Creative ways of utilising renewable energy sources in electricity generation especially in remote areas and particularly in countries depending on imported energy, while increasing energy security and reducing cost of such isolated off-grid systems, is becoming an urgently needed necessity for the effective strategic planning of Energy Systems. The aim of this research project was to design and implement a new decision support framework for the optimal design of hybrid micro grids considering different types of different technologies, where the design objective is to minimize the total cost of the hybrid micro grid while at the same time satisfying the required electric demand. Results of a comprehensive literature review, of existing analytical, decision support tools and literature on HPS, has identified the gaps and the necessary conceptual parts of an analytical decision support framework. As a result this research proposes and reports an Iterative Analytical Design Framework (IADF) and its implementation for the optimal design of an Off-grid renewable energy based hybrid smart micro-grid (OGREH-SμG) with intra and inter-grid (μG2μG & μG2G) synchronization capabilities and a novel storage technique. The modelling design and simulations were based on simulations conducted using HOMER Energy and MatLab/SIMULINK, Energy Planning and Design software platforms. The design, experimental proof of concept, verification and simulation of a new storage concept incorporating Hydrogen Peroxide (H2O2) fuel cell is also reported. The implementation of the smart components consisting Raspberry Pi that is devised and programmed for the semi-smart energy management framework (a novel control strategy, including synchronization capabilities) of the OGREH-SμG are also detailed and reported. The hybrid μG was designed and implemented as a case study for the Bayir/Jordan area. This research has provided an alternative decision support tool to solve Renewable Energy Integration for the optimal number, type and size of components to configure the hybrid μG. In addition this research has formulated and reported a linear cost function to mathematically verify computer based simulations and fine tune the solutions in the iterative framework and concluded that such solutions converge to a correct optimal approximation when considering the properties of the problem. As a result of this investigation it has been demonstrated that, the implemented and reported OGREH-SμG design incorporates wind and sun powered generation complemented with batteries, two fuel cell units and a diesel generator is a unique approach to Utilizing indigenous renewable energy with a capability of being able to synchronize with other μ-grids is the most effective and optimal way of electrifying developing countries with fewer resources in a sustainable way, with minimum impact on the environment while also achieving reductions in GHG. The dissertation concludes with suggested extensions to this work in the future.

M.Com. (Informatics) / Critical Infrastructure is the term used to describe assets that are of utmost importance, or in other words, essential in the functioning of an environment. Societies depend on their critical infrastructure in order to maintain and continuously improve on their population’s standard of living. The creation of more self-sustainable methods of energy consumption and generation drives towards the creation of a better and more efficient evolution of the power grid critical infrastructure, named the smart grid. The introduction of the smart grid brought in a paradigm shift towards the practices used to manage the generation and distribution of electric power. The introduction of highly capable information systems to intrinsically work with current power grid technologies provided the ability to enhance economic and environmental efficiency of power systems. Although providing a wide variety of benefits, such information systems also created new points of vulnerabilities, which if exploited, place the smart grid at risk of disruptions. In order to address the security issues that occur at the application and data exchange level of smart grid information systems, the dissertation proposed the use of a security model to protect the smart grid. The Multi-Agent Smart Grid Security (MA-SGS) model is based on the use of multiple autonomous intelligent software agents which attempt to create operational stability and efficiency in the smart grid...

Cette thèse s’intéresse à la gestion décentralisée des données récoltées par les réseaux de capteurs dans le contexte des réseaux électriques intelligents (smart grids). Nous proposons une architecture décentralisée basée sur les systèmes multi-agents pour la gestion des données et de l’énergie dans un smart grid. En particulier, nos travaux traitent de la gestion des données des réseaux de capteurs dans le réseau de distribution d’un smart grid et ont pour objectif de lever deux verrous essentiels : (1) l'identification et la détection de défaillances et de changements nécessitant une prise de décision et la mise en œuvre des actions correspondantes ; (2) la gestion des grandes quantités de données qui seront récoltées suite à la prolifération des capteurs et des compteurs communicants. La gestion de ces informations peut faire appel à plusieurs méthodes, dont l'agrégation des paquets de données sur laquelle nous nous focalisons dans cette thèse. Nous proposons d’agréger (PriBaCC) et/ou de corréler (CoDA) le contenu de ces paquets de données de manière décentralisée. Ainsi, le traitement de ces données s'effectuera plus rapidement, ce qui aboutira à une prise de décision rapide et efficace concernant la gestion de l'énergie. La validation par simulation de nos contributions a montré que celles-ci répondent aux enjeux identifiés, notamment en réduisant le volume des données à gérer et le délai de communication des données prioritaires / This thesis focuses on the decentralized management of data collected by wireless sensor networks which are deployed in a smart grid, i.e. the evolved new generation electricity network. It proposes a decentralized architecture based on multi-agent systems for both data and energy management in the smart grid. In particular, our works deal with data management of sensor networks which are deployed in the distribution electric subsystem of a smart grid. They aim at answering two key challenges: (1) detection and identification of failure and disturbances requiring swift reporting and appropriate reactions; (2) efficient management of the growing volume of data caused by the proliferation of sensors and other sensing entities such as smart meters. The management of this data can call upon several methods, including the aggregation of data packets on which we focus in this thesis. To this end, we propose to aggregate (PriBaCC) and/or to correlate (CoDA) the contents of these data packets in a decentralized manner. Data processing will thus be done faster, consequently leading to rapid and efficient decision-making concerning energy management. The validation of our contributions by means of simulation has shown that they meet the identified challenges. It has also put forward their enhancements with respect to other existing approaches, particularly in terms of reducing data volume as well as transmission delay of high priority data

Today, there is a growing number of buildings in a neighborhood and business parks that are utilizing renewable energy generation, to reduce their electric bill and carbon footprint. The most current way of implementing a renewable energy generation is to use solar panels or a windmill to generate power; then use a charge controller connected to a battery bank to store power. Once stored, the user can then access a clean source of power from these batteries instead of the main power grid. This type of power structure is utilizing a single module system in respect of one building. As the industry of renewable power generation continues to increase, we start to see a new way of implementing the infrastructure of the power system. Instead of having just individual buildings generating power, storing power, using power, and selling power there is a fifth step that can be added, sharing power. The idea of multiple buildings connected to each other to share power has been named a microgrid by the power community. With this ability to share power in a microgrid system, a catastrophic event which cause shutdowns of power production can be better managed. This paper then discusses the data from simulations and a built physical model of a resilient microgrid utilizing these principles.

Cette thèse s’intéresse à la gestion décentralisée à l’aide des systèmes multi-agents de l’énergie, notamment de sources renouvelables, dans le contexte des réseaux électriques intelligents (smart grids). Nos travaux de recherche visent à minimiser la facture énergétique des consommateurs en se focalisant sur deux verrous essentiels que nous nous proposons de lever : (1) résoudre le problème de l’intermittence des énergies renouvelables; (2) minimiser les pertes d’énergie. Pour pallier le problème d’intermittence des énergies renouvelables et dans le but de maintenir un coût énergétique peu onéreux même lors des pics d’utilisation, nous avons intégré un système de stockage intelligent. Nous avons, en effet, proposé des algorithmes permettant d’utiliser les systèmes de stockage intelligents et la négociation multi-agents pour réduire la facture énergétique tout en conservant un taux de décharge minimal de la batterie et une perte énergétique minimale. La validation par simulation de nos contributions a montré que celles-ci répondent aux enjeux identifiés, notamment en réduisant le coût de l’énergie pour les consommateurs en comparaison aux travaux de l’état de l’art. / This thesis focuses on the decentralized management using multi-agent systems of energy, including renewable energy sources, in the smart grid context. Our research aims to minimize consumers’ energy bills by answering two key challenges: (1) handle the problem of intermittency of renewable energy sources; (2) reduce energy losses. To overcome the problem of renewable resources intermittency and in order to minimize energy costs even during peak hours, we integrated an intelligent storage system. To this end, we propose many algorithms in order to use intelligent storage systems and multi-agent negotiation algorithm to reduce energy cost while maintaining a minimal discharge rate of the battery and minimal energy loss. The validation of our contributions has shown that our proposals respond to the identified challenges, including reducing the cost of energy for consumers, in comparison to the state of the art.

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.

Indiana University-Purdue University Indianapolis (IUPUI) / With the rapid growth of technology, scientists are trying to find ways to make the world a more efficient and eco-friendly place. The research and development of electric vehicles suddenly boomed since natural resource are becoming very scarce. The significance of an electric vehicle goes beyond using free energy, it is environ- mental friendly. The objective of this thesis is to understand what Vehicle to Grid Communication (V2G) for an electric vehicle is, and to implement a model of this highly efficient system into a Hybrid Petri Net. This thesis proposes a Hybrid Petri net modeling of Vehicle to Grid (V2G) Communication topology. Initially, discrete, continuous, and hybrid Petri net's are defined, familiarized, and exemplified. Secondly, the Vehicle and Grid side of the V2G communication system is introduced in detail. The modeling of individual Petri nets, as well as their combination is discussed thoroughly. Thirdly, in order to prove these systems, simulation and programming is used to validate the theoretical studies. A Matlab embedded simulation program known as SimHPN is used to simulate specific scenario's in the system, which uses Depth-first Search (DFS) Algorithm. In addition to SimHPN simulation program, Matlab program is made to output four levels of the reachability tree as well as specifying duplicate and terminate nodes. This code incorporates a technique known as Breadth-first Search (BFS) Algorithm.

Der erste Teil dieser Arbeit beschäftigt sich mit der Frage, welchen Einfluss kurzzeitige Schwankungen der erneuerbaren Energiequellen auf die synchrone Netzfrequenz haben. Zu diesem Zweck wird eine lineare Antworttheorie für stochastische Störungen von dynamischen Systemen auf Netzwerken hergeleitet. Anschließend wird diese Theorie verwendet, um den Einfluss von kurzfristigen Wind- und Sonnenschwankungen auf die Netzdynamik zu analysieren. Hierbei wird gezeigt, dass die Frequenzantwort des Netzes weitestgehend homogen ist, aber die Anfälligkeit für Leistungsschwankungen aufgrund von Leitungsverlusten entlang des Leistungsflusses zunimmt. Der zweite Teil der Arbeit befasst sich mit der Modellierung von netzbildenden Wechselrichterregelungen. Bislang existiert kein universelles Modell zur Beschreibung der kollektiven Dynamik solcher Systeme. Um dies zu erreichen, wird unter Ausnutzung der inhärenten Symmetrie des synchronen Betriebszustandes eine Normalform für netzbildende Akteure abgeleitet. Anschließend wird gezeigt, dass dieses Modell eine gute Annäherung an typische Wechselrichter-Dynamiken bietet, aber auch für eine datengesteuerte Modellierung gut geeignet ist. Der letzte Teil der Arbeit befasst sich mit der Analyse des Risikos von Stromausfällen, welche durch Hurrikans verursacht werden. Hohe Windgeschwindigkeiten verursachen häufig Schäden an der Übertragungsinfrastruktur, welche wiederum zu Überlastungen anderer Komponenten führen und damit eine Kaskade von Ausfällen im gesamten Netz auslösen können. Simulationen solcher Szenarien werden durch die Kombination eines meteorologischen Windmodells sowie eines Modells für kaskadierende Leitungsausfälle durchgeführt. Durch Monte-Carlo-Simulationen in einer synthetischen Nachbildung des texanischen Übertragungsnetzes können einzelne kritische Leitungen identifiziert werden, welche zu großflächigen Stromausfällen führen. / The first part of this thesis addresses the question which impact short-term renewable fluctuations have on the synchronous grid frequency. For this purpose, a linear response theory for stochastic perturbations of networked dynamical systems is derived. This theory is then used to analyze the impact of short-term wind and solar fluctuations on the grid frequency. It is shown that while the network frequency response is mainly homogenous, the susceptibility to power fluctuations is increasing along the power flow due to transmission line losses. The second part of the thesis is concerned with modeling grid-forming inverter controls. So far there exists no universal model for studying the collective dynamics of such systems. By utilizing the inherent symmetry of the synchronous operating state, a normal form for grid-forming actors is derived. It is shown that this model provides a useful approximation of certain inverter control dynamics but is also well-suited for a data-driven modeling approach. The last part of the thesis deals with analyzing the risk of hurricane-induced power outages. High wind speeds often cause damage to transmission infrastructure which can lead to overloads of other components and thereby induce a cascade of failures spreading through the entire grid. Simulations of such scenarios are implemented by combining a meteorological wind field model with a model for cascading line failures. Using Monte Carlo simulations in a synthetic test case resembling the Texas transmission system, it is possible to identify critical lines that trigger large-scale power outages.

Με το πέρασμα των χρόνων, τα συστήματα των ανανεώσιμων πηγών ενέργειας αποκτούν ολοένα και περισσότερο μέρος στα ηλεκτρικά δίκτυα. Το ενεργειακό πρόβλημα καθώς και οι επιπτώσεις στο περιβάλλον που αυτό δημιουργεί, οδηγούν σε εναλλακτικές μεθόδους παραγωγής ηλεκτρικής ενέργειας. Αυτό σημαίνει ότι προστίθονται στο δίκτυο εξαρτήματα τα οποία πρέπει να λειτουργούν αρμονικά το ένα σε σχέση με το άλλο για τον κατάλληλο χειρισμό της ηλεκτρικής ισχύος. Τέτοια εξαρτήματα είναι η μονάδα μετατροπής ενέργειας, ο μετατροπέας, το φίλτρο στην έξοδο του μετατροπέα καθώς και άλλες μονάδες πολύπλοκες ή πιο απλές. Η διακοπτική λειτουργία του μετατροπέα καθώς και η στοχαστική διαδικασία της παραγωγής ηλεκτρικής ενέργειας από τις ανανεώσιμες πηγές, προκαλούν τάσεις και ρεύματα με ανώτερες αρμονικές. Στην παρούσα διπλωματική εργασία θα εξετάσουμε διάφορες μεδόδους ελέγχου ισχύος στην πλευρά του δικτύου, με διάφορους τύπους φίλτρων και φορτίων στην έξοδο του μετατροπέα με σκοπό να εντοπίσουμε τις ομοιότητες και τις διαφορές ανάλογα με την τοπολογία που χρησιμοποιούμε. Τα συστήματα που θα εξομοιώσουμε περιλαμβάνουν την dc διασύνδεση, έναν μετατροπέα ισχύος που λειτουργεί με την μέθοδο PWM, διάφορες τοπολογίες φίλτρων όπως RL, LC και LCL σε ισχυρό δίκτυο και τέλος με διάφορα είδη φορτίων, δηλαδή σε ασθενές δίκτυο. Οι έλεγχοι θα εφαρμοστούν στο dq σύγχρονα στρεφόμενο σύστημα αναφοράς με την συχνότητα του δικτύου, με την βοήθεια του μετασχηματισμού Park έτσι ώστε να ελέγξουμε την dc τάση διασύνδεσης και να επιτύχουμε μοναδιαίο συντελεστή ισχύος από την πλευρά του δικτύου. Τέλος θα προσομοιώσουμε τα παραπάνω συστήματα στο Simulink του Matlab και θα εξάγουμε τα αντίστοιχα συμπεράσματα από τα αποτελέσματα των προσομοιώσεων. / During the years, systems of renewable energy sources are becoming more a significant part of electrical networks. The energy problem and its impact on the environment, lead to alternative methods of electricity production. This means that components added to the network must operate harmoniously in relation one to another for proper handling of electrical power. Such components are the power conversion unit, the inverter, the filter at the output of converter units and other complex or simple devices. The switching operation of the converter and the stochastic process of producing electricity from renewable sources, can provoke voltages and currents of higher harmonic spectrum. In this paper we will examine various methods to control power injected in the utility network with different types of filters and loads on the output of the converter in order to identify similarities and differences depending on the topology used. The systems will include simulation of dc link, a power converter that operates method PWM, different filter topologies such as RL, LC and LCL and then of different load topologies. The control will be applied in modern dq rotating reference system to the grid frequency, making use of the Park transformation to control the dc link voltage and succeed unit power factor in the grid side. In conclusion, simulations of these systems will be done in Simulink of Matlab and conclusions will be drowned.

Neste trabalho é apresentada uma abordagem de controle de demanda para consumidores residenciais de baixa tensão, visando melhoria da eficiência energética em Smart Grids. Inicialmente, um emulador de cargas elétricas residenciais é modelado com base na literatura. O emulador é composto pelo modelo de um reservatório de aquecimento de água (boiler), o modelo de um aparelho de ar condicionado e também modelos de consumo de iluminação, televisores e uma geladeira. Utilizando o software Matlab foi realizada a implementação e simulação do emulador. Os principais algoritmos de controle de demanda são investigados, a fim de verificar o seu desempenho quando aplicados ao conjunto de cargas residenciais. Esses algoritmos normalmente realizam o controle de demanda a partir de um sistema de prioridades. Ainda, a partir dessa analise demostra-se que estes algoritmos consideram níveis de conforto do usuário, porém não permitem o acionamento de duas ou mais cargas em um mesmo período caso a demanda da residência ultrapasse um limite predeterminado. Portanto, propõem-se um algoritmo de controle de demanda adaptativo que utiliza o método de busca Rosenbrock, com o objetivo de sobrepujar tais limitações. O procedimento proposto realiza a operação das cargas residenciais de forma gradual considerando níveis de prioridade e parâmetros de conforto dos usuários. Demonstra-se através de simulações e experimentos que através do método proposto é possível realizar a ativação de diversas cargas concorrentemente, desde que respeitados os níveis de conforto e de demanda. Para obtenção dos resultados experimentais o controlador de demanda foi implementado em um sistema embarcado e testado com o emulador de cargas elétricas residenciais implementado em uma arquitetura HIL (Hardware-in-the-loop). Analisando os resultados, observou-se que o consumo de energia foi o mesmo para todos os cenários simulados sendo que a demanda se manteve abaixo dos limites parametrizados. Porém com o limitador de demanda ativo, se obteve uma redução de até 52% no tempo de aquecimento da água utilizando o controlador de demanda adaptativo, dessa forma o desconforto dos usuários pode ser minimizado. / This work presents an approach to control demand for residential low voltage consumers, aiming to improve energy efficiency in Smart Grids. Initially, an emulator of residential electric loads is modeled based on the literature. The emulator consists of a reservoir for water heating model, the model of an air conditioner and also models of consumption for lighting, televisions and a refrigerator. The implementation and simulation were performed using software Matlab. The demand control algorithms are investigated in order to verify its performance when applied to the set of residential loads. These algorithms typically perform control demand from a system of priorities. Still, from this analysis it demonstrates that these algorithms consider levels of user comfort, but do not allow the drive of two or more loads in the same period of residence if the demand exceeds the limit. Therefore, we propose a control algorithm that uses Rosenbrock search of demand adaptive method, aiming to overcome these limitations. The proposed procedure performs the operation of residential loads gradually considering priority levels and parameters of comfort of users. It is shown through simulations and experiments using the proposed method can perform the activation of several concurrently loads, provided they comply with the limits of comfort and demand. To obtain the experimental results demand the controller was implemented in an embedded system and tested with the emulator residential electrical loads implemented in a HIL (Hardware-in-theloop) architecture. Analyzing the results, it was observed that the power consumption is the same for all scenarios simulated and demand remained below parametric limits. But with the demand limiter active, we obtained a reduction of up to 52% in heat water using the demand controller adaptive, so the discomfort of the users can be minimized.