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Kusnetsova, Elizaveta. "Microgrid agent-based modelling and optimization under uncertainty." Versailles-St Quentin en Yvelines, 2014. http://www.theses.fr/2014VERS005S.
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Le travail de recherche est axé sur la gestion de l'énergie dans les micro réseaux électriques. La contribution scientifique est ici basée sur: (i) des approches de modélisation d'intelligence individuelle pour la gestion d'énergie sous incertitudes et (ii) la gestion de l'énergie dans un micro réseau intégrant différents acteurs avec des objectifs conflictuels. Les acteurs de micro réseaux, opérant sous un accès limité aux informations et en présence d'incertitudes opérationnelles et environnementales, sont modélisés par une approche orientée agent (Agent-Based Modelling). Les approches considérées pour la modélisation de l'intelligence individuelle dans cette thèse, i. E. L'apprentissage par renforcement (Reinforcement Learning) et l'optimisation robuste (Robust Optimization), attribuent à chaque agent des capacités de prise de décision,d'adaptation à leur environnement stochastique et d'interactions avec d'autres agents. Les méthodes de modélisation développées ont été testées sur des micro réseaux urbains impliquant différents consommateurs d'énergie, des sources d'énergie renouvelable et des moyens de stockage, afin d'optimiser la gestion de l'énergie en termes de fiabilité et des aspects économiques, sous incertitudes opérationnelle, environnementale et de défaillances des composantsThis thesis concerns the energy management of electricity microgrids. The scientific contribution follows two directions: (i) modelling individual intelligence in energy management under uncertainty and (ii) microgrid energy management integrating diverse actors with conflicting objectives. Agent-Based Modelling (ABM) is used to describe the dynamics of microgrid actors operating under limited access to information, and operational and environmental uncertainties. The approaches considered to model individual intelligence in this thesis, Reinforcement Learning and Robust Optimization, provide each agent with the capability of making decision, adapting to the stochastic environment and interacting with other agents. The modelling frameworks developed have been tested on urban microgrids integrating different energy consumers, sources of renewable energy and storage facilities, for optimal energy management in terms of reliability and economic indicators under operational and environmental uncertainty, and components failures
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Rasouli, Disfani Vahid. "Optimization and Control for Microgrid and Power Electronic Converters." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5764.
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The proposed dissertation research investigates Optimization and Control for Microgrid and Power Electronic Converters. The research has two major parts:
i- Microgrid Operation and Control,
ii- Power Electronic Converter Control and Optimization.
In the first part, three focuses are investigated. First, a completely distributed algorithm is developed for dc optimal power flow problem for power distribution systems as one of the necessary functions considered in unit-commitment problem in day-ahead markets. This method is derived based upon the partial primal-dual representation of the economic dispatch problem, which is finally translated to DC-OPF problem. Second, the optimal interaction between the utility and communities will be studied, due to its improtance in real-time markets. The objective of this section will be to develop an iterative agent-based algorithm for optimal utility-community control. The algorithm will consider the AC power system constraints to maintain power system stability. In this algorithm, a simplified model of microgrid is considered. In the third focus, a comprehensive model of microgrid is taken into account. The optimal operation of the microgrid considering energy storage systems and renewable energy resources is investigated. The interaction of such microgrids with the main grid to define the optimal operation of the entire embedded system is studied through two iterative methods. In the microgrid's internal problem, a moving-horizon algorithm is considered to define the optimal dispatch of all distributed energy resources while considering the time-correlated constraints of energy storage systems. A thorough analysis of the effects of the size of storage systems on energy and reserve market parameters are also performed.
In the second part, the focus of research is to develop optimal control strategies for Power Electronic Converters. A Model Predictive Control (MPC) switching method is proposed for Modular Multilevel Converters (MMC). The optimal solution of MPC problem is then represented as an optimization problem. Due to lack of efficient algorithms to seek the optimal solution, a fast algorithm will be proposed in this research. The method proposed reduces the number of possible solutions and computation efforts dramatically.
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Ali, Loaqat. "Optimization of energy storages in microgrid for power generation uncertainties." Thesis, Curtin University, 2016. http://hdl.handle.net/20.500.11937/48485.
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Microgrid is a cluster of distributed generation units, energy storages, and loads which can operate grid-connected and islanded. This research focuses on selecting an economic standalone supply system for small and remote off-grid towns in Western Australia. Existing power systems of such towns have adverse environmental impacts due to the utilization of diesel and gas. The suitable electricity supply system is a hybrid system composed of generators, renewables, and energy storages.
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Moghimi, Mojtaba. "Modelling and Optimization of Energy Management Systems in Microgrids and Multi-Microgrids." Thesis, Griffith University, 2018. http://hdl.handle.net/10072/385882.
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With the new challenges brought by the high penetration of Renewable Energy Resources (RESs) into the modern grid, developing new solutions and concepts are necessary. Microgrid (MG) is one of the new concepts introduced to overcome upcoming issues in the modern electricity grids. MGs and Multi-Microgrids (MMGs) are defined as the building blocks of smart grids. MGs are the small units, where power generation and consumption happen at the same location and MG makes the decisions by itself. MGs can operate grid-connected or island mode depending on the functionality of the MG. Energy Management System (EMS) is the decision making centre of the MG. The data from the devices is received by the EMS and after processing, the commands are sent to the controllable components. Management of voltage, active and reactive power, neutral current, unit commitment and economic dispatch are of the tasks of EMS.
In this PhD thesis, an optimal EMS for MGs and MMGs is developed. The main objective of this project by developing the EMS is to optimize the energy flow in the MGs and MMGs to obtain peak load shaving in a cost beneficial system. In order to achieve an efficient EMS, communication system, forecasting system, scheduling system, and optimization system are modelled and developed. Different types of EMS operation, centralized, decentralized and distributed, are investigated in this work to achieve the best combination for MMG EMS operation.
The communication system is mainly utilizing Modbus TCP/IP protocol for data transmission at local level and Internet of Things (IoT) protocols (MQTT) for the global communication level. A communication operation algorithm is proposed to manage the MMG EMS under different communication operation modes and communication failure conditions. Furthermore, a monitoring system is developed to collect the data from different devices in the MG. The data is processed in the MG EMS and the commands are sent to components through the communication infrastructure. The link between MGs and MMGs is through the proposed two-level communication system, where the expansion of MGs to a MMG is investigated. In the MMG, MGs are functioning as a unit while having different priorities and operating under different policies. Each MG has its own MG EMS and the EMSs transfer information through the communication system between each other in either centralized, decentralized, distributed, or no communication modes under the MMG EMS.
The forecasting system is required in the EMS to predict the future MG characteristics such as power generation and consumption. The forecasted data is the input to the optimization and scheduling system of EMS. Employing the forecasting system in the EMS would increase the accuracy of the optimization and scheduling systems. In this thesis, the timeseries-based forecasting algorithms are employed to predict next day’s active power using the load data, generation data, weather data and temperature data as the inputs.
The heart of EMS is the scheduling and optimization system. The purpose of the scheduling system is to define the amount and the time of energy flow in the MG for different generation sources and consumption loads. Furthermore, scheduling system is responsible for peak load shaving and valley filling. On the other hand, the optimization system has the task of minimizing the operation costs of the MGs. The role of market in the scheduling and optimization is important. Time of Use (ToU) tariff is the pricing system, which determines the peak and off peak hours for energy usage pricing. In order to apply the optimization system, a model of the system, an objective function and systems constraints are defined, where aging of battery energy storage system (BESS), operational cost of components and MG cost benefits are considered. To operate the EMS scheduling and optimization system, IBM CPLEX Optimization Studio solver conducts the optimization while for the scheduling system, objective function and constraints are defined in MATLAB. In this thesis, a rule-based, MILP and MIQP optimization system for commercial MGs including electric vehicles (EVs) are proposed to investigate performance of MG EMS for different case studies.
In this thesis, the literature for different scheduling and forecasting systems is investigated and different optimization algorithms are analysed. The communication protocols utilized in this research are described and compared to other protocols in the literature. In different chapters of this thesis, the modelling of MGs and MMG EMS, different modules of EMS, forecasting, optimization, scheduling and communication systems are described and analysed. A novel communication system for MMG EMS operation is proposed for commercial buildings. The performance of MG EMS and MMG EMS is examined for power and neutral current sharing, operation cost optimization, and demand peak shaving applications and results are compared to investigate the performance of proposed algorithms.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Eng & Built Env
Science, Environment, Engineering and Technology
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Paniagua, Sánchez-Mateos Jesús. "Reliability-Constrained Microgrid Design." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187715.
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Microgrids are new challenging power systems under development. This report presents a feasibility study of microgrid development. This is an essential task before implementing microgrid systems. It is extremely important to know the number and size of distributed energy resources (DERs) needed and it is necessary to compare investment costs with benefits in order to evaluate the profitability of microgrids. Under the assumption that a large number of DERs improves the reliability of microgrids an optimization problem is formulated to get the accurate mix of distributed energy resources. Uncertainty in physical and financial parameters is taken into account to model the problem considering different scenarios. Uncertainty takes place in load demanded, renewable energy generation and electricity market price forecasts, availability of distributed energy resources and the microgrid islanding. It is modeled in a stochastic way. The optimization problem is formulated firstly as a mixed-integer programming solved via branch and bound and then it is improved formulating a two stage problem using Benders’ Decomposition which shortens the problem resolution. This optimization problem is divided in a long-term investment master problem and a short-term operation subproblem and it is solved iteratively until it reaches convergence. Bender’s Decomposition optimization problem is applied to real data from the Illinois Institute of Technology (IIT) and it gives the ideal mix of distributed energy resources for different uncertainty scenarios. These distributed energy resources are selected from an initial set. It proves the usefulness of this optimization technique which can be also applied to different microgrids and data. The different solutions obtained for different scenarios are explained and analyzed. They show the possibility of microgrid implementation and determine the most favorable scenarios to reach the microgrid implementation successfully. Reliability is a term highly linked to the microgrid concept and one of the most important reasons of microgrid development. Thus an analysis of reliability importance is implemented using the importance index of interruption cost ( ) in order to measure the reliability improvement of developing microgrids. It shows and quantifies the reliability improvement in the system.
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Milani, Neil Patrick. "PERFORMANCE OPTIMIZATION OF A HYBRID WIND TURBINE-DIESEL MICROGRID POWER SYSTEM." NCSU, 2006. http://www.lib.ncsu.edu/theses/available/etd-11062006-173005/.
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Nearly all off-grid, remote cold-weather facilities utilize diesel-only systems for both thermal and electrical power generation. In areas of minimal to moderate wind resources, these facilities could substantially decrease diesel fuel usage and could additionally provide for thermal energy production via the integration of a wind turbine system combined with resistance heating into the facility. Voltage and frequency grid stabilization could be obtained by using the diesel electrical generating unit as a synchronous condenser and by using incremental resistive load control, respectively. For systems following medium to high wind penetration guidelines, control components are required but no energy storage mechanisms are needed. This thesis investigates a High-Penetration, No Storage Wind Diesel (HPNSWD) system that can utilize available wind resources to minimize diesel fuel costs for the Scott Base facility ? all without implementing expensive and maintenance-intensive energy storage devices.
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Wang, Baochao. "Intelligent control and power flow optimization of microgrid : energy management strategies." Thesis, Compiègne, 2013. http://www.theses.fr/2013COMP2122/document.
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La production intermittente et aléatoire des énergies renouvelables, sources photovoltaïques et éoliennes, est toujours un problème pour leur intégration massive dans le réseau public. L'une des solutions est de grouper des sources renouvelables, des sources traditionnelles, des dispositifs de stockage et des charges locales, et les traiter comme une seule unité dans le réseau public. Il s'agit du concept "micro-réseau". Un micro-réseau a des potentiels pour mieux répondre aux besoins de l'utilisateur final et du réseau public, et il facilite la mise en œuvre de futur smart grid, soit le réseau intelligent.Basé sur un micro-réseau représentatif en zone urbaine et intégré aux bâtiments, cette thèse propose une supervision multicouche, afin d'effectuer une étude systémique en mettant en exergue un verrou scientifique concernant l'implémentation d'une optimisation dans l'exploitation en temps réel.La supervision traite un ensemble d’opérations telles que : l'équilibré des puissances,l'optimisation des coûts énergétiques, utilisation de métadonnées, et échange d'informations avec le réseau intelligent et avec l'utilisateur final. Cette supervision a été validée par des tests expérimentaux. Malgré les incertitudes concernant les prévisions météorologiques, la faisabilité d'implémentation de l'optimisation dans l'exploitation réelle est vérifiée. La supervision proposée est en mesure de gérer efficacement les flux en assurant l'équilibre des puissances dans tous les cas. Néanmoins, la performance d'optimisation est liée aux précisions de prédiction. Ce problème peut être amélioré dans les travaux futurs par la mise à jour des résultats d'optimisation en temps réelThe intermittent and random production of renewable sources, such as photovoltaic and wind turbine, is always a problem for their large-scale integration in the utility grid. One of the solutions is to group renewable sources, traditional sources, storage and local consumption and treat it as a single unit in the utility grid. This is the concept of microgrid. A microgrid has the potentials of better responding both grid and end-user requirement, it facilitate the implementation of future smart grid. Based on a representative microgrid in urban area and integrated in buildings, this thesis proposes a multi-layer supervision, in order to realise a systemic study while particularly attempting to cover the research gap of implementing optimisation in realtimeoperation. The supervision handles together power balancing, energetic cost optimisation, metadata using, and information exchanges from both end-users and the smart grid. The supervision has been validated by experimental tests. The feasibility of implementing optimisation in real-time operation is validated even with uncertainties. The supervision is able to manage efficiently the power flow while maintaining power balancing in any case. Nevertheless, optimization effect relies on prediction precision. This problem can be improved in future works by updating optimization in real-time
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Pacaud, François. "Decentralized optimization for energy efficiency under stochasticity." Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC1147/document.
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Les réseaux électriques doivent absorber une production d'énergie renouvelable croissante, de façon décentralisée. Leur gestion optimale amène à des problèmes spécifiques. Nous étudions dans cette thèse la formulation mathématique de tels problèmes en tant que problèmes d'optimisation stochastique multi-pas de temps. Nous analysons plus spécifiquement la décomposition en temps et en espace de tels problèmes. Dans la première partie de ce manuscrit, Décomposition temporelle pour l'optimisation de la gestion de microgrid domestique, nous appliquons les méthodes d'optimisation stochastique à la gestion de microgrid de petite taille. Nous comparons différents algorithmes d'optimisation sur deux exemples: le premier considère une microgrid domestique équipée avec une batterie et une centrale de micro-cogénération; le deuxième considère quant à lui une autre microgrid domestique, cette fois équipée avec une batterie et des panneaux solaires. Dans la seconde partie, Décomposition temporelle et spatiale de problèmes d'optimisation de grande taille, nous étendons les études précédentes à des microgrids de plus grandes tailles, avec différentes unités et stockages connectés ensemble. La résolution frontale de tels problèmes de grande taille par Programmation Dynamique s'avère impraticable. Nous proposons deux algorithmes originaux pour pallier ce problème en mélangeant une décomposition temporelle avec une décomposition spatiale --- par les prix ou par les ressources. Dans la dernière partie, Contributions à l'algorithme Stochastic Dual Dynamic Programming, nous nous concentrons sur l'algorithme emph{Stochastic DualDynamic Programming} (SDDP) qui est actuellement une méthode de référence pour résoudre des problèmes d'optimisation stochastique multi-pas de temps. Nous étudions un nouveau critère d'arrêt pour cet algorithme basé sur une version duale de SDDP, qui permet d'obtenir une borne supérieure déterministe pour le problème primalNew energy systems are designed to absorb a large share of renewableenergy in a decentralized fashion. Their optimized management raises specificissues. We study mathematical formulation as large scale multistagestochastic optimization problems. We focus on time and space decompositionmethods in a stochastic setting.In the first part of this manuscript, Time decomposition inoptimization and management of home microgrids, we apply stochasticoptimization algorithms to the management of small scale microgrids. We compare different optimization algorithms on two examples:a domestic microgrid equipped with a microCombined Heat and Power generator and a battery;a domestic microgrid equipped with a battery and solar panels.In the second part, Mixing time and spatial decomposition inlarge-scale optimization problems, we extend the previous studies tolarger microgrids, where different units and storage devices are connected together. As a direct resolution by Dynamic Programming of such large scale systemsis untractable, we propose original algorithms mixing time decomposition on the one hand, and price and resource spatial decomposition on the other hand.In the third part, Contributions to Stochastic Dual Dynamic Programming,we focus on the Stochastic Dual Dynamic Programming (SDDP) algorithm,a well-known algorithm to solve multistage stochastic optimizationproblems. We present a new stopping criteria based on a dual versionof SDDP which gives a deterministic upper-bound for the primal problem
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Omara, Ahmed Mohamed Elsayed. "Predictive Operational Strategies for Smart Microgrid Networks." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40101.
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There have been significant advances in communication technologies over the last decade, such as cellular networks, Wi-Fi, and optical communication. Not only does the technology impact peoples’ everyday lives, but it also helps cities prepare for power outages by collecting and exchanging data that facilitates real-time status monitoring of transmission and distribution lines. Smart grids, contrary to the traditional utility grids, allow bi-directional flow of electricity and information, such as grid status and customer requirements, among different parties in the grid. Thus, smart grids reduce the power losses and increase the efficiency of electricity generation and distribution, as they allow for the exchange of information between subsystems. However, smart grids is not resilient under extreme conditions, particularly when the utility grid is unavailable. With the increasing penetration of the renewable energy sources (RES) in smart grids, the uncertainty of the generated power from the distributed generators (DGs) has brought new challenges to smart grids in general and smart microgrids in particular. The rapid change of the weather conditions can directly affect the amount of the generated power from RES such as wind turbine and solar panels, and thus degrading the reliability and resiliency of the smart microgrids. Therefore, new strategies and technologies to improve power reliability,sustainability, and resiliency have emerged. To this end, in this thesis, we propose a novel framework to improve the smart microgrids reliability and resiliency under severe conditions. We study the transition to the grid-connected operational mode in smart microgrids,in the absence of the utility grid, as an example of emergency case that requires fast and accurate response. We perform a comparative study to accurately predict upcoming grid-connected events using machine learning techniques. We show that decision tree models achieve the best average prediction performance. The packets that carry the occurrence time of the next grid-connected transition are considered urgent packets. Hence, we per-form an extensive study of a smart data aggregation approach that considers the priority of the data. The received smart microgrids data is clustered based on the delay-sensitivity into three groups using k-means algorithm. Our delay-aware technique successfully reduces the queuing delay by 93% for the packets of delay-sensitive (urgent) messages and the Packet Loss Rate (PLR) by 7% when compared to the benchmark where no aggregation mechanism exists prior to the small-cell base stations. As a mitigation action of the utility grid unavailability, we use the electrical vehicles (EVs) batteries as mobile storage units to cover smart microgrids power needs until the utility grid recovery. We formulate a Mixed Integer Linear Programming (MILP) model to find the best set of electrical vehicles with the objective of minimum cost. The EVs participating in the emergency power supply process are selected based on the distance and throughput performance between the base station and the EVs
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Trigueiro, dos Santos Leonardo. "Contribution on the day-ahead and operational optimization for DC microgrid building-integrated." Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2352/document.
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Cette recherche se concentre sur l'optimisation d'un micro-réseau en interaction avec le réseau électrique intelligent. Il s'agit de la recherche de solutions optimales pour la conception d'un micro-réseau afin de minimiser les coûts, d'une part, et la possibilité augmenter 1'utilisation des sources renouvelables, d'autre part. La supervision, doit traiter la prise en compte des incertitudes dans la gestion prédictive optimisée des flux de puissanceThis thesis study focuses on a DC microgrid building-integrated satisfying the power balance at the local level and supplying DC loads during both, grid-connected and isolated operation modes. Considering that energy management can be defined as a group of different control strategies and operational practices that together with the new physical equipment and software solutions aims to accomplish the objectives of energy management, the main objective of this thesis is to define the energy management strategies for the building-integrated DC microgrid, aiming to keep the bus voltage stable as well as to reduce the energy cost to the end users and the negative impact to the main grid. Therefore, this research work focuses to optimize and develop the implementation of the designed controller of building-integrated DC microgrid. The proposed DC microgrid consists of PV building-integrated sources, a storage system, a main grid connection for the grid-connected mode and a micro turbine for the off-grid or isolated mode, and a DC load (electric appliances of a tertiary building). The bidirectional connections with the main grid and the storage aim to supply the building’s DC appliances, and sell or store the energy surplus. The results validate the operation of the whole system, ensuring the capability of the proposed supervisory control to manage the energy power flow while ensuring voltage stability. Other goals concern the analyze of the proposed separation between optimization and real time power balance and the usage of the proposed load shedding/restoration algorithm in the microgrid environment are also validate. Regarding the technical contributions, the work of this thesis allowed the creation and the practical development of a test bench for microgrid based on PV sources emulator, which allows the repeatability conditions (closeness of the agreement between the results of successive measurements of the same solar irradiance and air temperature carried out under the same conditions of measurement) and reproducibility (closeness of the agreement between the results of measurements of the same solar irradiation and air temperature carried out under changed conditions of measurement). Numerous experimental tests were carried out and allowed the validation of the proposed concepts
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Yao, Lisha. "Distributed Consensus, Optimization and Computation in Networked Systems." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404555/.
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In the first part of this thesis, we propose a distributed consensus algorithm under multi-layer multi-group structure with communication time delays. It is proven that the consensus will be achieved in both time-varying and fixed communication delays. In the second part, we study the distributed optimization problem with a finite-time mechanism. It is shown that our distributed proportional-integral algorithm can exponentially converge to the unique global minimizer when the gain parameters satisfy the sufficient conditions. Moreover, we equip the proposed algorithm with a decentralized algorithm, which enables an arbitrarily chosen agent to compute the exact global minimizer within a finite number of time steps, using its own states observed over a successive time steps. In the third part, it is shown the implementation of accelerated distributed energy management for microgrids is achieved. The results presented in the thesis are corroborated by simulations or experiments.
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Arghandeh, Jouneghani Reza. "Distributed Energy Storage Systems: Microgrid Application, Market-Based Optimal Operation and Harmonic Analysis." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/50603.
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The need for modern electricity infrastructures and more capable grid components brings attention to distributed energy storage systems because of their bidirectional power flow capability. This dissertation focuses on three different aspects of distributed energy storage system applications in distribution networks. It starts with flywheel energy storage system modeling and analysis for application in microgrid facilities. Then, a market-based optimal controller is proposed to enhance the operational profit of distributed energy storage devices in distribution networks. Finally, impact of multiple distributed energy storage devices on harmonic propagation in distribution networks is investigated.This dissertation provides a comparison between batteries and flywheels for the ride-through application in critical microgrid facilities like data centers. In comparison with batteries, the application of FES for power security is new. This limits the availability of experimental data. The software tool developed in this dissertation enables analysis of short-term, ride-through applications of FES during an islanded operation of a facility microgrid. As a result, it can provide a guideline for facility engineers in data centers or other types of facility microgrids to design backup power systems based on FES technology.
This dissertation also presents a real-time control scheme that maximizes the revenue attainable by distributed energy storage systems without sacrificing the benefits related to improvements in reliability and reduction in peak feeder loading. This optimal control algorithm provides a means for realizing additional benefits by utilities by taking advantage of the fluctuating cost of energy in competitive energy markets. The key drivers of the economic optimization problem for distributed energy storage systems are discussed.
In this dissertation, the impact of distribution network topology on harmonic propagation due to the interaction of multiple harmonic sources is investigated. Understanding how multiple harmonic sources interact to increase or decrease the harmonic distortion is crucial in distribution networks with a large number of Distributed Energy Resources. A new index, Index of Phasor Harmonics (IPH), is proposed for harmonic quantization in multiple harmonic source cases. The proposed IPH index presents more information than commonly used indices. With the help of the detailed distribution network model, topological impacts of harmonic propagation are investigated. In particular, effects of mutual coupling, phase balance, three phase harmonic sources, and single phase harmonic sources are considered.
Ph. D.
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Malekpour, Ahmadreza. "Smart grid operational strategies for power distribution systems with large penetration of distributed energy resources." Diss., Kansas State University, 2016. http://hdl.handle.net/2097/34681.
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Doctor of PhilosophyDepartment of Electrical and Computer Engineering
Anil Pahwa
Power distribution systems are transitioning from traditional centralized-control distribution grids to the modern distribution grids that are more customer-interactive and include microgrids (MGs) as well as various unpredictable and multi-scale distributed energy resources (DERs). However, power fueled by renewable DERs such as wind and solar is highly variable and high penetration of renewable DERs in distribution system may potentially degrade the grid reliability and power quality. Moreover, the growth of such generation sources will increase the number of variables and cause scalability concerns for distribution system operators (DSOs) in handling system optimization problems. Further, with development of MGs, DSO and MG may have different owners and schedule renewable and non-renewable DERs based on their own economic rules and policies while secure and economic operation of the entire system is necessary. The widespread integration of wind and solar and deployment of MGs in distribution system make the task of distribution system operation management quite challenging especially from the viewpoint of variability, scalability, and multi-authority operation management. This research develops unique models and methodologies to overcome such issues and make distribution grid operation, optimization and control more robust against renewable intermittency, intractability, and operation complexity. The objectives of this research are as follows: 1) to develop a three-phase unbalanced large-scale distribution system to serve as a benchmark for studying challenges related to integration of DERs, such as scalability concerns in optimization problems, incremental power losses, voltage rise, voltage fluctuations, volt/var control, and operation management; 2) to develop a novel hierarchical and multilevel distributed optimization for power loss minimization via optimal reactive power provisioning from rooftop PVs which addresses the scalability issues with widespread DER integration in large-scale networks; 3) to develop a dynamic operational scheme for residential PV smart inverters to mitigate the fluctuations from rooftop PV integration under all-weather-condition (fully sunny, overcast and transient cloudy days) while increasing network efficiency in terms of power losses, and number of transformer load tap changer (LTC) operation; 4) to develop a stochastic energy management model for multi-authority distribution system operating under uncertainty from load and wind generation, which is able to precisely account interactions between DSO and MGs.
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Alarcón, Mathias, and Robin Landau. "Resilience-enhancement through Renewable Energy Microgrid Systems in rural El Salvador." Thesis, Uppsala universitet, Fasta tillståndets fysik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-378591.
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This Master thesis investigates how Renewable Energy Microgrid Systems (REMS) can enhance resilience for a rural grid-connected community in El Salvador. The study examines the optimally resilient design of a grid-connected PV-Wind-Battery hybrid energy system. The optimally resilient system configuration was determined based on energy affordability, defined as minimum net present cost (NPC) and energy reliability, which was defined as a 1% maximum annual capacity shortage. The system modelling and optimisation was performed in the HOMER (Hybrid Optimisation of Multiple Energy Resources) software, where the system was optimised for different scenarios. The results of this study show that REMS can enhance resilience by lowering electricity costs for the community and thus increasing energy affordability. However, the REMS did not manage to make an equally substantial impact on energy reliability, due to the grid performance that proved to be high with few annual power outages. Besides the grid connection, the optimally resilient system was driven entirely by PV energy since it proved to be highly profitable. Wind power and battery storage were excluded from the optimally resilient system since they did not contribute to affordability and the capacity shortage limit was met already from the PV unit and the grid. Furthermore, the results show that self-sufficiency can be provided with REMS from the local energy resources, but that it is unrealistic with current costs due to the high battery prices. The study concludes that REMS should be considered as a legitimate resilience measure in rural El Salvador.
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de, Azevedo Ricardo. "Fully Decentralized Multi-Agent System for Optimal Microgrid Control." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2461.
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In preparation for the influx of renewable energy sources that will be added to the electrical system, flexible and adaptable control schemes are necessary to accommodate the changing infrastructure. Microgrids have been gaining much attention as the main solution to the challenges of distributed and intermittent generation, but due to their low inertia, they need fast-acting control systems in order to maintain stability. Multi-Agent Systems have been proposed as dynamic control and communication frameworks. Decentralized arrangements of agents can provide resiliency and the much-desired “plug and play” behavior. This thesis describes a control system that implements droop control and the diffusion communication scheme without the need of a centralized controller to coordinate the Microgrid agents to maintain the frequency and stable operating conditions of the system. Moreover, the inter-agent communication is unaffected by changing network configurations and can achieve optimal economic dispatch through distributed optimization.
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Aldaouab, Ibrahim. "Optimization and Control of Smart Renewable Energy Systems." University of Dayton / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1567770026080553.
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Alvarez, Genesis Barbie. "Control Design for a Microgrid in Normal and Resiliency Modes of a Distribution System." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/94627.
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As inverter-based distributed energy resources (DERs) such as photovoltaic (PV) and battery energy storage system (BESS) penetrate within the distribution system. New challenges regarding how to utilize these devices to improve power quality arises. Before, PV systems were required to disconnect from the grid during a large disturbance, but now smart inverters are required to have dynamically controlled functions that allows them to remain connected to the grid. Monitoring power flow at the point of common coupling is one of the many functions the controller should perform. Smart inverters can inject active power to pick up critical load or inject reactive power to regulate voltage within the electric grid. In this context, this thesis focuses on a high level and local control design that incorporates DERs. Different controllers are implemented to stabilize the microgrid in an Islanding and resiliency mode. The microgrid can be used as a resiliency source when the distribution is unavailable. An average model in the D-Q frame is calculated to analyze the inherent dynamics of the current controller for the point of common coupling (PCC). The space vector approach is applied to design the voltage and frequency controller. Secondly, using inverters for Volt/VAR control (VVC) can provide a faster response for voltage regulation than traditional voltage regulation devices. Another objective of this research is to demonstrate how smart inverters and capacitor banks in the system can be used to eliminate the voltage deviation. A mixed-integer quadratic problem (MIQP) is formulated to determine the amount of reactive power that should be injected or absorbed at the appropriate nodes by inverter. The Big M method is used to address the nonconvex problem. This contribution can be used by distribution operators to minimize the voltage deviation in the system.Master of Science
Reliable power supply from the electric grid is an essential part of modern life. This critical infrastructure can be vulnerable to cascading failures or natural disasters. A solution to improve power systems resilience can be through microgrids. A microgrid is a small network of interconnected loads and distributed energy resources (DERs) such as microturbines, wind power, solar power, or traditional internal combustion engines. A microgrid can operate being connected or disconnected from the grid. This research emphases on the potentially use of a Microgrid as a resiliency source during grid restoration to pick up critical load. In this research, controllers are designed to pick up critical loads (i.e hospitals, street lights and military bases) from the distribution system in case the electric grid is unavailable. This case study includes the design of a Microgrid and it is being tested for its feasibility in an actual integration with the electric grid. Once the grid is restored the synchronization between the microgrid and electric must be conducted. Synchronization is a crucial task. An abnormal synchronization can cause a disturbance in the system, damage equipment, and overall lead to additional system outages. This thesis develops various controllers to conduct proper synchronization. Interconnecting inverter-based distributed energy resources (DERs) such as photovoltaic and battery storage within the distribution system can use the electronic devices to improve power quality. This research focuses on using these devices to improve the voltage profile within the distribution system and the frequency within the Microgrid.
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García, Elvira David. "Contributions on DC microgrid supervision and control strategies for efficiency optimization through battery modeling, management, and balancing techniques." Doctoral thesis, Universitat Rovira i Virgili, 2021. http://hdl.handle.net/10803/672010.
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Aquesta tesi presenta equips, models i estratègies de control que han estat desenvolupats amb l'objectiu final de millorar el funcionament d'una microxarxa CC.
Es proposen dues estratègies de control per a millorar l'eficiència dels convertidors CC-CC que interconnecten les unitats de potència de la microxarxa amb el bus CC. La primera estratègia, Control d'Optimització de Tensió de Bus centralitzat, administra la potència del Sistema d'Emmagatzematge d'Energia en Bateries de la microxarxa per aconseguir que la tensió del bus segueixi la referència dinàmica de tensió òptima que minimitza les pèrdues dels convertidors. La segona, Optimització en Temps Real de la Freqüència de Commutació, consisteix a operar localment cada convertidor a la seva freqüència de commutació òptima, minimitzant les seves pèrdues.
A més, es proposa una nova topologia d'equilibrador actiu de bateries mitjançant un únic convertidor CC-CC i s'ha dissenyat la seva estratègia de control. El convertidor CC-CC transfereix càrrega cel·la a cel·la, emprant encaminament de potència a través d'un sistema d'interruptors controlats. L'estratègia de control de l'equalitzador aconsegueix un ràpid equilibrat del SOC evitant sobrecompensar el desequilibri.
Finalment, es proposa un model simple de degradació d'una cel·la NMC amb elèctrode negatiu de grafit. El model combina la simplicitat d'un model de circuit equivalent, que explica la dinàmica ràpida de la cel·la, amb un model físic del creixement de la capa Interfase Sòlid-Electròlit (SEI), que prediu la pèrdua de capacitat i l'augment de la resistència interna a llarg termini. El model proposat quantifica la incorporació de liti al rang de liti ciclable necessària per a aconseguir els límits de OCV després de la pèrdua de liti ciclable en la reacció secundària. El model de degradació SEI pot emprar-se per a realitzar un control predictiu de bateries orientat a estendre la seva vida útil.Aquesta tesi presenta equips, models i estratègies de control que han estat desenvolupats amb l'objectiu final de millorar el funcionament d'una microxarxa CC. Es proposen dues estratègies de control per a millorar l'eficiència dels convertidors CC-CC que interconnecten les unitats de potència de la microxarxa amb el bus CC. La primera estratègia, Control d'Optimització de Tensió de Bus centralitzat, administra la potència del Sistema d'Emmagatzematge d'Energia en Bateries de la microxarxa per aconseguir que la tensió del bus segueixi la referència dinàmica de tensió òptima que minimitza les pèrdues dels convertidors. La segona, Optimització en Temps Real de la Freqüència de Commutació, consisteix a operar localment cada convertidor a la seva freqüència de commutació òptima, minimitzant les seves pèrdues. A més, es proposa una nova topologia d'equilibrador actiu de bateries mitjançant un únic convertidor CC-CC i s'ha dissenyat la seva estratègia de control. El convertidor CC-CC transfereix càrrega cel·la a cel·la, emprant encaminament de potència a través d'un sistema d'interruptors controlats. L'estratègia de control de l'equalitzador aconsegueix un ràpid equilibrat del SOC evitant sobrecompensar el desequilibri. Finalment, es proposa un model simple de degradació d'una cel·la NMC amb elèctrode negatiu de grafit. El model combina la simplicitat d'un model de circuit equivalent, que explica la dinàmica ràpida de la cel·la, amb un model físic del creixement de la capa Interfase Sòlid-Electròlit (SEI), que prediu la pèrdua de capacitat i l'augment de la resistència interna a llarg termini. El model proposat quantifica la incorporació de liti al rang de liti ciclable necessària per a aconseguir els límits de OCV després de la pèrdua de liti ciclable en la reacció secundària. El model de degradació SEI pot emprar-se per a realitzar un control predictiu de bateries orientat a estendre la seva vida útil.
This dissertation presents a set of equipment, models and control strategies, that have been developed with the final goal of improving the operation of a DC microgrid. Two control strategies are proposed to improve the efficiency of the DC-DC converters that interface the microgrid’s power units with the DC bus. The first strategy is centralized Bus Voltage Optimization Control, which manages the power of the microgrid’s Battery Energy Storage System to make the bus voltage follow the optimum voltage dynamic reference that minimizes the converters’ losses. The second control strategy is Online Optimization of Switching Frequency, which consists in locally operating each converter at its optimum switching frequency, again minimizing power losses. The two proposed optimization strategies have been validated in simulations. Moreover, a new converter-based active balancing topology has been proposed and its control strategy has been designed. This equalizer topology consists of a single DC-DC converter that performs cell-to-cell charge transfer employing power routing via controlled switches. The control strategy of the equalizer has been designed to achieve rapid SOC balancing while avoiding imbalance overcompensation. Its performance has been validated in simulation. Finally, a simple degradation model of an NMC battery cell with graphite negative electrode is proposed. The model combines the simplicity of an equivalent circuit model, which explains the fast dynamics of the cell, with a physical model of the Solid-Electrolyte Interphase (SEI) layer growth process, which predicts the capacity loss and the internal resistance rise in the long term. The proposed model fine-tunes the capacity loss prediction by accounting for the incorporation of unused lithium reserves of both electrodes into the cyclable lithium range to reach the OCV limits after the side reaction has consumed cyclable lithium. The SEI degradation model can be used to perform predictive control of batteries oriented toward extending their lifetime.
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Tulpule, Pinak J. "Control and optimization of energy flow in hybrid large scale systems - A microgrid for photovoltaic based PEV charging station." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1313522717.
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Mustafa, Mehran. "OPTIMAL SIZING OF GRID CONNECTED MICROGRID IN RURAL AREA OF PAKISTAN WITH WIND TURBINES AND ENERGY STORAGE SYSTEM USING PARTICLE SWARM OPTIMIZATION." OpenSIUC, 2017. https://opensiuc.lib.siu.edu/theses/2132.
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Pakistan has been riddled with energy shortage crisis. Long hours of load shedding have caused major economic setbacks in urban areas and rural areas do not even make the cut. Some rural parts, which are connected to the grid, suffer major load shedding and so economic growth is minimal. Most energy is directed towards industrial demand; hence the domestic demand suffers and causes long hours of load shedding. To aid this supply-demand gap, microgrids can be helpful in relieving some of the domestic load on the grid. A microgrid may be more economical only as a support for the main grid in an area, depending on its configuration. Since microgrids are generally composed of renewable energy sources like wind or solar or a combination of both, the supply from just these sources may result in high intermittency. To allow uniform supply, a backup energy source or energy storage is included with the renewable sources. Sizing a microgrid for the targeted region is critical. Some major sizing factors include the availability of renewable resource, load profile of the region, land availability, grid availability, etc. For this thesis, a region near Gharo, a town in Thatta District in Sindh, Pakistan, is selected to deploy the microgrid with a wind farm and battery energy storage system. The microgrid is connected to the main feeder, which supplies grid electricity to a small town of 30 small homes, a school and a small hospital. Hourly wind speed data and an annual load profile is used to calculate the most economic size of the microgrid, depending on the energy dispatch philosophy. To find the most economical solution, this thesis incorporates a stochastic technique, known as the Particle Swarm Optimization (PSO), which is a powerful intelligence evolution algorithm for solving optimization problems. Over the years, PSO has gained popularity due to its simple structure and high performance in solving linear or non-linear objective functions with any number of constraints. In this case, the objective function to be minimized is the net present cost of the microgrid, which comprises of annual capital cost, annual operation and maintenance cost, annual replacement cost of all equipment involved and the annual net cost of buying/selling electricity from/to the grid, respectively.
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Li, Bei. "Sizing and Operation of Multi-Energy Hydrogen-Based Microgrids." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCA021/document.
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Avec le développement de la production décentralisée d'électricité à partir de sources renouvelables, il est fort probable que les micro-réseaux joueront un rôle central dans les réseaux du futur, non seulement pour réduire les émissions de gaz à effet de serre et maximiser l'utilisation d'énergie produite localement, mais également pour améliorer la résilience du système global. Du fait de l'intermittence et de l'incertitude sur la production renouvelable (par exemple, photovoltaïque ou éolien), des systèmes de stockage de l'énergie doivent être intégrés. Cependant, déterminer leur dimensionnement et comment les contrôler pose plusieurs défis, en particulier parce que le dimensionnement optimal dépend de la stratégie de gestion utilisée, ou encore lorsque différents types d'énergie sont utilisés. Cette thèse contribue à résoudre les problèmes de dimensionnement et de gestion de micro-réseaux électriques et multi-énergies (électricité, gaz, chaleur, froid et/ou hydrogène) intégrant du stockage. Tout d'abord, à l'aide des caractéristiques des différents composants, un modèle mathématique de micro-réseau est développé. Le problème de sa gestion est ensuite formulé comme un problème de programmation linéaire (MILP), utilisant une fonction objectif (minimiser le coût de fonctionnement) et différentes contraintes (puissance maximum, durée de démarrage/arrêt, limites d'état de charge, etc.). Ensuite, une structure permettant une co-optimisation est présentée pour résoudre le problème du dimensionnement à l'aide d'un algorithme génétique. Cette structure permet de explorer l'espace des valeurs de dimensionnement en fonction des résultats de la stratégie de gestion, ce qui permet de tendre vers le meilleur dimensionnement possible pour la stratégie sélectionnée. A l'aide de la méthode ci-dessus, quatre problèmes spécifiques sont étudiés. Le premier s'intéresse au dimensionnement d'un micro-réseau îloté entièrement électrique, combinant stockage par batteries et hydrogène-énergie pour du stockage à court et long terme, respectivement. Les résultats pour deux stratégies de gestion sont comparés : l'approche proposée (MILP) et une stratégie basée sur des règles. Une simulation à horizon glissant d'une heure sur un an est ensuite utilisée pour vérifier la validité du dimensionnement obtenu. Un second problème s'intéresse un à micro-réseau multi-énergies îloté avec différents types de charges. L'influence de trois facteurs sur les résultats du dimensionnement est en particulier étudiée : la stratégie de gestion, la précision des prévisions de consommation et de production renouvelable, ainsi que la dégradation des moyens de stockage. Une troisième partie de la thèse traite du dimensionnement d'un micro-réseau connecté aux réseaux de gaz, électricité et chaleur. La résilience du réseau est étudiée de façon à maximiser la résistance à une panne ou un défaut. La notion de centralité intermédiaire est utilisée pour déterminer le cas le plus défavorable pour une contingence et analyser son impact sur le dimensionnement. Deux systèmes de test de tailles différentes sont utilisés pour valider l'application de la méthode proposée et sa sensibilité à différents paramètresWith the development of distributed, renewable energy sources, microgrids can be expected to play an important role in future power systems, not only to reduce emissions and maximize local energy use, but also to improve system resilience. Due to the intermittence and uncertainty of renewable sources (such as photovoltaics or wind turbines), energy storage systems should also be integrated. However, determining their size and how to operate them remains challenging, especially as the adopted control strategy impacts sizing results, and for systems considering multiple, interdependent forms of energy. This thesis therefore contributes to solving the sizing and operation problems of full-electric and multi-energy (electricity, gas, heat, cooling and/or hydrogen) microgrids integrating storage systems.First, based on the characteristics of different components, a mathematical model of a microgrid is built. Then, the operation problem is formulated as a mixed integer linear problem (MILP), based on an objective function (minimize the operation cost) and different constraints (maximum power, startup/shutdown times, state-of-charge limits, etc.). Next, a co-optimization structure is presented to solve the sizing problem using a genetic algorithm. This specific structure enables to search for sizing values based on the operation results, which enables determining the best sizing for the selected operation strategy.Using the above method, four specific problems are then studied. The first one focuses on sizing a full-electric islanded microgrid combining battery and hydrogen storage systems for short and long-term storage, respectively. Results for two types of operation strategies are compared: the MILP approach and a rule-based strategy. A one-hour one-year rolling horizon simulation is used to check the validity of the sizing results.Second, a multi-energy islanded microgrid with different types of loads is studied. Specifically, the influence of three factors on sizing results is analyzed: the operation strategy, the accuracy of load and renewable generation forecasts, and the degradation of energy storage systems.Third, the work focuses on a grid-connected microgrid attached to a gas, electricity and heat hybrid network. Specifically, the resilience of the network is considered in order to maximize resistance to contingency events. Betweenness centrality is used to find the worst case under contingency events and analyze their impact on sizing results. Two test systems of different sizes are used with the proposed method and a study of its sensitivity to various parameters is carried out.Fourth, a structure with multiple grid-connected multi-energy-supply microgrids is considered, and an algorithm for determining electricity prices is developed. This price is used for energy exchanges between microgrids and load service entities interacting with the utility. The proposed co-optimization method is deployed to search for the best price that maximizes benefits to all players. Simulations on a large system show that the obtained price returns better results than a basic time-of-use price and helps reduce the operation cost of the whole system. To reduce the computation time, a neural network is presented to estimate the operation of the whole system and enable obtaining results faster with a limited impact on performance. At last, a sizing algorithm for grid-connected multi-energy supply microgrids operating under different prices is presented.The obtained results on these different applications show the usefulness of the proposed method, which is a promising contribution toward the creation of advanced design tools for such microgrids
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Zia, Muhammad Fahad. "On energy management optimization for microgrids enriched with renewable energy sources Microgrids energy management systems: a critical review on methods, solutions, and prospects, in Applied Energy 222, July 2018 Optimal operational planning of scalable DC microgrid with demand response, islanding, and battery degradation cost considerations, in Applied Energy 237, March 2019 Energy management system for an islanded microgrid with convex relaxation, in IEEE Transactions on Industry Applications 55, Nov.-Dec. 2019 Microgrid transactive energy: review, architectures, distributed ledger technologies, and market analysis, in IEEE Access, January 2020." Thesis, Brest, 2020. http://theses-scd.univ-brest.fr/2020/These-2020-SPI-Genie_electrique-ZIA_Muhammad_Fahad.pdf.
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Le réseau électrique actuel est confronté à plusieurs défis liés aux exigences environnementales, à l'augmentation de la demande mondiale d'électricité, aux contraintes de fiabilité élevées, à la nécessité d’une énergie décarbonisée et aux restrictions de planification. Afin d’évoluer vers un système d'énergie électrique respectueux de l’environnement et intelligent, les installations de production centralisées sont de nos jours transformées en de plus petites centrales de génération distribuées. Le concept de micro-réseau émerge ainsi. Le micro-réseau peut être considéré comme un système de distribution basse tension avec un ensemble de charges contrôlables et de ressources énergétiques distribuées, qui peuvent inclure de nombreuses sources d'énergie renouvelables et des systèmes de stockage d'énergie. La gestion d’énergie d'un grand nombre de ressources énergétiques distribuées est nécessaire au bon fonctionnement d'un micro-réseau afin d’en assurer la stabilité, la fiabilité et la disponibilité. Par conséquent,un système de gestion d'énergie est au coeur de l'exploitation des micro-réseaux afin d’en assurer un développement économique et durable. À cet égard, cette thèse se focalise sur la proposition de modèles d'optimisation de système de gestion de l'énergie pour une exploitation optimale des micro-réseaux. Une gestion d’énergie optimale requiert la prise en compte de plusieurs contraintes techniques, économiques et environnementales. De plus, ces travaux de recherche prennent en considération un modèle pratique du coût de dégradation des batteries Li-ion. Le problème de gestion d’énergie optimale se traduit ainsi par un problème d’optimisation sous contraintes. La fonction objective regroupe le coût d'exploitation des générateurs distribués, le coût des émissions de gaz à effet de serre des sources de production conventionnelles, l’obligation d’une utilisation maximale des sources d'énergie renouvelables, le coût de dégradation des batteries, les différentes incitations afin de modifier le profil de la demande et des pénalités en cas de délestage. Les contraintes quant à elles sont liées aux contraintes techniques des différents sous-systèmes du micro-réseau. Par ailleurs, un modèle conceptuel complet à sept couches est également développé afin de fournir des informations normalisées sur la mise en oeuvre d’une nouvelle économie de l’énergieThe current electric power system isfacing the challenges of environmental protection,increasing global electricity demand, high reliability requirement, cleanliness of energy, and planning restrictions. To evolve towards green and smart electric power system, centralized generating facilities are now being transformed into smaller and more distributed generations. As a consequence, the concept of microgrid emerges, where a microgrid can operate as a single controllable system and can be assumed as a cluster of loads and distributed energy resources, which may include many renewable energy sources and energy storage systems. The energy management of large numbers of distributed energy resources is needed for reliable operation of microgrid system. Therefore, energy management is the fundamental part of the microgrid operation for economical and sustainable development. In this regard, this thesis focuses on proposing energy management optimization models for optimal operation of microgrid system that include proposed practical Li-ion battery degradation cost model. These different energy management models include objective functions of operating cost of distributed generators, emission cost of conventional generation source, maximum utilization of renewable energy sources, battery degradation cost, demand response incentives, and load shedding penalization cost, with microgrid component and physical network constraints. A comprehensive conceptual seven layer model is also developed to provide standardized insights in implementing real transactive energy systems
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Heymann, Benjamin. "Mathematical contributions for the optimization and regulation of electricity production." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLX052/document.
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Nous présentons notre contribution sur la régulation et l’optimisation de la production d’électricité.La première partie concerne l’optimisation de la gestion d’un micro réseau. Nous formulons le programme de gestion comme un problème de commande optimal en temps continu, puis nous résolvons ce problème par programmation dynamique à l’aide d’un solveur développé dans ce but : BocopHJB. Nous montrons que ce type de formulation peut s’étendre à une modélisation stochastique. Nous terminons cette partie par l’algorithme de poids adaptatifs, qui permet une gestion de la batterie du micro réseau intégrant le vieillissement de celle-ci. L’algorithme exploite la structure à deux échelles de temps du problème de commande.La seconde partie concerne des modèles de marchés en réseaux, et en particulier ceux de l’électricité. Nous introduisons un mécanisme d’incitation permettant de diminuer le pouvoir de marché des producteurs d’énergie, au profit du consommateur. Nous étudions quelques propriétés mathématiques des problèmes d’optimisation rencontrés par les agents du marché (producteurs et régulateur). Le dernier chapitre étudie l’existence et l’unicité des équilibres de Nash en stratégies pures d’une classe de jeux Bayésiens à laquelle certains modèles de marchés en réseaux se rattachent. Pour certains cas simples, un algorithme de calcul d’équilibre est proposé.Une annexe rassemble une documentation sur le solveur numérique BocopHJBWe present our contribution on the optimization and regulation of electricity produc- tion.The first part deals with a microgrid Energy Management System (EMS). We formulate the EMS program as a continuous time optimal control problem and then solve this problem by dynamic programming using BocopHJB, a solver developed for this application. We show that an extension of this formulation to a stochastic setting is possible. The last section of this part introduces the adaptative weights dynamic programming algorithm, an algorithm for optimization problems with different time scales. We use the algorithm to integrate the battery aging in the EMS.The second part is dedicated to network markets, and in particular wholesale electricity markets. We introduce a mechanism to deal with the market power exercised by electricity producers, and thus increase the consumer welfare. Then we study some mathematical properties of the agents’ optimization problems (producers and system operator). In the last chapter, we present some pure Nash equilibrium existence and uniqueness results for a class of Bayesian games to which some networks markets belong. In addition we introduce an algorithm to compute the equilibrium for some specific cases.We provide some additional information on BocopHJB (the numerical solver developed and used in the first part of the thesis) in the appendix
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Rigo-Mariani, Remy. "Méthodes de conception intégrée "dimensionnement-gestion" par optimisation d'un micro-réseau avec stockage." Thesis, Toulouse, INPT, 2014. http://www.theses.fr/2014INPT0140/document.
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L’augmentation de la consommation pour soutenir la croissance, le souci de réduction des gaz à effet de serre et les avancées technologiques ont favorisé le développement des sources d’énergie renouvelables depuis les années 90. L’implantation de ces générateurs décentralisés a progressivement modifié l’architecture du réseau en passant d’un modèle vertical à une situation davantage clusterisée. Ce réseau maillé voit ainsi apparaitre de nouveaux acteurs, à la fois producteurs et consommateurs (en anglais, les « prosumers»). Pour ce type de structures, la stratégie classique actuelle consiste à acheter l'ensemble de l'énergie consommée alors que la totalité de la production est vendue séparément à des tarifs intéressants. Avec les progrès réalisés sur les différentes technologies de stockage, de nouveaux degrés de liberté apparaissent et des opérations plus intelligentes deviennent possibles. L’objet de l’étude est un microréseau comprenant un générateur photovoltaïque et un consommateur tertiaire associés à un moyen de stockage. Deux technologies sont envisagées avec des volants d’inertie dans un premier temps et une batterie électrochimique (Li-ion) par la suite. Les domaines d’étude relatifs à ce type de système sont la gestion énergétique par planification, la commande temps réel et le dimensionnement. Les travaux de cette thèse se concentrent d’abord sur la problématique de gestion par optimisation des flux d’énergie. Différents algorithmes sont ainsi utilisés et comparés pour planifier le fonctionnement du microréseau. L’objectif est de diminuer la facture énergétique en tenant compte des données de consommation et production mais également des politiques tarifaires en vigueur et d’éventuelles contraintes de fonctionnement imposées par le fournisseur d’énergie. Dans un second temps la problématique de dimensionnement est abordée avec une démarche de conception optimale intégrant la boucle de gestion dès la phase de design. Nous montrons plus particulièrement comment l’adéquation entre les méthodes d’optimisation utilisées et le modèle du microréseau employé peut permettre la réduction significative des temps de calcul. Une configuration optimale du microréseau, valable sur des horizons temporels longs intégrant les alternances saisonnières, peut finalement se dégager. Les travaux se concluent sur une phase d’analyse avec des dimensionnements établis pour différents contextes tarifaires. Le but est de dégager des domaines permettant de valoriser et justifier l’installation d’un moyen de stockage qui s’avère indispensable pour soutenir le développement des sources d’énergies renouvelables et assurer la transition énergétiqueTo face the increasing demand of electrical power in compliance with the liberalization of the electricity market and the need of reducing CO2 emissions, many distributed energy resources have emerged and especially the generation systems that utilize renewable energy sources. In the nearfuture, the grid could be described as an aggregation of several microgrids both consumer and producer. For those "prosumers", a classical strategy consists in selling all the highly subsidized production at important prices while all consumed energy is purchased. Smarter operations now become possible with developments of energy storage technologies and evolving prices policies. The microgrid considered in the thesis is composed of an industrial load and a photovoltaic generator associated to an energy storage. Two technologies are considered with high speed flywheels on one hand and a Li-ion electrochemical battery on the other. The common study referring to such systems allude to the optimal scheduling, the real-time management and the sizing methodology. Firstly in the thesis, the optimal power flow dispatching is performed using various algorithms. Those operations aim at reducing the electrical bill taking account of consumption and production forecasts as well as the different fares and possible constraints imposed by the power supplier. Then the design strategy is investigated. The approach consists in simultaneously integrating the energy management and the sizing of the system. We particularly underline the complexity of the resulting optimization problem and how it can be solved using suitable optimization methods in compliance with relevant models of the microgrid. We specifically show the reduction of the computational time allowing the microgrid simulation over long time durations in the optimization process in order to take seasonal variations into account. In the last part a cost analysis is performed, and different design are computed depending on the prices policies. The goal is to determine a financial context that would encourage the deployment of storage systems that are necessary to favor the development of intermittent renewable energy sources
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Nguyen, Tung Lam. "Contrôle et optimisation distribués basés sur l'agent dans les micro-réseaux avec implémentation Hardware-in-the-Loop." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT022/document.
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En ce qui concerne la hiérarchie de contrôle des micro-réseaux, la coordination des contrôleurs locaux est obligatoire aux niveaux secondaire et tertiaire. Au lieu d'utiliser une unité centrale comme approche conventionnelle, dans ce travail, des schémas distribués sont considérés. Les approches distribuées ont récemment fait l'objet d'une attention particulière en raison de leurs avantages en termes de fiabilité, d'évolutivité et de sécurité. Le système multi-agents est une technique avancée dont les propriétés les rendent aptes à servir de base à la construction de systèmes de contrôle distribués modernes. La thèse porte sur la conception d'agents visant à distribuer des algorithmes de contrôle et d'optimisation dans des micro-réseaux avec un déploiement en ligne réaliste sur une plate-forme Hardware-in-the-Loop. Sur la base de l'architecture à trois couches fournie par micro-réseaux, une plate-forme de laboratoire avec configuration Hardware-in-the-Loop est construite au niveau du système. Cette plateforme comprend deux parties : (1) un simulateur numérique en temps réel permet de simuler en temps réel des micro-réseaux de cas de test avec des contrôleurs locaux ; et (2) un cluster de Raspberry PI représente le système multi-agent fonctionnant dans un réseau de communication physique épars. Un agent est un programme en Python exécuté sur un seul Raspberry PI qui permet de transférer des données à ses voisins et d’effectuer des calculs selon des algorithmes de manière distribuée.Dans la thèse, nous appliquons les algorithmes distribués pour les niveaux de contrôle secondaire et tertiaire. Les contrôles secondaires distribués dans un micro-réseau îloté sont présentés selon deux approches d'algorithme de consensus à temps fini et d'algorithme de consensus moyen avec les améliorations des performances. Une extension de la plate-forme avec la Power Hardware-in-the-Loop et la communication basée sur la norme IEC 61850 est traitée pour rapprocher le déploiement des agents des applications industrielles. Au niveau de contrôle supérieur, les agents exécutent la méthode des multiplicateurs à sens alternatif pour déterminer les points de fonctionnement optimaux des systèmes de micro-réseaux en état d'îlot et de connexion au réseau. Les objectifs de contrôle secondaire et tertiaire sont atteints dans un cadre unique qui est rarement mentionné dans d'autres études.Dans l'ensemble, l'agent est explicitement étudié et déployé dans des conditions réalistes pour faciliter l'application des algorithmes distribués pour le contrôle hiérarchique dans les micro-réseaux. Cette recherche constitue une étape supplémentaire qui rapproche les algorithmes distribués de l'implémentation sur siteIn terms of the control hierarchy of microgrids, the coordination of local controllers is mandatory in the secondary and tertiary levels. Instead of using a central unit as conventional approaches, in this work, distributed schemes are considered. The distributed approaches have been taken attention widely recently due to the advantages of reliability, scalability, and security. The multi-agent system is an advanced technique having properties that make them suitable for acting as a basis for building modern distributed control systems. The thesis focuses on the design of agents aiming to distributed control and optimization algorithms in microgrids with realistic on-line deployment on a Hardware-in-the-loop platform. Based on the provided three-layer architecture of microgrids, a laboratory platform with Hardware-in-the-loop setup is constructed in the system level. This platform includes two parts: (1) a digital real-time simulator uses to simulate test case microgrids with local controllers in real-time; and (2) a cluster of hardware Raspberry PIs represents the multi-agent system operating in a sparse physical communication network. An agent is a Python-based program run on a single Raspberry PI owing abilities to transfer data with neighbors and computing algorithms to control the microgrid in a distributed manner.In the thesis, we apply the distributed algorithms for both secondary and tertiary control level. The distributed secondary controls in an islanded microgrid are presented in two approaches of finite-time consensus algorithm and average consensus algorithm with the improvements in performances. An extension of the platform with Power Hardware-in-the-Loop and IEC 61850-based communication is processed to make the deployment of agents closer to industrial applications. On the top control level, the agents execute the Alternating Direction Method of Multipliers to find out the optimal operation points of microgrid systems in both islanded and grid-connect state. The secondary and tertiary control objectives are achieved in a single framework which is rarely reported in other studies.Overall, the agent is explicitly investigated and deployed in the realistic conditions to facilitate applications of the distributed algorithms for the hierarchical control in microgrids. This research gives a further step making the distributed algorithms closer to onsite implementation
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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.
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Le travail de recherche de cette thèse se concentre sur l’élaboration de deux modes de fonctionnement du microréseau à savoir : mode connecté au réseau, mode hors réseau comprenant les modes îloté et isolé. Le problème de la défaillance du réseau en mode connecté au réseau et la faible fiabilité de l'alimentation électrique en mode hors réseau doivent être résolues. Ainsi, le but de cette thèse est de proposer un microréseau DC combinant à la fois les avantages du mode connecté au réseau et ceux du mode isolé. On obtient ainsi un microréseau DC qu’on peut qualifier de complet. Le microréseau DC complet contient les sources d'énergie renouvelables, le stockage et le réseau public, et les sources de secours sont utilisées pour réduire le délestage. Dans ce microréseau DC, un système de supervision est proposé dans le but de gérer le flux des puissances. La gestion de la puissance en temps réel dans la couche opérationnelle du système de supervision permet de maintenir l'équilibre de puissance. Dans la couche d'optimisation du système de supervision, l'optimisation journalière est proposée afin de minimiser le coût d'exploitation global. Les résultats de la simulation montrent que le microréseau DC complet peut minimiser les coûts d'exploitation. Ensuite, le système de supervision prend en compte l'efficacité dynamique du convertisseur pour résoudre le problème lié à la qualité de la puissance du microréseau qui peut être dégradée à cause de la tension instable du bus DC. Les résultats de la simulation montrent que la prise en compte de l'efficacité dynamique du convertisseur dans la couche opérationnelle du système de supervision permet de réduire les fluctuations de la tension du bus DC. En ce qui concerne l'importance de la prédiction PV pour l'optimisation de la veille, deux modèles de prédiction sont étudiés et comparés pour donner une puissance de prédiction PV précise. Les résultats montrent que les deux modèles ont presque les mêmes résultatsThis 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
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Maknouninejad, Ali. "Cooperative Control and Advanced Management of Distributed Generators in a Smart Grid." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5663.
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Smart grid is more than just the smart meters. The future smart grids are expected to include a high penetration of distributed generations (DGs), most of which will consist of renewable energy sources, such as solar or wind energy. It is believed that the high penetration of DGs will result in the reduction of power losses, voltage profile improvement, meeting future load demand, and optimizingthe use of non-conventionalenergy sources. However, more serious problems will arise if a decent control mechanism is not exploited. An improperly managed high PV penetration may cause voltage profile disturbance, conflict with conventional network protection devices, interfere with transformer tap changers, and as a result, cause network instability. Indeed, it is feasible to organize DGs in a microgrid structure which will be connected to the main grid through a point of common coupling (PCC). Microgrids are natural innovation zones for the smart grid because of their scalability and flexibility. A proper organization and control of the interaction between the microgrid and the smartgrid is a challenge. Cooperative control makes it possible to organize different agents in a networked system to act as a group and realize the designated objectives. Cooperative control has been already applied to the autonomous vehicles and this work investigates its application in controlling the DGs in a micro grid. The microgrid power objectives are set by a higher level control and the application of the cooperative control makes it possible for the DGs to utilize a low bandwidth communication network and realize the objectives. Initially, the basics of the application of the DGs cooperative control are formulated. This includes organizing all the DGs of a microgrid to satisfy an active and a reactive power objective. Then, the cooperative control is further developed by the introduction of clustering DGs into several groups to satisfy multiple power objectives. Then, the cooperative distribution optimization is introduced to optimally dispatch the reactive power of the DGs to realize a unified microgrid voltage profile and minimizethelosses. Thisdistributedoptimizationis agradient based techniqueand itis shown that when the communication is down, it reduces to a form of droop. However, this gradient based droop exhibits a superior performance in the transient response, by eliminating the overshoots caused by the conventional droop. Meanwhile, the interaction between each microgrid and the main grid can be formulated as a Stackelberg game. The main grid as the leader, by offering proper energy price to the micro grid, minimizes its cost and secures the power. This not only optimizes the economical interests of both sides, the microgrids and the main grid, but also yields an improved power flow and shaves the peak power. As such, a smartgrid may treat microgrids as individually dispatchable loads or generators.Ph.D.
Doctorate
Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering
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Liu, Jianzhe. "On Control and Optimization of DC Microgrids." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1512049527948171.
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Yassuda, Yamashita Damiela. "Hierarchical Control for Building Microgrids." Thesis, Poitiers, 2021. http://www.theses.fr/2021POIT2267.
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Représentant plus d'un tiers de la consommation mondiale d'électricité, les bâtiments sont le secteur énergétique majeur pour promouvoir l’usage des énergies renouvelables. L'installation à la fois de sources d’énergie rénouvelable et d'un système de stockage d'énergie électrique dans les bâtiments peut favoriser la transition énergétique vers un système électrique à faible émission de carbone, tout en permettant aux consommateurs d'énergie finaux de bénéficier d'une énergie propre. Malgré tous ces avantages, cette topologie innovante et distribuée d’un Micro-réseau dédié au Bâtiment (MB)nécessite des changements importants dans le réseau actuel, qui dépend des politiques énergétiques et d’avancement technologiques.La conception d'un Système de Gestion de l'Energie (EMS) capable de gérer efficacement les composants électriques du micro-réseau sans menacer la stabilité du réseau principal est un obstacle au développement des MB. Pour atténuer les effets néfastes introduits par des acteurs d’énergie imprévisibles, le concept d'autoconsommation est de plus en plus adopté. Néanmoins, une analyse technico-économique plus approfondie est nécessaire pour piloter d’une manière optimaledes systèmes de stockage d'énergie afin d’atteindre des indices d'autoconsommation plus élevés.Face à ces enjeux, le but de ce doctorat est de proposer un EMS pour les micro-réseaux installés dans les bâtiments afin de maximiser leur taux d’autoconsommation à un coût d’exploitation minimum. Parmi les architectures de contrôle, la structure hiérarchique s'est avérée efficace pour gérer des objectifs contradictoires qui ne sont pas dans la même échelle de temps. Ainsi, une structure de contrôle Hiérarchique à Modèle Prédictif (HMPC) a été adoptée pour remédier aux incertitudes liées aux déséquilibres de puissance ainsi qu’établir un compromis entre la réduction du coût de fonctionnement et le respect du code de l’énergie français.Considérant que les bâtiments ne sont pas homogènes et nécessitent des solutions adaptées à leur besoin, le contrôleur proposé a été couplé à deux modules fonctionnant à base d’analyse de données. Le premier algorithme consiste à gérer les inexactitudes dans les modèles internes de l’HMPC. Sans avoir besoin de régler aucun paramètre, cet algorithme améliore la précision du modèle de batteries jusqu'à trois fois et augmente jusqu'à dix fois la précision du modèle de stockage d'hydrogène, réduisant ainsi la dépendance de l’EMS aux étapes de modélisation. Le deuxième algorithme détermine de manière autonome les paramètres de l’HMPC et facilite le compromis entre les aspects économiques et énergétiques. S'appuyant uniquement sur l'analyse des données de déséquilibre de puissance et des mesures, le contrôleur hiérarchique spécifie quel dispositif de stockage d'énergie doit fonctionner quotidiennement en fonction de l'estimation du taux d'autoconsommation et du coût de fonctionnement du micro-réseau. Ces estimations diminuent les dépenses annuelles du micro-réseau en évitant la pénalisation en ce qui concerne les exigences d'autoconsommation et en réduisant la dégradation et l'entretien des systèmes de stockage d'énergie.L’EMS proposé s'est également révélé capable de charger de préférence les batteries des véhicules électriques en période de surplus d’énergie et les décharger pendant les périodes de déficit pour réduire les échanges d’énergie avec le réseau principal. Les résultats ont aussi montré que la contribution des batteries de véhicules électriques dépend de la taille du parc de véhicules, de leur temps de connexion et du profil de déséquilibre de puissance. En conclusion, à travers les simulations utilisant le dimensionnement réel d'un bâtiment public et résidentiel, l’EMS hiérarchique s'est avéré efficace pour gérer de nombreux dispositifs de stockage d'énergie et contribuer à l’essor de micro-réseaux dédiés aux bâtiments à l’avenirRepresenting 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
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Akhlagi, Ali. "A Modelica-based framework for modeling and optimization of microgrids." Thesis, KTH, Energiteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263037.
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Microgrids have lately drawn much attention due to their considerable financial benefits and the increasing concerns about environmental issues. A solution that can address different engineering problems - from design to operation - is desired for practical reasons and to ensure consistency of the analyses. In this thesis, the capabilities of a Modelicabased framework is investigated for various microgrid optimization problems. Various sizing and scheduling problems are successfully formulated and optimized using nonlinear and physical component models, covering both electrical and thermal domains. Another focus of the thesis is to test the optimization platform when varying the problem formulation; performance and robustness tests have been performed with different boundary conditions and system setups. The results show that the technology can effectively handle complex scheduling strategies such as Model Predictive Control and Demand Charge Management. In sizing problems, although the platform can efficiently size the components while simultaneously solving for the economical load dispatch for short horizons (weekly or monthly), the implemented approach would require adaptations to become efficient on longer horizons (yearly).
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Xie, Lutao. "Numerical approaches to optimize dispatch on microgrids with energy storage." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104567.
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Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2016.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 49-50).
Microgrids and distributed generation are predicted to become extremely dominant in developing nations, and will be largely beneficial to both electricity suppliers and consumers. With the penetration of renewable energy into the electricity supply, to maintain a balance between power supply and demand is becoming more difficult. Nevertheless, it is quite feasible that large electrical storage systems such as batteries can efficiently mitigate problems caused by the intermittency of renewables, and thus enable stable adoption of such power sources. In order to understand how the energy capacity and power characteristics of batteries should be specified to optimize economic or socioeconomic benefits, an optimizing strategy for battery usage in microgrids energy scheduling was constructed. This strategy is based on the past power consumption, predictions of day-ahead power consumption, and historical trends of seasonal and daily trends, which gives a nonlinear, discontinuous and high dimensional objective function. Optimizing such an objective function is found to be very computational intensive and complex. In this paper, the nature of this large-scale optimization problem is studied. For real time dispatch, four optimization methods including active-set, interior-point method, sequential quadratic programming (SQP) and trust-region-reflective are discussed and compared to find the relatively fast and robust optimization algorithm. The computation was implemented by using the MATLAB nonlinear programming solver 'fmincon'. Three main objectives are carried out to improve the efficiency of solving this optimization problem: (1) determination of the mathematical& physical definitions of tolerances and discussion on convergence criteria with the corresponding tolerances; (2) Study and comparison on influences of the initial condition and the behavior of the objective function (highly related to peak demand charge); and (3) suggestions on modification of the model to achieve reduction of the computation time whilst maintain acceptable accuracy.
by Lutao Xie.
S.M.
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Aleksandar, Selakov. "Оптимално управљање микро мрежама у карактеристичним радним режимима." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2017. https://www.cris.uns.ac.rs/record.jsf?recordId=104672&source=NDLTD&language=en.
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У дисертацији је дат концепт микро мрежа и описане постојеће методе у управљању и оптимизацији рада микро мрежа. Предложен је нови централизовани контролер микро мрежe заснован на технологији више-агентног система, који омогућава координацију три режима рада (повезани, острвски и хаваријски) и обезбеђује једноставну конфигурацију и комбинацију оптимизационих критеријума, уз уважавање широког скупа ограничења. Предложени модел примењен је на релевантни тест систем и резултати су приказани уз одговарајућу анализу резултата.U disertaciji je dat koncept mikro mreža i opisane postojeće metode u upravljanju i optimizaciji rada mikro mreža. Predložen je novi centralizovani kontroler mikro mreže zasnovan na tehnologiji više-agentnog sistema, koji omogućava koordinaciju tri režima rada (povezani, ostrvski i havarijski) i obezbeđuje jednostavnu konfiguraciju i kombinaciju optimizacionih kriterijuma, uz uvažavanje širokog skupa ograničenja. Predloženi model primenjen je na relevantni test sistem i rezultati su prikazani uz odgovarajuću analizu rezultata.
Dissertation provides the microgrids concept and describes existing methods for control and optimization of microgrid operation. This paper proposes a novel, centralized, multi-agent-based, microgrid controller architecture, which provides the coordination of all three operation modes (grid-connected, island and emergency) and enables the easy configuration/combination of optimization goals that are subject to a given set of operational constraints.The simulation results are presented for a typical microgrid test example.
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Yuan, Chen. "RESILIENT DISTRIBUTION SYSTEMS WITH COMMUNITY MICROGRIDS." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1480478081556766.
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Karlnoski, Rachel Anne. "Optimization of anti-Abeta antibody therapy." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002145.
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Constante, Flores Gonzalo Esteban. "Conservation Voltage Reduction of Active Distribution Systems with Networked Microgrids." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531861356445195.
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Rigaut, Tristan. "Time decomposition methods for optimal management of energy storage under stochasticity." Thesis, Paris Est, 2019. http://www.theses.fr/2019PESC2015/document.
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L'évolution du stockage d'énergie permet de développer des méthodes innovantes de gestion de l'énergie à une échelle locale. Les micro réseaux électriques sont une forme émergente de petits réseaux électriques munis de production locale, de stockage d'énergie et en particulier d'un système de gestion de l'énergie (EMS pour Energy Management System). De nombreuses études et recherches scientifiques ont été menées pour proposer diverses stratégies d'implémentation de ces EMS. Néanmoins il n'existe pas à ce jour d'articulation claire et formelle de ces méthodes permettant leur comparaison. L'une des principales difficultés pour les EMS, est la gestion des dynamiques des différents systèmes énergétiques. Les variations de courant vont à la vitesse de l'électron, la production d'énergie solaire photovoltaïque varie au gré des nuages et différentes technologies de stockages peuvent réagir plus ou moins vites à ces phénomènes imprévisibles. Nous étudions dans ce manuscrit, un formalisme mathématique et des algorithmes basés sur la théorie de l'optimisation stochastique multi-étapes et la Programmation Dynamique. Ce formalisme permet de modéliser et de résoudre des problèmes de décisions inter-temporelles en présence d'incertitudes, à l'aide de méthodes de décomposition temporelle que nous appliquons à des problèmes de gestion de l'énergie. Dans la première partie de cette thèse, "Contributions à la décomposition temporelle en optimisation stochastique multi-étapes", nous présentons le formalisme général que nous utilisons pour décomposer en temps les problèmes d'optimisation stochastique avec un grand nombre de pas de temps. Nous classifions ensuite différentes méthodes de contrôle optimal au sein de ce formalisme. Dans la seconde partie, "Optimisation stochastique de stockage d'énergie pour la gestion des micro réseaux", nous comparons différentes méthodes, introduites dans la première partie, sur des cas réels. Dans un premier temps, nous contrôlons une batterie ainsi que des ventilations dans une station de métro récupérant de l'énergie de freinage des trains, en comparant quatre algorithmes différents. Dans un second temps, nous montrons comment ces algorithmes pourraient être implémentés sur un système réel à l'aide d'une architecture de contrôle hiérarchique de micro réseaux électrique en courant continu. Le micro réseaux étudié connecte cette fois ci de l'énergie photovoltaïque à une batterie, une super-capacité et à une charge électrique. Enfin nous appliquons le formalisme de décomposition par blocs temporels présenté dans la première partie pour traiter un problème de gestion de charge de batterie mais aussi de son vieillissement long terme. Ce dernier chapitre introduit 2 algorithmes basés sur la décomposition par blocs temporels qui pourraient être utilisés pour le contrôle hiérarchique de micro réseaux ou les problèmes d'optimisation stochastique présentant un grand nombre de pas de temps. Dans la troisième et dernière partie, "Logiciels et expériences", nous présentons DynOpt.jl un paquet développé en langage Julia qui a permis de développer toutes les applications de cette thèse et bien d'autres. Nous étudions enfin l'utilisation de ce paquet dans un cas de pilotage réel de système énergétique : la gestion intelligente de la température dans une maison de l'équipement Sense CityThe development of energy storage paves the way to innovative methods to manage energy at a local scale. Micro grids are a novel kind of electrical grids with local production (renewable and waste energy), local demand, local storage and an Energy Management System (EMS). A wide literature already studies EMS implementations in micro grids but the produced methods are not exhaustively framed and compared. One of the main difficulty in micro grids energy management is to handle the different dynamics of electrical devices. Current variations are lighting fast, solar power changes quickly, different kind of storage react at different paces and batteries ageing is a slow process. We studya mathematical framework and algorithms, based on multistage stochastic optimization theory and Dynamic Programming, to model and solve energy management problems in micro grids with time decomposition methods. In the first part of this thesis, Contributions to time decomposition in multistage stochastic optimization, we present a general framework to decompose temporally large scale stochastic optimization problems into smaller subproblems. We then classify multiple existing resolution methods inside this framework. In the second part, Stochastic optimization of energy storage for management of micro grids, we compare different methods presented in the first part on realistic applications. First we control a battery and a ventilation in a subway station recovering subways braking energy with four different algorithms. Then we present how these results could be implemented on a real micro grid. We implement a fast online control method to stabilize the voltage in a simulated islanded DC micro grid connecting solar panels, an electrical load and two sorts of energy storage: a battery and a supercapacitor. Finally we apply our time decomposition framework to a problem of long term aging and energy management of a storage in a micro grid. This last chapter introduces a framework to model time decomposition of micro grids hierarchical control architectures, as well as two algorithms to solve temporally large scale stochastic optimization problems.In the third part, Softwares and experimentations, we present DynOpt.jl, a Julia language package developed to produce all the results of this thesis and more. Then we study an application of this software to the control of a real test bed: the energy aware temperature regulation of a real house in the equipment named "Sense City"
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Salameh, Khouloud. "Écosystème numérique pour une meilleure gestion des microréseaux." Thesis, Pau, 2017. http://www.theses.fr/2017PAUU3010/document.
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Durant la dernière décennie, de nouveaux concepts ont émergé dans le domaine de l'électricité, notamment les Smart Grids, la génération distribuée et les Microgrids (MGs). Dans cette thèse, nous nous concentrons principalement sur l'étude des MGs. Selon les prévisions des spécialistes du domaine, les MGs devraient prendre une place de plus en plus importante dans les futurs systèmes électriques. Mais pour cela, ils devront être mieux gérés, et il faudra donc d’abord résoudre plusieurs problèmes importants : l’identification, la mobilité, l’aspect multi-rôles, l’interopérabilité, la non-coopération et la planification de l’offre et la demande de l’électricité. Afin de résoudre tous ces problèmes, nous proposons un Framework dédié composé de 3 couches : physique, de connaissance et de gestion. Trois principales contributions sont présentées dans ce travail ciblant la résolution des problèmes déjà cités : OntoMG : un modèle d'information ontologique pour les Microgrids, DECF : un modèle coopératif pour l’optimisation de l’échange d’électricité dans le MG, et MOCSF : une planification coopérative multi-objectifs de l’électricité dans le MG. OntoMG est un modèle ontologique de données, basé sur les standards IEC 61970 et IEC 61580, complété par un nombre de paramètres additionnels permettant au MG d’atteindre l’ensemble de ses objectifs. Notre approche présente plusieurs avantages par rapport aux approches existantes dans la littérature scientifique, notamment : elle permet une planification de la consommation, la production et le stockage de l’électricité dans le MG, elle considère plusieurs sources d'énergie contrairement aux approches existantes qui ne prennent en compte que l'interaction des consommateurs avec une seule source d'énergie, et elle prend en compte l’ensemble des préférences des composants du MG à la différence des approches existantes qui ne considèrent ces préférences qu’en partieOver the past decade, new concepts have emerged in the electricity field, including the Smart Grids, the Distributed Generation and the Micro- grids (MGs). In this thesis, we will be mainly focusing on the study of the MGs. An MG is a small-scale power system, consisting of local power generation, local loads and energy storage systems. Thanks to their numerous economical, ecological and operational benefits, the MGs are expected to hold the promise of becoming a major ingredient in the implementation of the future power systems. However, there are several significant challenges to overcome in order to achieve its expected bene- fits, namely: the cyber-attacks, the mobility aspect, the interoperability, the non-cooperation, and the demand-side management. Three main contributions are developed. First, we present OntoMG, an ontology-based data model, capable of representing the heterogeneous components of the MG and their properties, while being compliant with existing models and information standards (i.e., IEC 61970 and IEC 61850) and coping with the interoperability issues and the multi-objective aspect of MG. Secondly, we introduce DECF, a cooperative model for the optimization of the electricity exchange in the MG, offering several advantages over existing approaches, in particular: 1) its generic in that it considers all heterogeneous components of MG, 2) it is a cooperative model that reduces the technical, ecological and economic costs and encourages the local power exchange, and 3) it is user-oriented in that it gives the user the possibility to fine-tune the weight of each objective aspect . Finally, we introduce MOCSF, a ‘Multi-objective Cooperative Scheduling Framework’ designed for scheduling the production, consumption and storage in the MG. MOCSF 1) provides a multi-type scheduling in that it allows the scheduling of all the power consumption, production and storage of the MG, 2) considers multiple energy sources and 3) considers the MG components’ preferences. After detailing the existing power scheduling techniques and their drawbacks regarding our challenges, we presented our ‘MOCSF’ modules: The Preference-based compromise builder, designed to generate the best balance between the sellers and buyers desired schedules and the Multi-Objective Scheduler, aiming at scheduling the seller-to-buyer associations resulting from the DECF, while reducing the operational, economic and ecological costs of the MG. An illustrative example is provided after each step to ease the understanding of each module. Finally, a set of experiments showed the performance and efficiency of our approach. Illustrative examples are provided after each step to facilitate understanding of each module. Then, a number of simulations are made to show the effectiveness of our approaches to solve our challenges in relation to the existing approaches
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Kanchev, Hristiyan. "Gestion des flux énergétiques dans un système hybride de sources d’énergie renouvelable : Optimisation de la planification opérationnelle et ajustement d’un micro réseau électrique urbain." Thesis, Ecole centrale de Lille, 2014. http://www.theses.fr/2014ECLI0001/document.
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L’objectif est de développer un algorithme de gestion énergétique d’un parc de production comprenant de la production distribuée sous forme de micro turbines à gaz et de générateurs PV pilotables dits «actifs » en vue de minimiser le coût économique et environnemental. Les principes généraux de la production d’électricité à base d’énergie renouvelable et non renouvelable sont d’abord présentés et le fonctionnement actuel des réseaux électriques est rappelé pour situer les innovations attendues dans les futurs réseaux dits intelligents. Ensuite, un algorithme de suivi du point de puissance maximale et de puissance limitée dans un générateur actif PV est présenté. La modélisation des micro-turbines à gaz est aussi présentée. La contribution principale concerne la conception d’une planification opérationnelle des moyens de production la veille pour le lendemain à partir de prédictions de la charge et de la production PV en utilisant une programmation dynamique adaptée. La méthode proposée prédétermine le profil de production des générateurs de manière à réaliser une optimisation globale d’une fonction objective pour un réseau électrique urbain. Pour l’exploitation, un algorithme d’ajustement est proposé et intervient toutes les ½ heures de manière à prendre en compte les déviations par rapport aux prédictions en utilisant un réseau de communication. Un micro réseau urbain est utilisé pour tester les algorithmes de gestion implantés dans un superviseur interfacé à un simulateur temps réel. Des comparaisons dans des situations identiques avec différentes fonctions objectives sont réalisées ainsi que des évaluations économiques et environnementales à l’aide d’indicateursThe presented research works aim to develop an energy management system for a cluster of distributed micro gas turbines and controllable PV generators called «active generators». The general principles of electricity generation from renewable and non-renewable energy sources are first presented. The operation of actual electric grids is also recalled in order to highlight the challenges and expected innovations in future Smart Grids. Then, the integration of a novel method for maximum and limited power point tracking in a PV-based active generator is presented. The modeling of micro-gas turbines in a microgrid energy management system is also presented. The main contribution of this thesis concerns the design of an operational planning of generators one day ahead by the means of a dynamic programming-based algorithm, taking into account the PV power production and the consumption forecasts. The proposed method calculates the production planning of generators by performing a global optimization of an objective function. An adjustment algorithm is proposed and executed every ½ hours through a communication network in order to take into account the uncertainty in forecasted values. An urban microgrid is used for testing the developed algorithms through Supervisory Control and Data Acquisition (SCADA) with hardware-in-the-loop and real-time simulations. Comparisons of the microgrid operation in identical situations with different objective functions are performed, as well as evaluations of economic and environmental indicators
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Bhela, Siddharth. "A Game-theoretic Framework to Investigate Conditions for Cooperation between Wind Power Producers and Energy Storage Operators." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/52026.
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Game theory has its applications in various domains, but has only recently been applied to study open problems in smart microgrids. A simple microgrid system with a small wind farm, a storage facility and an aggregate load entity is studied here using a non-cooperative game-theoretic framework.
The framework developed is used to study the behavior of rational market participants (players), namely wind power producer and energy storage. The framework is implemented to find the existence of any Nash equilibria and see if cooperation is a natural outcome of the game. If cooperation is not self-enforcing then usefulness of the framework to find the conditions for cooperation is presented. It must be noted that cooperation is not automatically guaranteed as the payoff of the energy storage operator is dependent on the strategy employed by the wind power producer. Similarly, the payoff for the wind power producer is highly intertwined with the strategy employed by the energy storage operator. Historical weather and market data is used to calculate expected payoffs for each possible combination of strategies. The results are presented in the form of payoff matrices and the best response algorithm and/or elimination of dominated strategies is used to find the Nash equilibrium.
Sensitivity of the Nash equilibrium to various storage parameters like storage size, charging/discharging limits, charging/discharging efficiency, and other market parameters like energy imbalance penalties, efficiency of up/down regulation, and electricity market prices is studied and necessary conditions for cooperation are presented.Master of Science
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Nemati, Mohsen Shiralizadeh [Verfasser]. "Optimization of Unit Commitment and Economic Dispatch in Microgrids Based on Genetic Algorithm and Mixed Integer Linear Programming / Mohsen Shiralizadeh Nemati." Kassel : Kassel University Press, 2018. http://d-nb.info/1161470972/34.
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Alramlawi, Mansour [Verfasser], Georg Akademischer Betreuer] Frey, Peter [Akademischer Betreuer] [Bretschneider, and Pu [Gutachter] Li. "Model-based optimization of PV-based microgrids considering grid blackout and battery lifetime / Mansour Alramlawi ; Gutachter: Pu Li ; Georg Frey, Peter Bretschneider." Ilmenau : TU Ilmenau, 2021. http://d-nb.info/1239050178/34.
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Cano-Andrade, Sergio. "Thermodynamic Based Framework for Determining Sustainable Electric Infrastructures as well as Modeling of Decoherence in Quantum Composite Systems." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/25878.
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In this dissertation, applications of thermodynamics at the macroscopic and quantum levels of description are developed. Within the macroscopic level, an upper-level Sustainability Assessment Framework (SAF) is proposed for evaluating the sustainable and resilient synthesis/design and operation of sets of small renewable and non-renewable energy production technologies coupled to power production transmission and distribution networks via microgrids. The upper-level SAF is developed in accord with the four pillars of sustainability, i.e., economic, environmental, technical and social. A superstructure of energy producers with a fixed transmission network initially available is synthesized based on the day with the highest energy demand of the year, resulting in an optimum synthesis, design, and off-design network configuration. The optimization is developed in a quasi-stationary manner with an hourly basis, including partial-load behavior for the producers. Since sustainability indices are typically not expressed in the same units, multicriteria decision making methods are employed to obtain a composite sustainability index.
Within the quantum level of description, steepest-entropy-ascent quantum thermodynamics (SEA-QT) is used to model the phenomenon of decoherence. The two smallest microscopic composite systems encountered in Nature are studied. The first of these is composed of two two-level-type particles, while the second one is composed of a two-level-type particle and an electromagnetic field. Starting from a non-equilibrium state of the composite and for each of the two different composite systems, the time evolution of the state of the composite as well as that of the reduced and locally-perceived states of the constituents are traced along their relaxation towards stable equilibrium at constant system energy. The modeling shows how the initial entanglement and coherence between constituents are reduced during the relaxation towards a state of stable equilibrium. When the constituents are non-interacting, the initial coherence is lost once stable equilibrium is reached. When they are interacting, the coherence in the final stable equilibrium state is only that due to the interaction. For the atom-photon field composite system, decoherence is compared with data obtained experimentally by the CQED group at Paris. The SEA-QT method applied in this dissertation provides an alternative and comprehensive explanation to that obtained with the "open system" approach of Quantum Thermodynamics (QT) and its associated quantum master equations of the Kossakowski-Lindblad-Gorini-Sudarshan type.Ph. D.
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Truong, Duc Trung [Verfasser], Jörg [Akademischer Betreuer] Raisch, Jörg [Gutachter] Raisch, Kai [Gutachter] Strunz, and Johann [Gutachter] Reger. "Stability, voltage performance and power sharing issues of inverter-based microgrids via LMI optimization / Duc Trung Truong ; Gutachter: Jörg Raisch, Kai Strunz, Johann Reger ; Betreuer: Jörg Raisch." Berlin : Technische Universität Berlin, 2018. http://d-nb.info/116565038X/34.
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Pajot, Camille. "OMEGAlpes : outil d’aide à la décision pour une planification énergétique multi-fluides optimale à l’échelle des quartiers." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT042.
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Majoritairement responsable du dérèglement climatique, le secteur de l’énergie est particulièrement visé et des politiques de transition énergétique voient le jour, en s’appuyant sur les principes de sobriété, d’efficacité et de productions énergétiques bas-carbone. Les systèmes énergétiques doivent s’adapter rapidement à ces changements et être conçus de façon à intégrer une approche multi-énergies et des stratégies de gestion de la demande. Dans ce contexte, cette thèse propose de développer une méthodologie et un outil d’aide à la décision associé, offrant aux différents acteurs énergétiques une aide pour concevoir, dimensionner, et gérer les systèmes énergétiques au niveau des quartiers. En premier lieu, une approche de planification énergétique par optimisation sera développée. Une méthodologie, basée sur des bilans de puissance sera ensuite présentée, pour traiter de façon générique des cas d’étude de planification énergétique à l’échelle du quartier, puis illustrée sur un cas de valorisation de chaleur fatale. Des modèles de consommation basés sur des approches statistiques seront ensuite employés, afin de représenter des scénarios de flexibilité temporelle (décalage d’usages). Une alternative à cette approche par les données, basée sur la modélisation physique des bâtiments, sera ensuite présentée à travers l’utilisation de modèles thermiques réduits. Enfin, l’ensemble de ces modèles sera capitalisé au sein d’un outil de génération automatique de modèles d’optimisation, s’appuyant sur une méthodologie de construction de modèles énergétiques à partir d’éléments génériques. Le développement de cet outil open source, en langage Python, et le principe de génération automatique des modèles sera enfin détailléMostly responsible for climate change, the energy sector is particularly targeted and energy transition policies are emerging, based on the principles of sobriety, efficiency and low-carbon energy production. Energy systems need to adapt quickly to these changes and be designed to consider a multi-energy approach and demand-side management strategies. In this context, this thesis proposes to develop a methodology and an associated decision support tool OMEGAlpes, offering the different energy actors an aid to design, size, and manage energy systems at the district level. First, an optimal energy planning approach will be developed. A methodology, based on power balances will then be presented, to treat generically study cases about energy planning at the district scale, and then illustrated on a case of wasted heat recycling. Consumption models based on statistical approaches will then be used to represent temporal flexibility scenarios (load shifting). An alternative to this data approach, based on the physical modeling of buildings, will then be presented through the use of reduced thermal models. Finally, all of these models will be capitalized within an automatic generation tool for optimization models, based on a methodology for building energy models from generic elements. The development of this open source tool, in Python language, and the principle of automatic generation of models will finally be detailed
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Pinto, Espinoza Carolina [Verfasser], and Friedrich [Akademischer Betreuer] Koch-Nolte. "Optimization of nanobodies for in vivo targeting of P2X7 ion channel on brain microglia and kidney T cells / Carolina Pinto Espinoza ; Betreuer: Friedrich Koch-Nolte." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2019. http://d-nb.info/119028572X/34.
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Pinto, Espinoza Carolina Verfasser], and Friedrich [Akademischer Betreuer] [Koch-Nolte. "Optimization of nanobodies for in vivo targeting of P2X7 ion channel on brain microglia and kidney T cells / Carolina Pinto Espinoza ; Betreuer: Friedrich Koch-Nolte." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2019. http://nbn-resolving.de/urn:nbn:de:gbv:18-97989.
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Fernandez, Orjuela Julian Alberto. "Intégration des véhicules électriques dans le réseau électrique résidentiel : impact sur le déséquilibre et stratégies V2G innovantes." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENT044/document.
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Ces travaux de recherche constituent une contribution à l'étude des interactions entre le réseau électrique et le véhicule électrique (VE) en mode de recharge (Vehicle-to-Grid V2G). La recharge des VEs engendrant des surconsommations variant entre deux et plusieurs dizaines de kilowatts, occasionne des perturbations sur la qualité de l'énergie du réseau auquel ils sont connectés ; la gestion de l'énergie délivrée au VE est donc une priorité pour les différents acteurs industriels qui ont établi les infrastructures de recharge. Dans cette thèse nous proposons d'étudier l'impact des nombreux VEs en mode de recharge sur le déséquilibre en courant et en tension du réseau de distribution basse tension ainsi que sur les stratégies de recharge à mettre en œuvre pour améliorer la qualité de l'énergie, et notamment minimiser les taux de déséquilibre. Nous commençons par définir le besoin de réduire le déséquilibre en courant et en tension dans le réseau résidentiel de basse tension. Ensuite, nous étudions l'impact du taux d'insertion des VEs sur ces déséquilibres en estimant la sensibilité des paramètres statistiques les décrivant. Enfin, nous proposons des stratégies de gestion de la recharge et de la décharge cherchant à minimiser les déséquilibres occasionnés tout en respectant les contraintes de confort, c'est-à-dire de la recharge du VE avant le départ et les limites structurelles du systèmeThe study of the Vehicle to Grid (V2G) interactions is the main contribution of this research work. To charge an electric vehicle (EV) battery the overloading in low voltage (LV) residential networks is expected to be between 2 kW and maximum 10kW. To avoid power quality deterioration a battery recharge management is a priority for the charging infrastructure business. Our work has been, first, to study the impact of a significant number of EVs in recharge mode on the voltage and current unbalances in a LV residential electric network scenario and second to develop charging strategies to minimize those unbalances.First, we defined why it is important for the LV residential network to minimize the unbalances both in current and in voltage. Then, we studied the impact of different market penetration rates of the EV on the unbalances by estimating the sensibility of the statistical parameters describing them. Finally we developed several charging/discharging strategies in order to minimize the current unbalance by using optimization algorithms in the continuous and discrete domains. Several constraints were formulated in order to preserve power limits and an enough state of charge for the mobility
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Mouhammad, Al Anfaf Mohamed Mladjao. "Contribution à la modélisation et à l’optimisation de systèmes énergétiques multi-sources et multi-charges." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0127/document.
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La demande énergétique mondiale continue d’augmenter. Les prix des énergies fossiles sont instables et incertains. La libéralisation du marché électrique et une conscience environnementale des acteurs mondiaux sont des leviers au développement des énergies renouvelables. Ces dernières se développent à un rythme rapide dans le monde. Elles ont atteint une maturité technique qui leur permet de devenir un segment important de l’industrie de l’énergie. Leur insertion dans le mix énergétique pose de nouveaux défis par rapport aux sources d'énergie traditionnelles. Avec un potentiel abondant encore sous-exploité, le photovoltaïque et l'énergie éolienne sont avantageux sur le plan économique et environnemental. Cependant, leur caractère intermittent diminue leur efficacité énergétique lorsqu’elles sont exploitées individuellement. L'utilisation de systèmes hybrides (multi-sources) combinant ces sources d'énergie renouvelables, le réseau de distribution national (réseau électrique historique) et les systèmes de stockage classiques, est généralement considérée par tous comme solution d’avenir, à la fois efficiente et fiable. Il est alors nécessaire de repenser la structure des réseaux électriques et des marchés de l’énergie, ainsi que des changements dans les méthodes de gestion de réseau. Dans ce contexte, l’apport envisagé avec ce travail de thèse est de contribuer à la modélisation et l’optimisation de systèmes multi-sources multi-charges pour alimenter aussi bien des sites isolés « énergie de proximité » (campus, village) que des sites étendus tels que des régions françaises à travers leur interconnexion « pooling ». Différents scenarii de gestion et différentes configurations des systèmes sont modélisés, testés et comparés pour analyser l’efficacité et la robustesse de chaque cas de figure. Une analyse technico-économique complète est réalisée, dans le but d’étudier la faisabilité de chaque système. Pour démontrer la validation de ces modèles, des études ont été réalisées sur un campus Universitaire Français, un micro-réseau au Mali et trois régions Françaises. Ces dernières ont fait l’objet d’application à un modèle original d’interconnexion basé sur les réseaux de Pétri pour l’aide à la décision en termes de configurations du réseau et le contrôle des flux d’énergie échangés entre des territoires producteurs-consommateurs interconnectés sans système de stockageGlobal energy demand continues to rise. The fossil fuel prices are unstable and uncertain. The liberalization of the electricity market and environmental awareness of the global leaders are levers for the development of renewable energy. These are growing at a rapid pace in the world. They reached technical maturity that enables them to become an important segment of the energy industry. Their integration in the energy mix poses new challenges compared to traditional energy sources. With an underexploited potential, photovoltaic and wind energy are advantageous economically and environmentally. However, their intermittent decreases their energy efficiency when operated. The use of hybrid systems (multi-sources) combining these renewable energy sources, the national distribution network (historical grid) and conventional storage systems, is generally regarded by all as a future solution, both efficient and reliable. Thereby, it is necessary to rethink the structure of electrical networks and energy markets, and changes in network management methods. In this context, the foreseen intake with this thesis is to contribute to the modeling and optimization of multi- load multi- source systems to power both remote sites “closeness energy” (campus, village) and large sites such as French regions through their interconnection "pooling ". Different scenarios of management and different configurations of the systems are modeled, tested and compared to analyze the effectiveness and robustness of each case. A complete technical and economic analysis is performed in order to study the feasibility of each system. To demonstrate the validation of these models, studies were performed on a French university campus, a Micro-grid in Mali and three French regions. These latter have been applied to an original interconnection model based on Petri nets for decision support in terms of network configuration and control of energy flows exchanged between interconnected producers/consumers territories without storage
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Yu-Chan, Hung, and 洪語禪. "Optimization of BESS setting in the Microgrid." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/16054511464316982631.
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碩士國立臺灣海洋大學
電機工程學系
103
Abstract Primary energy is facing the problem of running out fuel and globalwarming is more and more serious so that developing green energy, which has low pollution and zero fuel cost, has become the main issue in the world. Based on the volatility of renewable power generation, smart grid and microgridare being developed to schedule these distributed generation effectively. In this study, we construct a microgrid model by the some of data and forecast, and we solve a unit commitment with power flow constraint in the microgrid by using a genetic algorithmcombined with linear programming to reach the minimum cost. To confirm the proposed program is availability under different operating conditions, multi- simulation cases of microgrid are discussed. The result of this study can efficiently use the renewable energy in the microgrid and reduce generation costs. Keywords: Unit Commitment, Microgrid, Genetic algorithm, LinearProgramming.
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Tseng, Yi-Chih, and 曾翊誌. "Coordination Optimization of the Overcurrent Relay for Microgrid System." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/7345yw.
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碩士國立臺灣科技大學
電機工程系
99
In this thesis, a distribution network, characterizing the microgrid, is constructed with a solar power system, diesel engine generators and wind turbines established by using Matlab/Simulink. Microgrid may be operating in the island mode or connected mode. And it needs to be protected under any type of mode. Therefore, this thesis is discussed the coordination optimization of overcurrent relay for microgrid system. In the relay setting, through the three-phase fault current analysis and ground fault current analysis, using the particle swarm algorithm to set the pickup current value and the time dial setting of the overcurrent relay and ground overcurrent relay. In addition, central control unit is joined to microgrid for adjusting relay parameters; therefore, protective systems can maintain protective coordination under different modes.