its effectiveness to handle different kinds of energy storage devices and foster the development of forthcoming building microgrids
Castro, Flores Jose Fiacro. "Low-temperature based thermal micro-grids : operation and performance assessments." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2018. http://www.theses.fr/2018IMTA0084/document.
Energy use in the urban environment is vital for the proper functioning of our society, and in particular, comfort heating –and cooling– is a central element of our energy system that is often taken for granted. Within this context, district energy systems and especially, district heating (DH) systems must evolve to adapt to the upcoming decades-long transition towards a sustainable energy system. This dissertation seeks to introduce, discuss, and asses from a techno-economic perspective, the concept of low-temperature based thermal micro-grids (subnets) as active distribution thermal networks. For this purpose, a mixed methodological approach based on analytical simulation for the assessment of alternatives is developed and discussed to evaluate a set of technologies. Key findings of this research include: an updated and improved model of aggregated heat loads; the identification of differences in load and temperature patterns for certain LT subnets; the analysis of benefits and drawbacks of active substations with distributed heat sources and/or storage; and the impact of the reduction of the primary network return temperature, which leads to lower generation & operating costs. These outcomes reveal that the integrated design and operation of the active thermal micro-grid have the potential to improve the performance of the entire system, to address the matter of providing comfort heating in an effective and cost-efficient manner. This work advances the current DH knowledge by identifying synergies and challenges that arise with these new developments, in order for DH to play a key role in the future smart and sustainable energy system
Bou, Tayeh Gaby. "Towards smart firefighting using the internet of things and machine learning." Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCD015.
In this thesis, we present a multilevel scheme consisting of both hardware and software solutions to improve the daily operational life of firefighters. As a core part of this scheme, we design and develop a smart system of wearable IoT devices used for state assessment and localization of firefighters during interventions. To ensure a maximum lifetime for this system, we propose multiple data-driven energy management techniques for resource constraint IoT devices. The first one is an algorithm that reduces the amount of data transmitted between the sensor and the destination (Sink). This latter exploits the temporal correlation of collected sensor measurements to build a simple yet robust model that can forecast future observations. Then, we coupled this approach with a mechanism that can identify lost packets, force synchronization, and reconstruct missing data. Furthermore, knowing that the sensing activity does also require a significant amount of energy, we extended the previous algorithm and added an additional adaptive sampling layer. Finally, we also proposed a decentralized data reduction approach for cluster-based sensor networks. All the previous algorithms have been tested and validated in terms of energy efficiency using custom-built simulators and through implementation on real sensor devices. The results were promising as we were able to demonstrate that our proposals can significantly improve the lifetime of the network. The last part of this thesis focusses on building data-centric decision-making tools to improve the efficiency of interventions. Since sensor data clustering is an important pre-processing phase and a stepstone towards knowledge extraction, we review recent clustering techniques for massive data management in IoT and compared them using real data for a gas leak detection sensor network. Furthermore, with our hands on a large dataset containing information on 200,000 interventions that happened during a period of 6 years in the region of Doubs, France. We study the possibility of using Machine Learning to predict the number of future interventions and help firefighters better manage their mobile resources according to the frequency of events
Amelete, Sam. "Gestion des actifs, industrie 4.0 et efficacité de la maintenance." Thèse, 2020. http://depot-e.uqtr.ca/id/eprint/9670/1/eprint9670.pdf.
Doucouré, Boubacar. "Proposition, intégration dans un système de gestion de réseau intelligent et validation expérimentale d'une méthode de prédiction pour un système d'énergies renouvelables." Thèse, 2015. http://depot-e.uqtr.ca/7674/1/031014383.pdf.