Dissertations / Theses: 'Networked microgrid'

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Zhang, Fan. "Operation of Networked Microgrids in the Electrical Distribution System." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1467974481.

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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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Irwin, Robert. "Evaluation of a Generator Networked Control System in the Presence of Cyberattacks." Master's thesis, Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/433164.

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Educational Psychology M.S.E.E. With the advancement of technology, there has been a push to transition from the conventional electric grid to a smart grid. A smart grid is an electric delivery system that uses technology such as electronic sensors and digital communication networks to improve the reliability, resilience, and efficiency of the system. The transition toward a smart grid has increased the importance of networked control systems (NCS), which are the infrastructure that allows sensors, actuators and controllers to exchange information via a digital communication network. The research presents the development of an islanded generator NCS, and a grid connected NCS, and the investigation of the effects of cyberattacks on the NCS. This research considers two types of cyberattacks, such as Denial-of-Service (DoS) attack, and false data injection in the generator control loop. DoS attacks greatly increase the rate of packet loss and the duration of packet delay in a network. A high degree of packet drop and delay degrade the performance of the controller, which causes problems in the synchronization of the generator with the rest of the grid. False data injection in the sensors alters the generator terminal voltage and power output, and can cause the generator to lose synchronism. A mathematical model of the generator NCS systems is developed which includes the data acquisition and network characteristics, as well as the generator dynamics. The stability analysis of each NCS is performed which provides a mathematical approach to understanding the severity of cyberattacks that the system can tolerate before becoming unstable. The performance of the controllers, with respect to voltage control, is experimentally evaluated. Temple University--Theses

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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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Darden, Kelvin S. "Smart Microgrid Energy Management Using a Wireless Sensor Network." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404560/.

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Modern power generation aims to utilize renewable energy sources such as solar power and wind to supply customers with power. This approach avoids exhaustion of fossil fuels as well as provides clean energy. Microgrids have become popular over the years, as they contain multiple renewable power sources and battery storage systems to supply power to the entities within the network. These microgrids can share power with the main grid or operate islanded from the grid. During an islanded scenario, self-sustainability is crucial to ensure balance between supply and demand within the microgrid. This can be accomplished by a smart microgrid that can monitor system conditions and respond to power imbalance by shedding loads based on priority. Such a method ensures security of the most important loads in the system and manages energy by automatically disconnecting lower priority loads until system conditions have improved. This thesis introduces a prioritized load shedding algorithm for the microgrid at the University of North Texas Discovery Park and highlight how such an energy management algorithm can add reliability to an islanded microgrid.

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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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Qiu, Quanwei. "Networked Model Predictive Control for Microgrids with Distributed PV Generators." Thesis, Griffith University, 2020. http://hdl.handle.net/10072/400460.

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More and more renewable energy sources are being integrated into microgrids—and while this causes many control challenges for microgrids, it can also yield numerous economic and environmental benefits. Therefore, it is necessary to develop proper control schemes for microgrids to address the different control issues in their hierarchical structure while adapting to the different time scales of the three control levels. Conversely, because model predictive control (MPC) has significant advantages—the inclusion of forecasts, the simplicity of the algorithm, and the flexibility to handle hard constraints—it has attracted significant attention in industrial control systems. Motivated by these factors, this research focuses on implementing MPC techniques in microgrids, which are solely supplied by photovoltaic (PV) generators, to address different control problems. For primary control of the microgrid hierarchy, which is mainly responsible for the inner control of the local distributed generation units, MPC can be applied to control of the power converters that serve as interfaces between the sources and the loads. Therefore, in this control level, a novel output-feedback MPC technique based on ellipsoidal set-membership state estimation is designed for a direct current to direct current (DC-DC) converter, considering the unknown-but-bounded external disturbances. A long-horizon finite-states (FS) MPC strategy is designed for the direct current to alternating current (DC-AC) inverter to reduce the sampling and switching frequency through a multi-step implementation approach and a control sequence rearrangement method. For secondary control, which is in charge of the compensation for the frequency and voltage deviations and is usually communication-based, the distributed MPC strategy can be used to realize the desired cooperative control among the geographically dispersed units. Thus, a novel distributed model predictive controller is developed to enhance system performance. It takes into account the fact that the distributed controllers’ communication network might be subject to switching topology due to the disconnection and reconnection of controllers, random failures, and recoveries of the links between controllers. A Markov chain with a time-varying probability transition matrix is used to describe the stochastic topology evolution of the control network. Tertiary control is used to coordinate the power flow between the microgrid and the utility grid and offers economic operations for microgrids. Since the integration of renewable energy sources causes low inertia and power fluctuation in microgrids, battery energy storage is essential to addressing these issues. To coordinate the charging/discharging schedule of the battery storage units, a networked MPC strategy can be adopted to realize the communication between different microgrid components and make use of the forecasts for PV power generation and load demand. The multi-microgrid system is considered subject to partial fault because of non-functional generators, batteries, or even transmission lines in this research. Hence, both the connection status of the electrical grid and the communication network are incorporated into the system modeling. In addition, the set-membership estimation is adopted to deal with the possible state unavailability caused by non-functional batteries or communication failures. In the theoretical section of this thesis, different sufficient conditions are established to ensure the stability of the investigated systems, and the optimal control inputs are obtained by solving the corresponding optimization problems. For easy implementation with MATLAB solvers, all the constraints and conditions of the optimization problems are transformed into linear matrix inequalities. Different recursive MPC algorithms are designed to control the target systems, and some extended algorithms are also developed to assist with the computation to determine the optimal solutions. In the demonstration section of this thesis, the designed controllers are all implemented in the numerical simulations or Simulink tests to verify their effectiveness, and an experimental test based on Raspberry Pi is conducted to demonstrate the wireless communication employing the designed networked model predictive controller. Thesis (PhD Doctorate) Doctor of Philosophy (PhD) School of Eng & Built Env Science, Environment, Engineering and Technology Full Text

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Islam, Mojaharul. "Control and Optimisation of Grid-Connected Microgrids for Tie-line Smoothing." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/404162.

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Renewable energy resources (RESs) are significantly integrated in distribution networks to promote green technologies in future power systems. The idea of microgrids (MGs) is developed for the efficient use of RESs through an appropriate control, monitoring and management system. Control and management of MGs are challenging tasks along with numerous economic and environmental benefits. The challenges of MGs operation include tie-line power fluctuations that have an adverse effect on the stability and quality of distribution networks. Tie-line power control in a residential MG is difficult due to dependency on RESs as a primary generation unit in MGs. Motivated by these, this thesis investigates the tie-line power control issues in grid-connected residential MGs and applies several controls and optimisation methods to achieve a smooth tie-line power satisfying system boundary conditions. First, a dynamic energy management system (EMS) is designed to reduce the tie-line fluctuation in a grid-connected MG through an indirect grid power control strategy. A fuzzy logic-based EMS is proposed to control the battery power due to the variations in generations and loads. The net power demand and battery state of charge (SoC) of an MG are considered inputs of the fuzzy controller to determine the battery power by keeping the battery SoC within limits. An offline optimisation method is used to optimise the membership functions and rules to shape the performance parameters. Thereafter, a golden section search-based non-linear programming method is applied to design a battery power management system to minimise the tie-line fluctuation in an MG counting the system constraints and disturbances. Two other rule-based methods are also demonstrated for comparative analysis of the proposed methods in terms of predefined performance parameters. Afterward, a dynamic grid power control method is presented to control the interlink inverters in grid-connected MGs. A grid power controller is designed based on a complete model of the MG systems to achieve a constant tie-line power on typical days of the year. The designed controller can effectively smooth tie-line fluctuation in a grid-connected residential MG. The charging/ discharging of the battery is controlled by a DC-DC converter which is also responsible to provide a stable DC bus to the input of an interlink inverter. The reference tie-line power is determined by a MG controller based on statistical power generations, load demand and battery SoC. Moreover, an eigenvalue-based stability analysis is performed to show the sensitivity of system parameters on system stability. Furthermore, the tie-line power control in a networked MG (NMG) is investigated to obtain a smooth tie-line power in an NMG connected to a common bus. A model predictive control-based distributed power flow controller is proposed to control the interlink inverters of the NMG in a distributed manner. Charging/ discharging of battery is controlled by a decentralised model predictive power controller to provide a stable DC voltage for MGs. Communication between MGs is performed for sharing the status of the tie-line power along with the scheduled tie-line reference. The information from the network is used to determine the instantaneous reference grid power of individual MGs for achieving a smooth tie-line power for the network. Inverter switching actions are performed to minimise the difference between predictions and references. In addition, a comparative study with a decentralised operation of MGs is conducted to show the benefits of networked operation. All the proposed methods are tested through rigorous case studies to validate the performance despite the variations in input and output system disturbances. Comparative analysis among different methods is also conducted to demonstrate the performance variations through adopting different methods. For the simulation experiment set up, MATLAB SIMULINK Simscape Electrical is used to develop a designed system model of MGs and experimental models of the proposed methods. Experiments are performed using real weather and residential load information in Queensland, Australia. The results demonstrate that the proposed methods have achieved the design objectives to solve the tie-line fluctuation problem of grid-connected residential MGs. Thesis (PhD Doctorate) Doctor of Philosophy (PhD) School of Eng & Built Env Science, Environment, Engineering and Technology Full Text

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He, Youbiao. "The Energy Management of Next-generation Microgrid Systems." University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1500907510831555.

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Гузов, Анатолій Геннадійович. "Модифікована система управління мережею MicroGrid на основі Інтернету Речей". Master's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/39339.

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Робота містить 69 сторінки, 20 рисунків та 25 таблиць. Було використано 32 джерела. Мета роботи: Покращити ефективність системи управління мережею MicroGrid за рахунок її модифікації при застосуванні Інтернету речей. Проаналізовано різні існуючі типи структур інтелектуальних мереж. Зокрема Smart Grid, Smart Power Grid, SCADA системи та MicroGrid. Підсумовано і підтверджено актуальність розробки концепції контролю Інтернету речей над MicroGrid. Розглянуті проблематики, які виникають при впровадженні і експлуатації даної концепції системи. Поставлено за завдання модифікувати створену імітаційну модель управління ІоТ над MicroGrid. Для вирішення поставленного завдання запропонована аналітична модель, заснована на принципах існуючих конецепцій інтелектуальних мереж Smart Grid та Microgrid з урахуванням Інтернету речей з використанням хмарних технологій. У рамках даної імітаційної моделі визначено правила взаємодій елементів системи. Застосування запропонованого рішення дозволяє мати певне представлення системи при її проектуванні, яке відповідає заданій предметній області. Метод мусить передбачати відсутність участі людини, але при формуванні на стільки великої системи не дозволяє ліквідувати її контроль над не контрольованими елементами мережі. Отримані результати доводять на основі імітаційної моделі, що запропонована модифікація є енергоефективною та відмовостійкою. The work contains 69 pages, 20 figures and 25 tables. 32 sources were used. Purpose: To improve the efficiency of the MicroGrid network management system by modifying it when using the Internet of Things. Various existing types of intelligent network structures are analyzed. In particular Smart Grid, Smart Power Grid, SCADA systems and MicroGrid. The relevance of developing the concept of Internet of Things control over MicroGrid is summarized and confirmed. The problems that arise during the implementation and operation of this system concept are considered. The task is to modify the created simulation model of IoT control over MicroGrid. To solve this problem, an analytical model based on the principles of existing concepts of intelligent networks Smart Grid and Micro Grid, taking into account the Internet of Things using useless technologies. Within the framework of this simulation model the rules of interactions of system elements are defined. The application of the proposed solution allows you to have a certain representation of the system in its design, which corresponds to a given subject area. The method must provide for the absence of human participation, but when forming such a large system does not allow to eliminate its control over uncontrolled elements of the network. The obtained results prove on the basis of the simulation model that the proposed modification is energy efficient and fault tolerant.

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Bertot, Charlotte. "Le rôle des cellules microgliales dans le développement des circuits neuronaux." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0414/document.

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Les cellules microgliales constituent la population de macrophages résidents du système nerveux central. De par leur appartenance au système immunitaire, elles furent longtemps considérées actives uniquement en conditions pathologiques. Au contraire, ces dernières décennies, elles sont apparues comme physiologiquement actives, notamment au cours de la période critique de formation du système nerveux central. Au cours du développement embryonnaire et postnatal, les neurones nouvellement générés migrent vers leur position définitive avant de développer leur arbre dendritique et axonal afin de former les connexions synaptiques à la base des réseaux nécessaires aux fonctions cérébrales. L'étude des microglies au cours de la période postnatale, a montré l'implication d'un mode de communication spécifique entre les neurones et la microglie, la voie Fractalkine/CX3CR1, dans la mise en place des cellules microgliales d'une part et dans le développement synaptique glutamatergique d'autre part. Cependant, l'importance de cette communication neurone-microglie pour le développement du système inhibiteur GABAergique est peu connue. Au cours de mon travail de thèse, je me suis intéressée au rôle de la voie de communication FractalKine/CX3CR1 dans la distribution des cellules microgliales et le développement postnatal du réseau GABAergique de l'Hippocampe. Nous avons ainsi montré que la suppression du récepteur microglial CX3CR1 induit une diminution du nombre de microglies dans la région CA3 de l'Hippocampe, dans une fenêtre temporelle précise entre 7 et 2 jours après la naissance. Cette diminution du nombre de microglies est corrélée avec une altération de l'activité de réseau au niveau de cette région. En effet, la fréquence des GDPs (Giant Depolarizing Potentials), une activité de réseau impliquée dans la formation et la maturation des synapses et spécifiquement générée en CA3, est diminuée à la fin de la première semaine postnatale. De plus, malgré l'absence de modification majeure de l'activité synaptique glutamatergique et GABAergique, les évènements postsynaptiques GABAergiques présentent une sous population d'évènements plus amples et des cinétiques légèrement plus rapides, pouvant suggérer une modification de la population d'interneurones mis en jeu. L'ensemble de mon travail de thèse met en évidence l'impact de la communication neurone-microglie par la voie Fractalkine/CX3CR1 sur le développement postnatal de l'Hippocampe Son absence affecte d'une part, la colonisation microgliale, et d'autre part, une activité de réseau caractéristique de l'Hippocampe, dans une fenêtre temporelle critique pour la mise en place des connexions synaptiques et la formation des réseaux neuronaux Microglial cells, the resident macrophages of the central nervous system, were mainly studied for their role in pathological conditions, but they recently appeared to be involved in synaptic development and circuits formation during postnatal period. During this critical period, microglial cells colonize the central nervous system and interact with other cell types, including neurons. A specific way of communication between neurons and microglia involves neuronal released fractalkine (CX3CL1) and its specific microglial receptor CX3CR1. CX3CR1 KO mice contributed to unclose microglial role during development. Indeed, CX3CR1 ablation alters microglia distribution in the brain, and it affects glutamatergic transmission and synapse maturation. However, these effects seem to be transient and brain region specific and their mechanisms are poorly understood. Furthermore, some effects observed in juvenile or adult mice may have origin during development, when neuronal connections are established. GABA plays a fundamental role in this process since it is excitatory The influence of neuron.microglia interaction on neuronal activity in the hippocampus during this period is poorly understood. In particular, nothing is known on GABAergic activity, known to be synaptogenic during this period My PhD project aimed at investigating how the signaling fractalkine pathway impacts microglial coloniation of the hippocampus and neuronal activity during the first two postnatal weeks. Our results indicate that in CX3XR1KO mice there is a reduction in the density of microglial cells at P7-P9 in the CA3 hippocampal area, accompanied at P7 by a significant reduction of frequency of Giant Depolarizing Potentials (GDPs), a network activity involved in hippocampal synapse formation and maturation Furthermore, despite no overall difference in glutamatergic or GABAergic synaptic activity, GABAergic events display a subpopulation of larger events, and the kinetics was slightly faster. Thus, the disruption of the specific neuronal.microglia signaling pathway on one hand impacts the microglia coloniation of the hippocampus and on the other hands affects specifically neuronal network activity during a time window critical for the establishment of neuronal connections

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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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Lundholm, André. "Implementing an OpenAI Gym for Machine Learning of Microgrid Electricity Trading." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42743.

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Samhället går idag bort från centraliserad energi mot decentraliserade system. Istället för att köpa från stora företag som skapar el från fossila bränslen har många förnybara alternativ kommit. Eftersom konsumenter kan generera solenergi med solpaneler kan de också bli producenter. Detta skapar en stor marknad för handel av el mellan konsumenter i stället för företag. Detta skapar ett så kallat mikronät. Syftet med denna avhandling är att hitta en lösning för att köpa och sälja på dessa mikronät. Genom att använda en Q-learning-lösning med OpenAI Gym-verktygslådan och en mikronätsimulering syftar denna avhandling till att svara på följande frågor: I vilken utsträckning kan Qlearning användas för att köpa och sälja energi i ett mikrosystem, hur lång tid tar det köp och sälj algoritm för att träna och slutligen påverkar latens genomförbarheten av Q-learning för mikronät. För att svara på dessa frågor måste jag mäta latens och utbildningstid för Q-learninglösningen. En neural nätverkslösning skapades också för att jämföra med Q-learning-lösningen. Från dessa resultat kunde jag säga att en del av det inte var så tillförlitligt, men vissa slutsatser kunde fortfarande göras. För det första är den utsträckning som Q-learning kan användas för att köpa och sälja ganska bra om man bara tittar på noggrannhetsresultaten på 97%, men detta sitter på mikronätets simulering för att vara korrekt. Hur lång tid det tar att köpa och sälja algoritm för att träna uppmättes till cirka 12 sekunder. Latensen anses vara noll med Q-learning-lösningen, så den har stor genomförbarhet. Genom dessa frågor kan jag dra slutsatsen att en Q-learning OpenAI Gym-lösning är genomförbart. Society is today moving away from centralized power towards decentralized systems. Instead of buying from large companies that create electricity from fossil fuels, many renewable alternatives have arrived. Since consumers can generate solar power with solar panels, they can also become the producers. This creates a large market for trading electricity between consumer instead of companies. This creates a so called microgrid. The purpose of this thesis is to find a solution to buying and selling on these microgrids. By using a Q-learning solution with the OpenAI Gym toolkit and a microgrid simulation this thesis aims to answer the following questions: To what extent can Q-learning be used to buy and sell energy in a microgrid system, how long does it take the buy and sell algorithm to train and finally does latency affect the feasibility of Q-learning for microgrids. To answer these questions, I must measure the latency and training time of the Q-learning solution. A neural network solution was also created to compare to the Q-learning solution. From these results I could tell some of it was not that reliable, but some conclusions could still be made. First, the extent that Q-learning can be used to buy and sell is quite great if just looking at the accuracy results of 97%, but this is on the microgrid simulation to be correct. How long it takes to buy and sell algorithm to train was measured to about 12 seconds. The latency is considered zero with the Q-learning solution, so it has great feasibility. Through these questions I can conclude that a Qlearning OpenAI Gym solution is a viable one.

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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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Qiao, Feng. "Hybrid AC/DC distribution network voltage control." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/22978.

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A hybrid AC/DC distribution network can be formed after integration of increasing numbers of electronically interfaced distributed generators (DGs) and microgrids (MGs). Voltage/Var control (VVC) in this evolved system requires to control not only the traditional VVC resources such as transformer tap changer and shunt capacitor but also the newly emerged ones such as DGs and MGs. In addition, various stakeholders such as MG's operator and distribution network operator coexist in this evolved system. They usually represent distinct operational interests and make the VVC even more difficult. Therefore, VVC in hybrid AC/DC distribution networks expects to addresses not only the coordination among various voltage/var resources but also the conflicting interests of different stakeholders. In this thesis, various VVC schemes are developed to address above mentioned concerns, which provide promising solutions for system operators in future hybrid AC/DC distribution networks. Driven by advancements in power conversion and communication technologies, the dispersed MGs can be participated in VVC scheme and coordinated with other VVC resources. This thesis firstly proposes a VVC scheme to leverage the flexible power injections from grid-tied MGs. The tuning range of MGs' reactive power injections are widen by controlling local energy storage systems. Then, a two-layer VVC control scheme is developed. The upper layer is a multi-objective voltage/var optimisation model that schedules all the VVC resources including grid-tied MGs. The lower layer consists of various controllers in MGs, which aims to maintain the local power quality and to execute the setpoints sending from the upper layer. Although VVC performance can be enhanced by controlling MGs' reactive power injections, a lack of consideration for their active power control could result in deterioration on MG's local power supply. To this end, a coordinated VVC scheme is proposed to link MG's power management with VVC. The control of MG's local devices and control of voltage/var resources in distribution network are allocated into two different but interlinked optimisation models. Furthermore, the mechanically controlled OLTC and SC and electronically controlled DGs and MGs are scheduled in different timescales. Finally, a multi-objective VVC scheme is proposed to maximise the VVC contributions from various stakeholders such as MGs and distribution network operator. Since trade-off solutions are utilised in this scheme, it is promising to be used in multi-lateral cases where MGs are not unilaterally controlled by distribution network operators. The scheme is supported by an identification approach which fairly quantifies the VVC contributions from various stakeholders. Each stakeholder could be rewarded in proportion to its VVC contribution, so their participations are motivated without conflicts to satisfy voltage control requirements.

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Rios, Penaloza Juan Diego <1990&gt. "Protection systems and stability of distribution networks and microgrids with distributed energy resources." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amsdottorato.unibo.it/9871/1/RiosPenaloza_JuanDiego_tesi.pdf.

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The large-scale integration of Distributed Energy Resources in distribution networks has several technical implications and consequences, which increase in complexity when energy sources are of renewable type. Renewable Energy Sources are characterized by intermittent/unpredictable availability and are connected to the grid through converters, often close to the final users, which means that they are more prone to cause instability issues and potential mis-operation of protection schemes. These effects are the objects of this thesis. A protection system against earth faults in radial and meshed distribution networks with unearthed and compensated neutral is proposed and assessed. The faulty feeder identification algorithm is based on the angle between the zero-sequence voltage and current phasors, estimated at the dominant transient frequency inferred from the transient response of the network within the first milliseconds after the fault. The performances of the protection system algorithm are assessed through a Monte Carlo method that considers the fault resistance, incidence angle and fault location variations. The power system is simulated within the EMTP-RV environment, while the protection algorithm is developed in Matlab. Results of a real-time simulation obtained in the Opal-RT environment further support the applicability of the algorithm. Another important aspect of the large deployment of distributed resources are the diffusion of Microgrids (MGs) which are characterized by faster dynamics than conventional distributions systems. In this context, load dynamics considerably affect the transient stability performance of MGs. The transient stability of a medium voltage MG is analyzed in two different cases: an islanding transition and a fault when the MG is standalone. The exclusion of any rotating generator is expected to heighten the load influence on the system dynamics. Modern controllable loads are also included. The system is implemented in the EMTP-RV simulation environment, in Simulink and real-time simulations are carried out in the Opal-RT environment.

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KORJANI, SAMAN. "Planning and Management of Energy Storage in Microgrids according to Complex Network Approach." Doctoral thesis, Università degli Studi di Cagliari, 2019. http://hdl.handle.net/11584/260672.

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This PhD dissertation deals with planning and management of Energy Storage System (ESS) in power systems. Chapter 1 is devoted to the State of the Art of ESS technologies, discussing them according to their structure and physical and chemical proprieties. For each class, the most relevant ESSs are presented and briefly portrayed, featuring their main advantages and drawbacks. In this way, a general comparison is performed with regards of different characterization of ESSs. Chapter 2 refers to planning and management of ESSs in a power system and presents the genetic algorithm-based multi-period optimal power flow (GA-MPOPF) a management method that includes degradation costs in the economic optimization of ESS. The GA-MPOPF includes complex aging function taking into account cycle and calendar degradation costs. This is still an open issue, mainly due to the difficult estimation of cycle aging in presence of high penetration of intermittent Renewable Energy Sources (RESs). The proposed method has been exploited in two different microgrid applications based on real load and generation data: (1) planning of the optimal position of a Li-ion battery ESS (BESS) in the standard 69 IEEE bus network with high RES penetration; (2) the economic management of BESS including cycle and calendar costs. Results demonstrate that GA-MPOPF can optimize the BESS use for one month, notwithstanding the complex operative costs functions, guaranteeing in the meantime excellent convergence properties. Chapter 3 deals with Real-Time planning and management of ESSs in the power systems. The presented GA-MPOPF has been extended to the case of Real-Time aging cost management by including a prediction algorithm based on system identification methods.Two main goals are considered: first, to have a correct BESS size within planning approach; real-time management of the BESS State of Charge (SoC) by taking into account the its degradation costs minimizing the total costs for the whole microgrid. Results show that the accuracy of cost optimization in real time is comparable with the ideal case of a perfect knowledge of the future (i.e. using for Real-Time optimization the actual data). Results also confirm that the method is able to optimize complex cost functions highlighting that a careful sizing of BESS is need to avoid economic losses due to BESS aging costs. Chapter 4 introduces a criterion for the optimal placement of active and reactive power compensator (i.e. ESS) based on complex networks centrality metrics aiming at voltage regulation. The chapter shows the relation between centrality measures and voltage fluctuations in power networks with high penetration of RESs and ESSs. In fact, the correlation between network node centrality (namely Eigenvector, Closeness, Pagerank, Betweenness) and voltage fluctuations is statistically significant implying that the topological characteristics of the power networks are enough to find the optimal positioning of active and reactive power compensators. The results demonstrate that eigenvector centrality shows a statistically significant exponential correlation as the voltage stability increases. This finding provides a quick and easy way to position reactive power compensators in complex networks without the need to compute the traditional Optimal Power Flow (OPF).

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Numair, M., D.-EA Mansour, and Geev Mokryani. "A Proposed IoT Architecture for Effective Energy Management in Smart Microgrids." IEEE, 2020. http://hdl.handle.net/10454/18491.

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yes The current electricity grid suffers from numerous challenges due to the lack of an effective energy management strategy that is able to match the generated power to the load demand. This problem becomes more pronounced with microgrids, where the variability of the load is obvious and the generation is mostly coming from renewables, as it depends on the usage of distributed energy sources. Building a smart microgrid would be much more economically feasible than converting the large electricity grid into a smart grid, as it would require huge investments in replacing legacy equipment with smart equipment. In this paper, application of Internet of Things (IoT) technology in different parts of the microgrid is carried out to achieve an effective IoT architecture in addition to proposing the Internet-of-Asset (IoA) concept that will be able to convert any legacy asset into a smart IoT-ready one. This will allow the effective connection of all assets to a cloud-based IoT. The role of which is to perform computations and big data analysis on the collected data from across the smart microgrid to send effective energy management and control commands to different controllers. Then the IoT cloud will send control actions to solve microgrid's technical issues such as solving energy mismatch problem by setting prediction models, increasing power quality by the effective commitment of DERs and eliminating load shedding by turning off only unnecessary loads so consumers won't suffer from power outages. The benefits of using IoT on various parts within the microgrid are also addressed.

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Waseem, Irfan. "Impacts of Distributed Generation on the Residential Distribution Network Operation." Thesis, Virginia Tech, 2008. http://hdl.handle.net/10919/36394.

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In this research, the impacts of installing DG on a residential distribution circuit are explored. The work is focused on analyzing the impact of DG installation on distribution network operation including voltage analysis, electric losses and reliability of the system. First, various DG penetration levels and the impact of distributing the DG across several locations are explored. Secondly, the impacts of installing DG on any one phase on the voltage profiles of the unbalanced three-phase distribution network are investigated. Thirdly, the losses of the system are analyzed. Next, the reliability analysis (SAIDI, CAIDI, ENS, and AENS) of the system is performed by installing DGs as backup generators. Different DG penetration levels, locations and the impacts of installing one large-scale DG on the main distribution line vs. several small-scale randomly distributed DGs are explored. A residential distribution circuit in Blacksburg, VA was built using its one-line diagram in DEW (Distributed Engineering Workstation) to perform detailed analysis. The research involves several case studies that explore the impacts of installing distributed generation (DG) on residential distribution network operation including the voltage profile, losses, and reliability indices of the system. Master of Science

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Boutros, Fouad. "Nouvelles approches d'optimisation multi-objectifs pour les Microgrids DC Autonomes." Electronic Thesis or Diss., Nantes Université, 2025. http://www.theses.fr/2025NANU4002.

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Dans un monde confronté à l’urgence du changement climatique, les microgrids offrent une solution prometteuse pour concevoir des systèmes énergétiques durables. En particulier, les microgrids en courant continu (DC) isolés, fonctionnant indépendamment des réseaux électriques traditionnels, présentent des défis et des opportunités uniques. Le microgrid étudié dans ce travail est un microgrid DC isolé, composé de panneaux solaires, de batteries, d’un générateur diesel ainsi que de charges électriques résidentielles. Ce travail s’inscrit dans un effort global visant à réduire les émissions de gaz à effet de serre (GES) en optimisant la conception de ces microgrids tout en prenant en compte leur nature multi-objectif, notamment les aspects techniques, économiques et environnementaux. Face à la complexité de la transition énergétique mondiale, notre recherche se concentre sur trois dimensions majeures : l’optimisation des dimensions des composants du microgrid, la localisation stratégique des sources d’énergie et l’optimisation de la topologie des microgrids à réseau maillé. Ces objectifs sont atteints grâce à une approche novatrice combinant des techniques de modélisation avancées et des algorithmes d’optimisation In a world facing the urgency of climate change, microgrids offer a promising solution for designing sustainable energy systems. In particular, isolated direct current (DC) microgrids, which operate independently of traditional power grids, present unique challenges and opportunities. The microgrid studied in this work is an isolated DC microgrid composed of solar panels, batteries, a diesel generator, and residential electrical loads. This work is part of a global effort to reduce greenhouse gas (GHG) emissions by optimizing the design of these microgrids while accounting for their multi-objective nature, including technical, economic, and environmental aspects. Amid the complexity of the global energy transition, our research focuses on three major dimensions: optimizing the sizing of microgrid components, strategically locating energy sources, and optimizing the topology of meshed microgrid networks. These objectives are achieved through an innovative approach combining advanced modelling techniques and optimization algorithms

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Sargent, Garrett Craig. "A Conditional Generative Adversarial Network Demosaicing Strategy for Division of Focal Plane Polarimeters." University of Dayton / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1606050550958383.

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Zhang, Wang. "Optimisation and Integration of Variable Renewable Energy Sources in Electricity Networks." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/16858.

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The growing penetration of renewable energy sources (RESs) into the electricity power grid is profitable from a sustainable point of view and provides economic benefit for long-term operation. Nevertheless, balancing production and consumption is and will always be a crucial requirement for power system operation. However, the trend towards increasing RESs penetration has raised concerns about the stability, reliability and security of future electricity grids. The clearest observation in this regard is the intermittent nature of RESs. Moreover, the location of renewable generation tends to be heavily defined by meteorological and geographical conditions, which makes the generation sites distant from load centres. These facts make the analysis of electricity grid operation under both dynamic and the steady state more difficult, posing challenges in effectively integrating variable RESs into electricity networks. The thesis reports on studies that were conducted to design efficient tools and algorithms for system operators, especially transmission system operators for reliable short-term system operation that accounts for intermittency and security requirements. Initially, the impact of renewable generation on the steady state is studied in the operation stage. Then, based on the first study, more sophisticated modeling on the electricity network are investigated in the third and fourth chapters. Extending the previous studies, the fourth chapter explores the potential of using multiple microgrids to support the main grid’s security control. Finally, the questions regarding the computational efficiency and convergence analysis are addressed in chapter 5 and a DSM model in a real-time pricing environment is introduced. This model presents an alternative way of using flexibility on the demand side to compensate for the uncertainties on the generation side.

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Isapour, Chehardeh Maziar. "AUTOMATIC RECONFIGURATION OF RADIAL DISTRIBUTION NETWORK FOR RELIABILITY ASSESSMENT USING THE CIRCUIT GRAPH." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/dissertations/1572.

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The problem of optimum restoration after occurrence the outages in a distribution network is an important issue in smart grids. In this kind of networks remote-controlled switches, alternative sources and grid-connected distributed generators (DG) are employed. Therefore, the reliability of the system (corresponding to the frequency of failures and the duration of interruptions) is improved by operating the switches to resupply a part of interrupted system during the repair time. To evaluate the reliability indices in smart grids, neglecting the restoration during the repair time causes the wrong assessment of the network. Thus, considering the rerouting the power during the interruptions seems necessary to calculate the reliability indices. The problem of restoration is formulated as a non-linear integer programming problem with the assistance of the network graph. The circuit graph method is also used to pre-evaluate the feasible interchanging operations to enhance the efficiency of the computations. The topological and operational constraints in this formulation can be found and resolved with the assistance of fundamental cut-set matrix. The optimum restoration schemes is obtained by considering the optimal islanded mode of operation of the DGs which implies maximizing the loading of DGs while not violating their generation capacities. The optimum restoration policies lead us to find the optimum number and location of those manual switches that should be upgraded to the remote-controlled switches. This is a multi-objective problem that contains the contribution of each restoration policy in the reliability improvement and the cost of those switching operations. The proposed algorithm is applied to different standard test systems and the results are compared to the results obtained from other methods and algorithms.

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Swinnen, Nina. "Microglia in the embryonic brain and spinal cord during the development of neuronal networks." Paris 6, 2013. http://www.theses.fr/2013PA066321.

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Les cellules microgliales sont les cellules immunitaires résidentes du système nerveux central (SNC). Elles peuvent déjà être détectées au début du développement embryonnaire du SNC. Dans ce projet de recherche nous avons étudié l'invasion et les caractéristiques phénotypiques des cellules microgliales du cerveau embryonnaire. Nos résultats demontrent que les microglies dans le cortex embryonnaire ont un phénotype de « repos »; elles expriment peu de marqueurs d'activation et n'ont presque aucun canaux K+ à rectification entrante. Pourtant, elles sont très dynamiques comme dans le cerveau adulte. Au cours du développement du plexus choroïde, des microglies activées au phenotype phagocytique s'accumulent à un moment coïncidant avec un pic d'apoptose dans cette structure. La proliferation des microglies dans la moelle épinière embryonnaire dépend de récepteurs P2X7. Nous avons retrouvé les mêmes récepteurs sur les cellules microgliales du cortex. Diverses études ont demontré que les infections et l'activation immunitaire pendant la grossesse donnent un risque accru de développement de maladies neuro-psychiatriques chez les enfants. Puisque les microglies sont les cellules immunitaires du SNC et qu’elles sont présentes au cours du développement embryonnaire, nous avons examiné si elles sont activées après une reaction immunitaire maternelle pendant la grossesse. Nos résultats indiquent qu’il n'y a aucune augmentation de densité ou d’activation des cellules microgliales dans le cerveau embryonnaire après induction d’une réaction immunitaire maternelle The microglia are the resident immune cells of the central nervous system (CNS). They can be detected from the beginning of the development of the embryonic CNS. In this project we have studied the invasion and phenotypic characteristics of the microglial cells in the embryonic brain. Our results show that embryonic microglia in the cortex have a “resting” phenotype; the express little activation markers and have little to no inward rectifying K+ channels. However, they are very dynamic like observed in the adult brain. During development of the choroid plexus, activated microglia with a phagocytic phenotype accumulate at the moment apoptotic cells are present in this structure. The proliferation of microglial in the embryonic spinal cord depends on P2X7 receptors. We found the same receptors to be present on the microglia in the cortex. Different studies have shown that infections and immune activation during pregnancy increase the risk on neuropsychiatric disorders in the offspring. Since microglia are the immune cells of the CNS and they are present early in development, we studied the effect of maternal inflammation during pregnancy on these cells. Our results indicate that there is no effect on microglia density and activation after maternal immune activation

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Tegling, Emma. "On performance limitations of large-scale networks with distributed feedback control." Licentiate thesis, KTH, Reglerteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-186180.

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We address the question of performance of large-scale networks with distributed feedback control. We consider networked dynamical systems with single and double integrator dynamics, subject to distributed disturbances. We focus on two types of problems. First, we consider problems modeled over regular lattice structures. Here, we treat consensus and vehicular formation problems and evaluate performance in terms of measures of “global order”, which capture the notion of network coherence. Second, we consider electric power networks, which we treat as dynamical systems modeled over general graphs. Here, we evaluate performance in terms of the resistive power losses that are incurred in maintaining network synchrony. These losses are associated with transient power flows that are a consequence of “local disorder” caused by lack of synchrony. In both cases, we characterize fundamental limitations to performance as networks become large. Previous studies have shown that such limitations hold for coherence in networks with regular lattice structures. These imply that connections in 3 spatial dimensions are necessary to achieve full coherence, when the controller uses static feedback from relative measurements in a local neighborhood. We show that these limitations remain valid also with dynamic feedback, where each controller has an internal memory state. However, if the controller can access certain absolute state information, dynamic feedback can improve performance compared to static feedback, allowing also 1-dimensional formations to be fully coherent. For electric power networks, we show that the transient power losses grow unboundedly with network size. However, in contrast to previous results, performance does not improve with increased network connectivity. We also show that a certain type of distributed dynamic feedback controller can improve performance by reducing losses, but that their scaling with network size remains an important limitation. QC 20160504

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Gifalli, André. "Impacto de microrredes sobre o sistema de proteção de redes de distribuição /." Bauru, 2019. http://hdl.handle.net/11449/191236.

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Orientador: André Nunes de Souza Resumo: A crescente demanda por energia elétrica, combinada com questões ambientais e financeiras, vem promovendo a integração de unidades geradoras distribuídas nas redes de distribuição. Essa configuração topológica, construída próxima aos consumidores, consiste em um conceito chamado de microgrid, desenvolvido nos últimos anos. Esse modelo é caracterizado por um conjunto de pequenas unidades geradoras, cargas e dispositivos de armazenamento de energia, capazes de operar em modo paralelo ou isolado, em relação à rede existente. Vários estudos apontam que as microrredes influenciam o planejamento, operação e manutenção da rede de distribuição elétrica, principalmente porque as microrredes funcionam em um fluxo de energia bidirecional em vez do modo unidirecional convencional. Essa topologia de rede pode influenciar significativamente o perfil de tensão, estabilidade, qualidade de energia e comportamento de proteção do sistema elétrico. Em relação ao esquema de proteção, esses sistemas podem interferir na coordenação e seletividade dos equipamentos que constituem a rede. Nesse sentido, o objetivo desta dissertação é analisar o impacto da contribuição da corrente de curto-circuito das conexões de microrrede no sistema de proteção de sobrecorrente nas redes de distribuição convencionais. A análise é desenvolvida modelando uma rede de distribuição IEEE de 34 barras. O software OpenDss é usado em conjunto com um aplicativo Python desenvolvido para avaliar os impactos na coordenação e sel... (Resumo completo, clicar acesso eletrônico abaixo) Abstract: The growing demand for electricity, combined with environmental and financial issues, fostered the integration of distributed generating units into distribution networks. This topological configuration, build up nearby the consumers, consist of a concept called microgrid, which has been developed in recent years. This model is characterized by a set of small generating units, loads and energy store devices, capable of operating in a parallel or isolated mode, concerning the existing network. Several studies point out that the microgrids influence the planning, operation, and maintenance of the electrical distribution network, mainly because of microgrids woks with a bidirectional power flow rather than the conventional unidirectional mode. This network topology can significantly influence the voltage profile, stability, power quality, and electrical system protection behavior. Regarding the protection scheme, these systems can interfere with the coordination and selectivity of the equipment that constitutes the network. In this sense, the purpose of this dissertation is to analyze the impact of the short circuit current contribution from the micro-network connections in the overcurrent protection system in the conventional distribution networks. The analysis is developed by modeling an IEEE 34-bar distribution network. The OpenDss software is used in conjunction with a developed Python application to assess the impacts on coordination and selectivity of the overcurrent protec... (Complete abstract click electronic access below) Mestre

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Oliveira, Hércules Araújo. "Rede híbrida de distribuição de energia em CC e CA como solução alternativa para microrredes isoladas." Universidade Federal do Maranhão, 2017. http://tedebc.ufma.br:8080/jspui/handle/tede/1408.

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Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-05-16T18:46:41Z No. of bitstreams: 1 HerculesAraujo.pdf: 4155547 bytes, checksum: a184b99018c0f978ec408861bdd090df (MD5) Made available in DSpace on 2017-05-16T18:46:41Z (GMT). No. of bitstreams: 1 HerculesAraujo.pdf: 4155547 bytes, checksum: a184b99018c0f978ec408861bdd090df (MD5) Previous issue date: 2017-03-13 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPQ) This work proposes a topology of isolated microgrids with hybrid network (part in DC and part in AC) of electric power distribution. This topology can serve as an alternative model to the conventional AC distribution network model for the electrical service of isolated communities. The topology consists of using a main system of DC power distribution and subsystems with an AC distribution. DC/AC converters are strategically distributed along the DC main network, forming AC subsystems, in order to serve a certain number of consumers with AC loads. Although there are loads that can be fed in DC, this is not a reality for household loads, which are basically AC powered. Thus, the interest of this work is to evaluate the possible advantages of this topology over the conventional microrredes with distribution network in low voltage in AC. In this contexto, the analysis parameters to be studied are: the increasing the extension of the distribution network without the need to use transformers, electric conductors with larger cross sections or distributed generation; the efficiency in the distribution of energy, evaluating the losses, and the reduction of implantation and operation costs. In order to compare the microgrid with hybrid distribution network, an isolated microgrid with purely CA distribution network was adopted as reference: the microgrid with solar-wind generation of Lençóis Island, located in the northeast of Brazil, which has been in operation since July 2008. Este trabalho propõe uma topologia de microrredes isoladas com rede híbrida (parte em CC e parte em CA) de distribuição de energia elétrica. Essa topologia pode servir como modelo alternativo ao modelo convencional de rede de distribuição de energia totalmente em CA para o atendimento elétrico de comunidades isoladas. A topologia consiste em utilizar um sistema tronco de distribuição de energia em CC e de subsistemas com distribuição CA. Conversores CC/CA são distribuídos estrategicamente ao longo da rede tronco CC, formando subsistemas CA, com a finalidade de atender determinado número de consumidores com carga em CA. Apesar de existirem cargas que podem ser alimentadas em CC, essa não é uma realidade para as cargas de uso doméstico, que basicamente são alimentadas em CA. Assim, o interesse deste trabalho é avaliar as possíveis vantagens dessa topologia sobre as convencionais microrredes com rede de distribuição em baixa tensão em CA. Neste contexto, os parâmetros de análise a serem estudados são o aumento da extensão da rede de distribuição sem a necessidade de se utilizar transformadores, condutores elétricos com seções transversais maiores ou geração distribuída; a eficiência na distribuição de energia, avaliando as perdas, e a redução de custos de implantação e operação. Para se comparar a microrrede com rede de distribuição híbrida, adotouse como referência uma microrrede isolada com rede de distribuição somente CA: a microrrede com geração eólica-solar da Ilha de Lençóis está localizada no nordeste do Brasil, a qual está em operação desde julho de 2008.

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O'Flynn, Alexander W. "Testing of Phasor Measurement Units (PMUs) for Distribution Network Applications." Thesis, Queensland University of Technology, 2020.

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Enabling islanded operation of power distribution networks will greatly improve the reliability of supply for customers. Measurement devices such as Phasor Measurement Units (PMUs) are required to protect and control the islanded network. PMUs are widely used in transmission network. This thesis examines whether existing PMUs meet the performance requirements to enable islanded distribution network operation.

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Feijoo, Felipe. "Analysis of Carbon Policies for Electricity Networks with High Penetration of Green Generation." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5684.

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In recent decades, climate change has become one of the most crucial challenges for humanity. Climate change has a direct correlation with global warming, caused mainly by the green house gas emissions (GHG). The Environmental Protection Agency in the U.S. (EPA) attributes carbon dioxide to account for approximately 82\% of the GHG emissions. Unfortunately, the energy sector is the main producer of carbon dioxide, with China and the U.S. as the highest emitters. Therefore, there is a strong (positive) correlation between energy production, global warming, and climate change. Stringent carbon emissions reduction targets have been established in order to reduce the impacts of GHG. Achieving these emissions reduction goals will require implementation of policies like as cap-and-trade and carbon taxes, together with transformation of the electricity grid into a smarter system with high green energy penetration. However, the consideration of policies solely in view of carbon emissions reduction may adversely impact other market outcomes such as electricity prices and consumption. In this dissertation, a two-layer mathematical-statistical framework is presented, that serves to develop carbon policies to reduce emissions level while minimizing the negative impacts on other market outcomes. The bottom layer of the two layer model comprises a bi-level optimization problem. The top layer comprises a statistical model and a Pareto analysis. Two related but different problems are studied under this methodology. The first problem looks into the design of cap-and-trade policies for deregulated electricity markets that satisfy the interest of different market constituents. Via the second problem, it is demonstrated how the framework can be used to obtain levels of carbon emissions reduction while minimizing the negative impact on electricity demand and maximizing green penetration from microgrids. In the aforementioned studies, forecasts for electricity prices and production cost are considered. This, this dissertation also presents anew forecast model that can be easily integrated in the two-layer framework. It is demonstrated in this dissertation that the proposed framework can be utilized by policy-makers, power companies, consumers, and market regulators in developing emissions policy decisions, bidding strategies, market regulations, and electricity dispatch strategies.

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PONGIGLIONE, PAOLA. "Optimal operation and planning of transmission and distribution networks, towards renewable sources and storage integration." Doctoral thesis, Università degli studi di Genova, 2020. http://hdl.handle.net/11567/1006216.

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In the last two decades, power systems have faced a thundering transformation due to the widespread penetration of Distributed Generation (DG) which revolutionized the traditional paradigms of network operation and planning. Driven by a multitude of factors (including the diffusion of renewable sources in distribution grids, the progress in storage technologies and their price reduction, the environmentally friendly policies that promoted green sources to reduce fossil fuels consumption, the improvements in Information and Communication Technology (ICT) field allowing remote monitoring and control) the traditional passive distribution networks are turning into active grids, therefore requiring far more complex control schemes, but at the same time offering the opportunity to implement strategies that improve the efficiency, reliability and quality of power supply, if remote devices are shrewdly exploited for grid services. This thesis focuses on the modelling approaches for optimal operation and planning of “smart” electrical transmission and distribution networks, able to integrate Distributed Energy Resources (DERs) for ancillary services provision. Among possible DERs and their applications, renewable sources and storage devices are targeted, either in stand-alone operation or as part of aggregations. The reported analysis starts indeed from the difficulty of planning in the modern scenario, dealing with uncertainty management due to stochastic resources and the guarantee of reliability requirements, that can be possibly overcome through storage devices, which however need high initial investments moving from Operating Expense (OpEx) to Capital Expenditure (CapEx) structure. Then, the challenge of network modelling is addressed: since complete power flow equations are computationally heavy, several methodologies for grid behaviour representation are proposed, sorted by increasing accuracy, comparing the pros and cons that each approach implies. As will be evident from these considerations, there is no claim to find a perfect technique for all purposes, but the best trade-off between robustness and approximation depends on the actual assumptions and goals of each problem. The proposed formulations incorporate also the main characteristics of all the network elements involved in power flows, e.g. branch maximum current bounds and both minimum and maximum bus voltage limits, power factor, energy balance, state of charge, etc. depending on the case. Some elements need a particular focus, like the above-mentioned charge and discharge plans of storage devices, which are discussed in details. The last theoretical aspect proposed is the design of Volt/Var Optimization (VVO) procedures, which are strongly related to the chosen power flow formulation, thus particularly hard to implement from a mathematical point of view: Volt/Var control aims to require optimized contributions of reactive power from DERs in order to regulate voltage at all nodes and relieve line congestions together with power losses. Finally, some applications of these techniques are described, showing examples of multi-target optimizations, of optimal sizing and allocation algorithms or real-time operation strategies, of coordinated approaches to control several dispatchable devices. The first chapter of this thesis describes power system evolution, from the original structure to modern challenges to be coped with, analysing emerging problems as well as leading solutions to take advantage of technological progress and presenting common planning techniques. In the end, the objectives and contributions of this thesis are illustrated. In the second chapter, the core point of electrical networks studies is deepened: power flow modelling, i.e. an overview of possible approaches to the strongly non-linear equations which rule the system behaviour. Chapter three focusses on some aspects of active networks management, like the challenges and possible solutions for storage systems inclusion in grid modelling, the approaches to distributed volt/var control formulation, and the integration of multi-target optimization in integrated systems. The fourth chapter describes the applications of proposed techniques on different test cases and with different goals, presenting performed simulations and discussing their results. Finally, in the last chapter, the conclusions of this work are drawn, analysing the strong points emerging from the simulations described but also open points yet to be resolved.

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Dewadasa, Jalthotage Manjula Dinesh. "Protection of distributed generation interfaced networks." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/43681/1/Jalthotage_Dewadasa_Thesis.pdf.

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With the rapid increase in electrical energy demand, power generation in the form of distributed generation is becoming more important. However, the connections of distributed generators (DGs) to a distribution network or a microgrid can create several protection issues. The protection of these networks using protective devices based only on current is a challenging task due to the change in fault current levels and fault current direction. The isolation of a faulted segment from such networks will be difficult if converter interfaced DGs are connected as these DGs limit their output currents during the fault. Furthermore, if DG sources are intermittent, the current sensing protective relays are difficult to set since fault current changes with time depending on the availability of DG sources. The system restoration after a fault occurs is also a challenging protection issue in a converter interfaced DG connected distribution network or a microgrid. Usually, all the DGs will be disconnected immediately after a fault in the network. The safety of personnel and equipment of the distribution network, reclosing with DGs and arc extinction are the major reasons for these DG disconnections. In this thesis, an inverse time admittance (ITA) relay is proposed to protect a distribution network or a microgrid which has several converter interfaced DG connections. The ITA relay is capable of detecting faults and isolating a faulted segment from the network, allowing unfaulted segments to operate either in grid connected or islanded mode operations. The relay does not make the tripping decision based on only the fault current. It also uses the voltage at the relay location. Therefore, the ITA relay can be used effectively in a DG connected network in which fault current level is low or fault current level changes with time. Different case studies are considered to evaluate the performance of the ITA relays in comparison to some of the existing protection schemes. The relay performance is evaluated in different types of distribution networks: radial, the IEEE 34 node test feeder and a mesh network. The results are validated through PSCAD simulations and MATLAB calculations. Several experimental tests are carried out to validate the numerical results in a laboratory test feeder by implementing the ITA relay in LabVIEW. Furthermore, a novel control strategy based on fold back current control is proposed for a converter interfaced DG to overcome the problems associated with the system restoration. The control strategy enables the self extinction of arc if the fault is a temporary arc fault. This also helps in self system restoration if DG capacity is sufficient to supply the load. The coordination with reclosers without disconnecting the DGs from the network is discussed. This results in increased reliability in the network by reduction of customer outages.

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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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Xu, Yang. "A Systems Approach to Dissecting Immune Gene Regulatory Networks in the Modulation of Brain Function." eScholarship@UMMS, 2010. http://escholarship.umassmed.edu/gsbs_diss/924.

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Although the central nervous system was long perceived as the ivory tower without immune entities, there is growing evidence that the immune and nervous systems are intimated connected. These two systems have been shown to communicate both cellularly and molecularly under physiological and pathological conditions. Despite our increasing understanding of the interplay between these two systems, there are still numerous open questions. In this thesis, I address such unanswered questions related to: the role of microglia and their mechanism in contributing to pathologies in Rett syndrome; the beneficial effects of T-cell secreted cytokines in supporting social brain function; the evolutionary link of the interactions between the nervous and immune systems; the transcription regulation of a subset of microglia population in common neurodegenerative diseases. Collectively, the current thesis is focused on the joint frontier of bioinformatics and experimental work in neuroimmunology. A multifaceted approach, that includes transcriptomics, genomics and other biomolecular modules, was implemented to unearth signaling pathways and mechanisms underlying the presenting biological phenomena. The findings of this thesis can be summarized as follows: 1) MeCP2 acts as a master regulator in the transcriptional repression of inflammatory stimuli in macrophages; 2) T-cell secreted IFN-γ supports social brain function through an evolutionally conserved interaction between the immune and nervous systems; 3) The APOE-TREM2 pathway regulates the microglia phenotype switch in neurodegenerative diseases. Provided that recent technologies allow for readily manipulating the immune system, the findings presented herein may create new vistas for therapeutic interventions in various neurological disorders.

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Xu, Yang. "A Systems Approach to Dissecting Immune Gene Regulatory Networks in the Modulation of Brain Function." eScholarship@UMMS, 2017. https://escholarship.umassmed.edu/gsbs_diss/924.

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Although the central nervous system was long perceived as the ivory tower without immune entities, there is growing evidence that the immune and nervous systems are intimated connected. These two systems have been shown to communicate both cellularly and molecularly under physiological and pathological conditions. Despite our increasing understanding of the interplay between these two systems, there are still numerous open questions. In this thesis, I address such unanswered questions related to: the role of microglia and their mechanism in contributing to pathologies in Rett syndrome; the beneficial effects of T-cell secreted cytokines in supporting social brain function; the evolutionary link of the interactions between the nervous and immune systems; the transcription regulation of a subset of microglia population in common neurodegenerative diseases. Collectively, the current thesis is focused on the joint frontier of bioinformatics and experimental work in neuroimmunology. A multifaceted approach, that includes transcriptomics, genomics and other biomolecular modules, was implemented to unearth signaling pathways and mechanisms underlying the presenting biological phenomena. The findings of this thesis can be summarized as follows: 1) MeCP2 acts as a master regulator in the transcriptional repression of inflammatory stimuli in macrophages; 2) T-cell secreted IFN-γ supports social brain function through an evolutionally conserved interaction between the immune and nervous systems; 3) The APOE-TREM2 pathway regulates the microglia phenotype switch in neurodegenerative diseases. Provided that recent technologies allow for readily manipulating the immune system, the findings presented herein may create new vistas for therapeutic interventions in various neurological disorders.

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Biswas, Shuchismita. "Power Grid Partitioning and Monitoring Methods for Improving Resilience." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/104684.

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This dissertation aims to develop decision-making tools that aid power grid operators in mitigating extreme events. Two distinct areas are focused on: a) improving grid performance after a severe disturbance, and b) enhancing grid monitoring to facilitate timely preventive actions. The first part of the dissertation presents a proactive islanding strategy to split the bulk power transmission system into smaller self-adequate islands in order to arrest the propagation of cascading failures after an event. Heuristic methods are proposed to determine in what sequence should the island boundary lines be disconnected such that there are no operation constraint violations. The idea of optimal partitioning is further extended to the distribution network. A planning problem for determining which parts of the existing distribution grid can be converted to microgrids is formulated. This partitioning formulation addresses safety limits, uncertainties in load and generation, availability of grid-forming units, and topology constraints such as maintaining network radiality. Microgrids help maintain energy supply to critical loads during grid outages, thereby improving resilience. The second part of the dissertation focuses on wide-area monitoring using Phasor Measurement Unit (PMU) data. Strategies for data imputation and prediction exploiting the spatio-temporal correlation in PMU measurements are outlined. A deep-learning-based methodology for identifying the location of temporary power systems faults is also illustrated. As severe weather events become more frequent, and the threats from coordinated cyber intrusions increase, formulating strategies to reduce the impact of such events on the power grid becomes important; and the approaches outlined in this work can find application in this context. Doctor of Philosophy The modern power grid faces multiple threats, including extreme-weather events, solar storms, and potential cyber-physical attacks. Towards the larger goal of enhancing power systems resilience, this dissertation develops strategies to mitigate the impact of such extreme events. The proposed schemes broadly aim to- a) improve grid performance in the immediate aftermath of a disruptive event, and b) enhance grid monitoring to identify precursors of impending failures. To improve grid performance after a disruption, we propose a proactive islanding strategy for the bulk power grid, aimed at arresting the propagation of cascading failures. For the distribution network, a mixed-integer linear program is formulated for identifying optimal sub-networks with load and distributed generators that may be retrofitted to operate as self-adequate microgrids, if supply from the bulk power systems is lost. To address the question of enhanced monitoring, we develop model-agnostic, computationally efficient recovery algorithms for archived and streamed data from Phasor Measurement Units (PMU) with data drops and additive noise. PMUs are highly precise sensors that provide high-resolution insight into grid dynamics. We also illustrate an application where PMU data is used to identify the location of temporary line faults.

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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 système The 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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Mosser, Coralie-Anne. "Implication des cellules microgliales dans le développement des réseaux synaptiques du néocortex somatosensoriel Microglial BDNF promotes the functional maturation of thalamocortical synaptic networks Microglia and prenatal inflammation regulate local and horizontal wiring of inhibitory circuits." Thesis, Sorbonne Paris Cité, 2018. https://wo.app.u-paris.fr/cgi-bin/WebObjects/TheseWeb.woa/wa/show?t=2167&f=13404.

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La microglie désigne l'ensemble des macrophages résidents du système nerveux central (SNC). Longtemps considérées comme étant actives uniquement en conditions pathologiques, les cellules microgliales sont pourtant essentielles à l'activité physiologique du SNC. En particulier, pendant la formation du SNC, elles régulent apoptose et survie neuronales, et interagissent directement avec les synapses en les éliminant, en promouvant leur formation ou en régulant leur activité. Toutefois, les mécanismes microgliaux impliqués dans la mise en place et la maturation fonctionnelle des circuits corticaux pendant le développement ne sont pas intégralement élucidés. Afin de mieux comprendre le rôle de la microglie dans le développement cortical, nous avons utilisé le système des champs de tonneaux du cortex somatosensoriel de la souris, et combiné des manipulations in vivo avec des approches électrophysiologiques, optogénétique, pharmacologique et histologique sur tranches de cerveaux de souris génétiquement modifiées. Dans une première étude, nous nous sommes intéressés aux conséquences de l'arrivée de la microglie à proximité des zones de terminaison des fibres thalamiques (les centres des tonneaux) dans le cortex somatosensoriel au cours de la première semaine postnatale sur les propriétés fonctionnelles des synapses thalamocorticales et de l'inhibition disynaptique associée (inhibition antérograde ou feedforward). Nos résultats montrent qu'une déplétion de la microglie pendant la première semaine postnatale entraîne un retard de maturation fonctionnelle de la connexion thalamocorticale excitatrice monosynaptique et de l'inhibition feedforward disynaptique au niveau des cellules principales excitatrices de la couche 4 (CP) entre les 10ème et 12ème jours postnataux (P10-12). Nous avons ensuite testé si le facteur neurotrophique BDNF (brain-derived neurotrophic factor) pouvait être la molécule microgliale impliquée dans la maturation de ces synapses corticales en utilisant une approche transgénique (lignée CX3CR1+/CreERT2;BDNFlox/lox). Nos enregistrements indiquent que l'absence de BDNF microglial entraîne aussi un déficit de maturation fonctionnelle des connexions excitatrices monosynaptiques et inhibitrices disynaptiques thalamocorticales entre P10-12. Nous avons donc identifié un facteur microglial clé dans la maturation des synapses corticales, et nos enregistrements chez le jeune adulte suggèrent que la suppression de BDNF microglial pendant la première semaine postnatale altère la synapse thalamocorticale excitatrice sur le long terme. Dans une deuxième étude, nous avons examiné les conséquences de perturbations de la microglie au cours du développement embryonnaire sur la mise en place des réseaux corticaux. L'induction d'une activation immunitaire maternelle (MIA) par injection de lipopolysaccharide (LPS) bactérien ou la déplétion de la microglie aux stades embryonnaires modifie la répartition laminaire des interneurones inhibiteurs exprimant la parvalbumine (PV+) _cellules responsables de l'inhibition feedforward_ dans le cortex jusqu'à P20. Nos données fonctionnelles ont révélé que ces protocoles de MIA et de déplétion induisent une augmentation de l'inhibition périsomatique des CP à P20, ainsi qu'une exubérance horizontale de l'inhibition soutenue par les interneurones PV+. Cette inhibition exacerbée ne perdure pas et nos enregistrements chez l'adulte indiquent au contraire un affaiblissement des synapses inhibitrices entre les interneurones PV+ et les CP. Nous postulons donc que les cellules microgliales sont le chaînon manquant entre des stimulations immunitaires, telles qu'elles peuvent se produire durant une inflammation pendant la grossesse, et l'augmentation du risque de développer des pathologies neurodéveloppementales. Ainsi, nos résultats mettent en exergue le rôle crucial de la microglie dans le développement des réseaux neuronaux corticaux pendant la période périnatale Microglial cells are a population of specialized macrophages residing in the CNS only. They have long been studied solely under pathological contexts and were thought to be active only upon homeostatic disturbance following a brain lesion. However, over the last decade, they have been increasingly recognized to be essential players in the physiological functioning of the CNS. Specifically, during the CNS formation, microglia has been shown to regulate apoptosis and neuronal survival. They are also able to directly interact with synapses, by eliminating supernumerary and inappropriate connections, by promoting synapse formation or by regulating their activity. However, mechanisms by which microglia influence wiring and functional maturation of cortical are not fully understood. To better assess the role of microglia in cortical development, we used the barrel field as a model of neuronal development and we combined in vivo manipulations together with electrophysiology, optogenetics, pharmacologic and histologic approaches on brain slices of genetically-engineered mice. We first explored the consequences of microglia entry near the terminals of thalamic afferents (center of the barrels) in the primary somatosensory cortex during the first postnatal week on functional properties of thalamocortical synapses and associated disynaptic feedforward inhibition. By selectively depleting microglia at early postnatal days by intracerebral injections of clodronate-encapsulated liposomes, we show that microglia absence during the first postnatal week delays the functional maturation of both monosynaptic thalamocortical synapse and feedforward inhibition of layer 4 principal cells of the barrel cortex (PC) up to the 10th and 12th postnatal days (P10-12). To identify the mechanism underlying this process, we used the CX3CR1+/CreERT2; BDNFlox/lox mouse line allowing the conditional deletion of microglial BDNF during the first postnatal week. Our recordings indicate that the absence of microglial BDNF, as well as early microglia depletion, leads to a deficit in the functional maturation of both monosynaptic excitatory and disynaptic inhibitory thalamocortical connexions between P10-12. We therefore identified a microglial key factor in the maturation of cortical synapses. Our recordings in the young adult suggest that early microglial BDNF deletion has a long-term effect on thalamocortical excitatory synapses. In a second study, we investigated the consequences of microglia dysfunction during embryonic development on cortical networks wiring. Maternal immune activation (MIA) triggered by bacterial lipopolysaccharide (LPS) injection modifies the laminar repartition of parvalbumin-expressing inhibitory interneurons (PV+), key actors in neuropsychiatric disease, in the cortex until P20. Our functional data revealed that these MIA and depletion protocols lead to an increase of layer 4 PC perisomatic inhibition at P20, as well as a horizontal exuberance of cortical inhibition supported by PV+ interneurons. This increased inhibition does not last within development as suggested by our recordings in the adult. On the opposite, it seems that MIA and early microglia depletion result in weaker inhibitory synapses at P60. To conclude, we postulate that microglial cells are the missing link between maternal immune challenge and à higher risk of having neurodevelopmental pathologies like autism or schizophrenia. Our results highlight the crucial role of microglial cells in neuronal network development during perinatal period

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Loureiro, Pedro da Cruz. "Controle de tensão e harmônicos por compensador estático de reativos com ajuste de parâmetros via redes neurais artificiais." Universidade Federal de Juiz de Fora, 2012. https://repositorio.ufjf.br/jspui/handle/ufjf/1785.

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Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-06-09T12:11:11Z No. of bitstreams: 1 pedrodacruzloureiro.pdf: 1767688 bytes, checksum: 1fa1e4fbfaa6feaf5a5c88ea70df09d6 (MD5) Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-07-13T13:31:22Z (GMT) No. of bitstreams: 1 pedrodacruzloureiro.pdf: 1767688 bytes, checksum: 1fa1e4fbfaa6feaf5a5c88ea70df09d6 (MD5) Made available in DSpace on 2016-07-13T13:31:22Z (GMT). No. of bitstreams: 1 pedrodacruzloureiro.pdf: 1767688 bytes, checksum: 1fa1e4fbfaa6feaf5a5c88ea70df09d6 (MD5) Previous issue date: 2012-04-16 CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Neste trabalho é proposta a aplicação de redes neurais artificiais para ajuste de parâmetros de um compensador estático de reativos, para controle de tensão e harmônicos. Devido à intensa produção de correntes harmônicas e possíveis afundamentos de tensão em instalações industriais como o forno a arco, é necessário um sistema de controle eficiente e robusto. Além disso, os sistemas elétricos de potência se encontram em um cenário com a presença cada vez maior de geração distribuída, cargas não-lineares e forte tendência à operação no contexto das smartgrids e microgrids. Sendo assim, o suporte de reativos deve ser adequado a esses sistemas, podendo atuar de forma rápida, precisa e confiável. Uma possível solução é a utilização de um compensador estático de reativos (CER) com função adicional de filtragem no ponto onde se deseja controlar a tensão e a distorção harmônica. Entretanto, para o correto funcionamento, é necessário um sistema preciso para o ajuste dos parâmetros do CER, ou seja, determinar os ângulos de disparo dos tiristores e o número de bancos de capacitores a serem ligados. Neste trabalho é proposta uma estratégia de controle via redes neurais artificiais, treinadas para o reconhecimento de padrões de operação em regime permanente e definição da configuração do CER, conferindo inteligência ao equipamento. Os desenvolvimentos propostos foram implementados no ambiente MatLab®. A validação do método é feita através de simulações em sistemas-teste, presentes na literatura técnica, utilizando o fluxo de potência pelo método de injeção de correntes trifásico harmônico. Os resultados obtidos mostram as vantagens da utilização da estratégia proposta. In this work, an artificial neural network-based static var compensator tuning is proposed for voltage and harmonic distortion control. Due to intense harmonic current injection and possible voltage sags produced by industrial facilities such as arc furnaces, an efficient robust control system is needed. Besides, electrical power systems face a new scenario with high penetration of distributed generation and non-linear loads and increased smart grid and microgrid trends. Therefore, the available reactive power sources must be able to provide system control in order to operate the system in a fast, accurate and reliable way. The application of a static var compensator (SVC) with additional filtering function at the controlled node is a possible solution. However, a precise SVC parameters tuning is needed, in order to make the system to work properly. In this work, a control strategy based on artificial neural networks is proposed. The neural networks are trained to recognize steadystate operating patterns and give the SVC adjustment. The proposed technique was implemented in the MatLab® environment. The methodology is validated by simulations in test-systems available in technical literature, using the three-phase harmonic current injection method power flow. Results show the advantages of the proposed methodology.

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"Self-organizing Coordination of Multi-Agent Microgrid Networks." Doctoral diss., 2019. http://hdl.handle.net/2286/R.I.55582.

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abstract: This work introduces self-organizing techniques to reduce the complexity and burden of coordinating distributed energy resources (DERs) and microgrids that are rapidly increasing in scale globally. Technical and financial evaluations completed for power customers and for utilities identify how disruptions are occurring in conventional energy business models. Analyses completed for Chicago, Seattle, and Phoenix demonstrate site-specific and generalizable findings. Results indicate that net metering had a significant effect on the optimal amount of solar photovoltaics (PV) for households to install and how utilities could recover lost revenue through increasing energy rates or monthly fees. System-wide ramp rate requirements also increased as solar PV penetration increased. These issues are resolved using a generalizable, scalable transactive energy framework for microgrids to enable coordination and automation of DERs and microgrids to ensure cost effective use of energy for all stakeholders. This technique is demonstrated on a 3-node and 9-node network of microgrid nodes with various amounts of load, solar, and storage. Results found that enabling trading could achieve cost savings for all individual nodes and for the network up to 5.4%. Trading behaviors are expressed using an exponential valuation curve that quantifies the reputation of trading partners using historical interactions between nodes for compatibility, familiarity, and acceptance of trades. The same 9-node network configuration is used with varying levels of connectivity, resulting in up to 71% cost savings for individual nodes and up to 13% cost savings for the network as a whole. The effect of a trading fee is also explored to understand how electricity utilities may gain revenue from electricity traded directly between customers. If a utility imposed a trading fee to recoup lost revenue then trading is financially infeasible for agents, but could be feasible if only trying to recoup cost of distribution charges. These scientific findings conclude with a brief discussion of physical deployment opportunities. Dissertation/Thesis Doctoral Dissertation Systems Engineering 2019

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Ingale, Ganesh Baliram. "Design of PV Based Stand-Alone System for DC Microgrid." Thesis, 2016. http://ethesis.nitrkl.ac.in/9179/1/2016_MT_GBIngale.pdf.

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Renewable energy sources have a significant impact on reducing the burden of the human being on the dependence on fossil fuel for its energy consumption. There are different renewable energy sources which are exploited in recent years. One of the widely used renewable energy source is solar energy. With the help of photovoltaic panel, electricity is generated which is dependent on solar irradiance and ambient temperature. Maximum Power Point Tracking (MPPT) is used to take maximum power from the Photovoltaic (PV) panel in varying environmental conditions. This thesis provides an detailed design and implementation aspect of a DC-micro grid using PV module. perturb & observe maximum power point tracking algorithm is used to track the maximum power point, for the requirement of MPPT a data acquisition (DAQ) unit is made up to sense the PV panel output voltage and current. A output of PV panel is given to boost converter to provide a regulated voltage to the load. The mathematical model of PV panel, MPPT and required power electronic converters are simulated and the simulation results are experimentally validated.

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Wang, Chun-Yi, and 王鈞毅. "Using Neural Network to Adapt Setting Group of IED in Microgrid." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/ypn3mw.

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碩士 國立臺灣科技大學 電機工程系 105 Microgrid may comprise by distributed generators, energy storage devices, power converter, versatile loads, supervisory equipment and protection equipment. The distributed generations installed in microgrid, which may diverse the path or direction of load current or fault current. Therefore, the overcurrent protection scheme for traditional radial type distribution system no longer be useful for microgrid. A microgrid protection management system (PMS) which integrated Intelligent Electronic Device (IED), IEC 61850 communication protocol and supervisory control and data acquisition (SCADA) is proposed in this thesis. First of all, PMS utilizes IED to measure electrical information of microgrid such as voltage, current, and breaker status. Those system informations were sent back to PMS through IEC 61850. In order to coordinate the operating sequence of IED, tripping and blocked signals are transmitted among IED by logic programming and GOOSE message of IEC 61850. PMS calculates the pick-up setting of directional overcurrent element of IED through topology analysis and using Neural Network analysis to accommodate an appropriate setting group of IED. Therefore, the PMS has the self-adaptive capability to deal with the architecture and dynamic changes of microgrid. This thesis uses ETAP PowerStation software and Matlab/Simulink to perform analysis work. The simulation results show that PMS can determine an appropriate pick-up setting and select the corresponding setting group of IED under various scenarios. As a result, PMS can achieve the goal of microgrid protection.

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Hsieh, Ting-Yen, and 謝廷彥. "Loop Frame of Reference Based Network Analysis Techniques for Microgrid Planning and Design." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/20984528440570078597.

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博士 國立臺灣科技大學 電機工程系 101 The main purpose of this dissertation is to develop a set of loop frame of reference based network analysis techniques for microgrid planning and design. First, a graph theory based method for formation of network matrices for radial distribution networks has been introduced. Second, a more accurate and efficient distribution power flow approach is provided in the dissertation to analyze the effects of neutral wire and grounding system on the system performance of a microgrid. Some operation information such as the voltages and currents of phase and neutral wires, system imbalance, and grounding currents can therefore be obtained to improve the power quality, whole system efficiency and operation safety of a microgrid. Third, a novel fault analysis method based on graph theory and complex short-circuit MVA representation has been proposed as an alternative method for a radial power system with dispersed generators (DGs). Two major DG models represented in terms of the complex short-circuit MVA form have been provided to evaluate the effects of DGs in a microgrid on the fault currents. Fourth, a direct harmonic power flow algorithm based on graph theory has been proposed as an alternative method of calculating harmonic power flow for a radial distribution system. A newly defined incidence matrix, the branch-shunt incidence matrix Kshunt has been applied to calculate the vector of shunt elements at each order of harmonics. Simulation results show that the proposed method has advantages which include better performance and high efficiency, especially for a large-scale system with large number of harmonic sources. Finally, an optimized application for evaluation of advantages of an energy storage system using recycled electric vehicle (EV) batteries is given. To evaluate the better allocation of an energy storage system using recycled EV batteries (ESS-rEVb), the full effects of battery charge/discharge time, the typical daily load curve, and hourly renewable energy generation curve are involved in this dissertation. A genetic algorithm is used to solve a multiple objective optimization problem considering electric rates, line loss, and voltage deviation. The developed distribution network analysis techniques and optimized application are of value in planning and design of a microgrid and to improve the operation of a microgrid system safety, with profit.

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Madureira, André Guimarães. "Coordinated and optimized voltage management of distribution networks with multi-microgrids." Doctoral thesis, 2010. http://hdl.handle.net/10216/58358.

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Madureira, André Guimarães. "Coordinated and optimized voltage management of distribution networks with multi-microgrids." Tese, 2010. http://hdl.handle.net/10216/58358.

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Bhattacharya, Somesh. "Controllers for distributed energy resources in active distribution networks." Thesis, 2018. http://localhost:8080/xmlui/handle/12345678/7756.

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Ustun, Taha Selim. "Design and development of a communication-assisted microgrid protection system." Thesis, 2013. https://vuir.vu.edu.au/22016/.

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Climate change concerns due to the rising amounts of the carbon gas in the atmosphere have in the last decade or so initiated a fast pace of technological advances in the renewable energy industry. Such developments in technology and the move towards cleaner sources of energy have made renewable resources based Distributed Generators (DGs) more desirable.

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Liu, Ting-Yu, and 劉庭佑. "Study on Economic Dispatch of a Microgrid by Radial Basis Function Neural Network and Bat Algorithm." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/hfhp77.

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碩士 國立臺灣科技大學 電機工程系 107 The purpose of this thesis is to simulate and analyze economic dispatch for a microgrid with distributed storage systems. Based on historical load data and renewable energy data of microgrid, the neural layer and weight values between voltage, phase angle, and active and reactive power of loads are trained by a radial basis function neural network. The radial basis function neural network can speed up the calculation of power flow analysis and it will be verification by the IEEE 30-bus standard test system. The developed power flow method can calculate the system line loss per hour for economic dispatch application by inputting load demands at different buses for the next 24 hours. First, bat algorithm is verified and simulated by the IEEE 10 units test system for economic dispatch problems. Secondly, the benefit of the distributed storage system is taken into consideration under a day ahead of unit commitment. Third, the multiple-objective bat algorithm is used to optimize economic dispatch and load factor by the distributed energy storage systems. Finally, the effects of different renewable energy penetration on power systems are analyzed. The research outcomes of this thesis are value to a microgrid for making more moderately scheduling under the high renewable energy penetration.

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Soman, Akhil. "Short Term Energy Forecasting for a Microgird Load using LSTM RNN." 2020. https://scholarworks.umass.edu/masters_theses_2/994.

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Decentralization of the electric grid can increase resiliency (during natural disasters) and can reduce T&D energy losses and emissions. Microgrids and DERs can enable this to happen. It is important to optimally control microgrids and DERs to extract the greatest economic, environmental and resiliency benefits. This is enabled by robust forecasting to optimally control loads and energy sources. An integral part of microgrid control is power side and load side demand forecasting. In this thesis, we look at the ability of a powerful neural network algorithm to forecast the load side demand for a microgrid using the UMass campus as the test bed. UMass has its own power plant producing 16 MW of power. In addition to this, Solar panels totaling 5.5MW and lithium ion battery bank of 1.32 MW/4 MWh are also available. An LSTM recurrent neural network is used for demand forecasting. In addition to a fully trained LSTM network, multi linear regression model, ARIMA and ANN model are also tested to compare the performance. In addition to the Short Term Load Forecasting, the peak prediction accuracy of the model was also tested to run a battery discharge algorithm to shave peak demand for the microgrid. This will result in demand cost savings for the facility. Finally, the fully trained neural network was deployed on a raspberry pi computer.

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Al, Omar Wesam F. "Decentralize operational scheme for large-scale smart microgrids integrated into utility network in island mode." Thesis, 2017. http://hdl.handle.net/1959.7/uws:47372.

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Distribution network blackouts are considered very limited. However, any major crisis in the network has high impact on consumers and distribution network operators (DNO). Overload, lack of maintenance and weather are mainly effected by network reliability and leads to cascading failures. Notably, the continuous growth in load demands and deteriorating cables increase the chances to fail the electrical system. To ensure power system availability and reliability, electrical power system should be resilient. Although, contingencies plans can manage restoration schemes to important and vital loads by finding the fault, isolate it and restore the supply neatly, but still other normal loads unable to get supply. The purposes of this thesis to keep the power supply running by enhancing microgrids (MGs) interactions between photovoltaic (PV) plants and battery energy storage systems (BESS) which is integrated to the electrical distribution network. When the main source of supply is lost, the upstream circuit breaker (CB) open and the supply restored by the MGs which located and integrated into the distribution network. Then, interactions schemes between PVs and BESSs are functioning to provide uninterrupted supply by MGs resources. The algorithm of the scheme is considering BESS and energy management to reduce the interruption impact at night for other customers. Sizes, locations, and total numbers of MGs are planned to handle peak demand and to cover unforeseen cases, such as restoring the supply of another electrical circuit network by using interconnection. When the MGs work in island mode as a standalone system, the electrical distribution system completely depends on generated power by PVs and stored power by BESS. Accordingly, the MG resources should be capable of handling the load demand any time during the interruption until the DNO clearing the fault and restore the main power supply. Electric power distribution reliability indices are employed to define the optimum locations for MGs. Accordingly, the sizes and the total number of MGs are selected based on location, voltage violation, and power losses. To ensure the electrical distribution system reliability and availability, an interaction algorithm formula is needed to manage load sharing between PVs and BESS during the interruption at daylight and night. On the otherhand, some constraints are there for charging and discharging BESS to keep the state of charge (SOC) between 20% to 90%. This research provides, an algorithm to organise all MG interactions including charging and discharging limits. The research methodology investigates and simulates the data by using DIgSILENT PowerFactory SP3 against different situations. The proposal is compared with existing restoring scheme by PVs only. Furthermore, the modification is tested again and verifies the reliability indices to compare it with the existing scheme. The resulting algorithm is implemented in different case studies for validation and testing purposes.

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Cabatac, Mark Tristan Angelo Morena, and 崔思安. "Fault Detection and Location by Static Switch in Microgrids Using Wavelet Transform and Taguchi-based Artificial Neural Network." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/3wz4w9.

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碩士 中原大學 電機工程研究所 106 This study presents a fault detection, classification and localization using the multiresolution analysis (MRA) of the discrete wavelet transform (DWT) and a Taguchi-based artificial neural network (ANN). The difference of wavelet energies of the three-phase fault voltages, three-phase fault currents and the wavelet energy of the ground fault current are utilized as inputs to the neural network. The wavelet energies are obtained from the local fault signals at the static switch located at the secondary side of the main transformer in the microgrid. The neural network identifies the faulty phase and the location of the fault. The neural network determines the control action (open or close) of the static switch when both the fault location and phase are identified. The proposed method is implemented in Renesas RX62T microcontroller. The microcontroller is then implemented in a Chip-in-the-loop with a real-time digital simulator. The DWT is also implemented using a 50-kVA static switch hardware.

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Dissertations / Theses on the topic 'Networked microgrid'

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