The future smart grid is envisioned as a large scale cyber-physical system encompassing advanced power, computing, communications and control technologies. This work provides comprehensive accounts of the application with optimization methods, probability theory, commitment and dispatching technologies for addressing open problems in three emerging areas that pertain to the smart grid: unit commitment, service restoration problems in microgrid systems, and charging services for the plug-in hybrid electric vehicle (PHEV) markets. The work on the short-term scheduling problem in renewable-powered islanded microgrids is to determine the least-cost unit commitment (UC) and the associated dispatch, while meeting electricity load, environmental and system operating requirements. A novel probability-based concept, {\em probability of self-sufficiency}, is introduced to indicate the probability that the microgrid is capable of meeting local demand in a self-sufficient manner. Furthermore, we make the first attempt in approaching the mixed-integer UC problem from a convex optimization perspective, which leads to an analytical closed-form characterization of the optimal commitment and dispatch solutions. The extended research of the renewable-powered microgrid in the connection mode is the second part of this work. In this situation, the role of microgrid is changed to be either an electricity provider selling energy to the main grid or a consumer purchasing energy from the main grid. This interaction with the main grid completes work on the scheduling schemes. Third, a microgrid should be connected with the main grid most of the time. However, when a blackout of the main grid occurs, how to guarantee reliability in a microgrid as much as possible becomes an immediate question, which motivates us to investigate the service restoration in a microgrid, driven islanded by an unscheduled breakdown from the main grid. The objective is to determine the maximum of the expected restorative loads by choosing the best arrangement of the power network configurations immediately from the beginning of the breakdown all the way to the end of the island mode. Lastly, the work investigating the pricing strategy in future PHEV markets considers a monopoly market with two typical service classes. The unique characteristics of battery charging result in a piecewise linear quality of service model. Resorting to the concept of subdifferential, some theoretical results, including the existence and uniqueness of the subscriber equilibrium as well as the convergence of the corresponding subscriber dynamics are established. In the course of developing revenue-maximizing pricing strategies for both service classes, a general tradeoff has been identi ed between monetization and customer acquisition. / Graduate

Smart grid technologies are starting to be the future of electric power systems. These systems are giving the utilities detailed information about their systems in real time. One of the most challenging things of implementing smart grid applications is employing the communications into the systems. Understanding the available communications can help ease the transition to these smart grid applications. Many of the utility personnel are spending too much time trying to figure out which communication is better for their application or applications. So this thesis presents the different communication types available with discussing the different attributes in which these communication types are going to offer to the utility. Then these communication types are looked such that utilities can quickly understand how to approach the difficult task of obtaining the information from the different smart grid applications by the use of different communication options.

L'énergie solaire photovoltaïque est une forme d'énergie renouvelable permettant de produire de l'électricité par transformation d'une partie du rayonnement solaire grâce à des modules solaires photovoltaïques, comprenant plusieurs cellules photovoltaïques reliées entre elles. Les impacts locaux du solaire sont très réduits : pas de bruit, pas de rejets et, sur le plan visuel, une relative discrétion voire, pour certaines structures intégrées au bâtiment une réelle élégance. L'électrification par l'énergie solaire photovoltaïque est une solution alternative pour un habitat en site isolé, éloigné du réseau électrique. Elle permet de couvrir les besoins domestiques d'une résidence principale en utilisant des appareils standards (petit électroménager, téléviseur, chaine haute-fidélité, micro-informatique, etc...) et des équipements spécifiques économes en énergie (éclairage et froid). Le photovoltaïque raccordé au réseau représente une filière émergente pour la production décentralisée d'électricité. Toute personne disposant d'un habitat résidentiel, d'un bâtiment communal ou d'un autre lieu d'implantation susceptible de recevoir un champ de modules photovoltaïques, peut devenir un producteur d'énergie renouvelable en injectant toute ou partie de l'électricité localement produite dans le réseau de distribution public. Cependant, à ce jour, le développement massif du solaire photovoltaïque, en tant que moyen de production d'électricité raccordé au réseau, reste pénalisé par son coût de production encore très élevé. Cest dans ce contexte que se situent les travaux de recherche présentés dans cette habilitation à diriger des recherches. Depuis 1996, les recherches du LAAS se sont orientées sur l'Optimisation, la Gestion et le Traitement de l'Energie, et plus particulièrement sur l'optimisation de chaines modulaires de conversion d'énergie photovoltaïque, en complémentarité avec la communauté scientifique française, majoritairement orientée vers la synthèse de matériaux e t le développement de nouveaux types de cellules. L'objectif est de concevoir, réaliser et caractériser des systèmes en liaison avec un aspect intégration technologique fort. Actuellement, différentes architectures de gestion de lénergie photovoltaïque sont proposées sur le marché et permettent de valoriser plus ou moins bien la production de ce type dénergie. Nous nous consacrerons ici aux architectures de conversion DC-DC discrétisées, permettant dapporter une solution technologique novatrice en termes damélioration du rendement de la chaîne de conversion, avec une volonté forte dintégration de lensemble. Après avoir rappelé le concept et la validité du concept de discrétisation, nous nous focaliserons sur létude dun micro-convertisseur pour une cellule photovoltaïque Tandem. Enfin, nous proposons diverses perspectives de recherches inhérentes à la thématique du photovoltaïque. Bien que la fourniture dénergie décentralisée comporte de nombreux avantages, la transition vers un " smart grid " représente plusieurs défis. Un des enjeux majeurs des réseaux d'électricité de demain consiste en lassimilation de la production d'électricité intermittente. Le développement des énergies renouvelables, sources de production d'électricité décentralisées, est souvent freiné par une inadéquation de ces moyens de production avec le fonctionnement du réseau actuel. Ainsi, partant du constat que la production intermittente d'énergie est en effet difficile à intégrer au réseau et ne correspond pas aux périodes de consommation de pointe, nous envisagerons différentes solutions pour intégrer la production d'électricité d'origine renouvelable, notamment par lintroduction de moyens de stockage. Pour valider notre approche qui se veut globale sur la problématique de lénergie, nous évoquerons la constitution du démonstrateur ADREAM en cours de construction au LAAS-CNRS, conçu dès le départ comme un outil de validation grandeur réelle.

The deployment of Renewable Energy (RE)-based generation has experienced a sustained global growth in the recent decades, driven by many countries' interest in reducing greenhouse gas emissions and dependence on fossil fuel for electricity generation. This trend is also observed in remote off-grid systems (isolated microgrids), where local communities, in an attempt to reduce fossil fuel dependency and associated economic and environmental costs, and to increase availability of electricity, are favouring the installation of RE-based generation. This practice has posed several challenges to the operation of such systems, due to the intermittent and hard-to-predict nature of RE sources. In particular, this thesis addresses the problem of reliable and economic dispatch of isolated microgrids, also known as the energy management problem, considering the uncertain nature of those RE sources, as well as loads. Isolated microgrids feature characteristics similar to those of distribution systems, in terms of unbalanced power flows, significant voltage drops and high power losses. For this reason, detailed three-phase mathematical models of the microgrid system and components are presented here, in order to account for the impact of unbalanced system conditions on the optimal operation of the microgrid. Also, simplified three-phase models of Distributed Energy Resources (DERs) are developed to reduce the level of complexity in small units that have limited impact on the optimal operation of the system, thus reducing the number of equations and variables of the problem. The proposed mathematical models are then used to formulate a novel energy management problem for isolated microgrids, as a deterministic, multi-period, Mixed-Integer Nonlinear Programming (MINLP) problem. The multi-period formulation allows for a proper management of energy storage resources and multi-period constraints associated with the commitment decisions of DERs. In order to obtain solutions of the energy management problem in reasonable computational times for real-time, realistic applications, and to address the uncertainty issues, the proposed MINLP formulation is decomposed into a Mixed-Integer Linear Programming (MILP) problem, and a Nonlinear programming (NLP) problem, in the context of a Model Predictive Control (MPC) approach. The MILP formulation determines the unit commitment decisions of DERs using a simplified model of the network, whereas the NLP formulation calculates the detailed three-phase dispatch of the units, knowing the commitment status. A feedback signal is generated by the NLP if additional units are required to correct reactive power problems in the microgrid, triggering a new calculation MINLP problem. The proposed decomposition and calculation routines are used to design a new deterministic Energy Management System (EMS) based on the MPC approach to handle uncertainties; hence, the proposed deterministic EMS is able to handle multi-period constraints, and account for the impact of future system conditions in the current operation of the microgrid. In the proposed methodology, uncertainty associated with the load and RE-based generation is indirectly considered in the EMS by continuously updating the optimal dispatch solution (with a given time-step), based on the most updated information available from suitable forecasting systems. For a more direct modelling of uncertainty in the problem formulation, the MILP part of the energy management problem is re-formulated as a two-stage Stochastic Programming (SP) problem. The proposed novel SP formulation considers that uncertainty can be properly modelled using a finite set of scenarios, which are generated using both a statistical ensembles scenario generation technique and historical data. Using the proposed SP formulation of the MILP problem, the deterministic EMS design is adjusted to produce a novel stochastic EMS. The proposed EMS design is tested in a large, realistic, medium-voltage isolated microgrid test system. For the deterministic case, the results demonstrate the important connection between the microgrid's imbalance, reactive power requirements and optimal dispatch, justifying the need for detailed three-phase models for EMS applications in isolated microgrids. For the stochastic studies, the results show the advantages of using a stochastic MILP formulation to account for uncertainties associated with RE sources, and optimally accommodate system reserves. The computational times in all simulated cases show the feasibility of applying the proposed techniques to real-time, autonomous dispatch of isolated microgrids with variable RE sources.

The effective modeling and analysis of large-scale power system disturbances especially those stemming from intentional attack represents an open engineering and research problem. Challenges stem from the need to develop intelligent models of cyber-physical attacks that produce salient disruptions and appropriately describe meaningful cyber-physical interdependencies such that they balance precision, scale and complexity. In our research, we present a foundation for the development of a class of intelligent cyber-physical attacks termed coordinated variable structure switching attacks whereby opponents aim to destabilize the power grid through con- trolled switching sequence. Such switching is facilitated by cyber-attack and corruption of communication channels and control signals of the associated switch(es). We provide methods and theorems to construct such attack models and demonstrate their utility in the simulation of extensive system disturbances. Our proposed class of cyber-physical switching attacks for smart grid systems has the potential to disrupt large-scale power system operation within a short interval of time. Through successful cyber intrusion, an opponent can remotely apply a state- dependent coordinated switching sequence on one or more relays and circuit breakers of a power system to disrupt operation. Existence of this switching vulnerability is dependent on the local structure of the power grid. Variable structure systems theory is employed to effectively model the cyber-physical aspects of a smart grid and determine the existence of the vulnerability and construct the destabilizing switching attack sequence. We illustrate the utility of the attack approach assess its impact on the different power system test cases including the single machine infinite bus power system model and the Western Electricity Coordinating Council (WECC) 3-machine 9-bus system through MATLAB/Simulink and PSCAD simulation environment. The results demonstrate the potential of our approach for practical attack. Moreover, we build on our work in several ways. First, we extend the research to demonstrate an approach to mitigation within the variable structure system frame- work. We demonstrate via small signal analysis how through persistent switching a stable sliding mode can be used to disrupt a dynamical system that seems stable. We also design an approach to vulnerability analysis to assess the feasibility of co-ordinated variable structure switching attacks. Moreover, we study the performance of our attack construction approach when the opponent has imperfect knowledge of the local system dynamics and partial knowledge of the generator state. Based on the system with modeling errors, we study the performance of coordinated variable structure switching attacks in the presence of state estimation. Finally, we illustrate the concepts of attack model within the multiple switching framework, the cascading failure analysis is employed in the New-England 10-machine, 39-bus power system using MATLAB/Simulink and DSATools simulation environment. Our results demonstrate the potential for coordinated variable structure switching attacks to enable large-scale power system disturbances.

Orientador: Anna Diva Plasencia Lotufo / Resumo: A maior inserção de tecnologias da informação nas redes de distribuição de energia elétrica vem permitindo que maiores volumes de dados de consumo sejam capturados em níveis cada vez mais detalhados, menos agregados e com maiores resoluções. Com a evolução dos mercados de energia elétrica, esses tipos de dados alcançam maior importância, uma vez que a comercialização de energia também passa a considerar estes níveis de consumo. Diversas técnicas têm sido aplicadas para previsão de cargas elétricas, como modelos estatísticos, de inteligência computacional e híbridos. Na literatura especializada é possível encontrar trabalhos que aplicam a rede neural artificial ARTMAP Fuzzy para tarefas de previsão de cargas elétricas, no entanto, a técnica ainda é pouco explorada em cenários de consumo menos agregados, e com maiores níveis de detalhe. Neste trabalho a rede ARTMAP Fuzzy é aplicada em tarefas de previsão multi-step de cargas elétricas reais com distintos níveis de agregação. Considerando o impacto do ruído sobre os previsores, sobretudo na capacidade de generalização das redes neurais artificiais, a técnica singular spectrum analysis é aplicada na tarefa de remoção de ruído. Os resultados de previsão permitiram analisar desempenho da rede ARTMAP Fuzzy, que foi comparada com outros dois previsores utilizados como benchmark, a saber, seasonal autoregressive integrated moving average e a rede neural multiLayer perceptron. A remoção de ruído permitiu melhora nos níveis de generaliz... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The increased insertion of information technologies in electricity distribution networks has allowed larger volumes of consumption data to be captured at increasingly detailed, less aggregated and higher resolution levels. With the evolution of electric energy markets, these types of data become more important, since the commercialization of energy also begins to consider these levels of consumption. Several techniques have been applied to predict electrical loads, such as statistical, computational intelligence and hybrids models. In the specialized literature it is possible to find works that apply the artificial neural network ARTMAP Fuzzy for tasks of prediction of electric charges, however, the technique is still little explored in less aggregated consumption scenarios, and with greater levels of detail. In this work the ARTMAP Fuzzy network is applied in multi-step forecasting tasks of real electric loads with different levels of aggregation. Considering the impact of noise on predictors, especially in the generalization capacity of artificial neural networks, the singular spectrum analysis technique is applied in the noise removal task. The prediction results allowed to analyze the performance of the ARTMAP Fuzzy network, which was compared with other two predictors used as benchmark, namely seasonal autoregressive integrated moving average and the multiLayer perceptron neural network. The noise removal allowed an improvement in the levels of network generalization, po... (Complete abstract click electronic access below) / Doutor

Made available in DSpace on 2014-06-11T19:30:50Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-07-21Bitstream added on 2014-06-13T19:19:31Z : No. of bitstreams: 1 leao_fb_dr_ilha.pdf: 4326970 bytes, checksum: 5e80d8b3eb8a0bff2c52ea28e2f0a451 (MD5) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Neste trabalho é proposta uma metodologia para a análise e interpretação de alarmes em tempo real em sistemas de distribuição de energia elétrica, considerando o diagnóstico em nível de subestações e redes. A metodologia busca superar as dificuldades e desvantagens dos métodos já propostos na literatura especializada para resolver o diagnóstico de faltas em sistemas de potência. O método proposto emprega um modelo matemático original bem como um novo algoritmo genético para efetuar o diagnóstico dos alarmes de maneira eficiente e rápida. O modelo matemático é dividido em duas partes fundamentais: (1) modelo de operação do sistema de proteção; e (2) modelo de Programação Binária Irrestrita (PBI). A parte (1) é composta por um conjunto de equações de estados esperados das funções de proteção dos relés do sistema, modeladas com base na lógica de operação de funções de proteção tais como sobrecorrente, diferencial e distância, bem como na filosofia de proteção de sistemas de potência. A parte (2) é estabelecida através de uma função objetivo formulada com base na teoria de cobertura parcimoniosa (parcimonious set covering theory), e busca a associação ou “match” entre os relatórios de alarmes informados pelo sistema SCADA (Supervisory Control and Data Acquisition) e os estados esperados das funções de proteção formuladas na parte (1) do modelo. O novo algoritmo genético proposto é empregado para minimizar o modelo de PBI e possui como característica a utilização de dois parâmetros de controle. O algoritmo possui taxas de recombinação e mutação automática e dinamicamente calibradas, baseadas na saturação da população corrente, possuindo uma imediata resposta à possível convergência prematura para ótimos locais. A metodologia desenvolvida para o diagnóstico... / This work proposes a methodology for the analysis and interpretation of real-time alarms in electric power distribution systems in the substation level and network level. The methodology seeks to overcome the difficulties and disadvantages of the methods already proposed in the literature to solve the fault diagnosis in power systems. The proposed method employs a novel mathematical model and a genetic algorithm to carry out the diagnosis of alarms efficiently and quickly. The model is divided into two main parts: (1) a protection system operation model; and (2) Unconstrained Binary Programming (UBP) model. Part (1) provides a set of expected state equations of the protective relay functions established based on the protection operation logic such as overcurrent, differential and distance as well as the protection philosophy. Part (2) is established through an objective function formulated based on parsimonious set covering theory for associating the alarms reported by SCADA (Supervisory Control and Data Acquisition) system with the expected states of the protective relay functions. The novel genetic algorithm use only two control parameters and is employed to minimize the UBP model. In addition the algorithm has recombination and mutation rates automatically and dynamically calibrated based on the saturation of the current population and it presents an immediate response to possible premature convergence to local optima. The methodology developed for the diagnosis of substations is extended to distribution networks considering that the network has sufficient level of automation for remote monitoring of the primary feeders. In this way a new paradigm for protection of distribution networks developed based on Smart Grid concept is proposed. Extensive tests are performed with the methodology applied to distribution... (Complete abstract click electronic access below)

Att öka leveranskvaliteten i sina elnät är något som varje nätbolag strävar mot. En metod att göra detta kan vara att utrusta nätstationer i mellanspänningsnätet med feldetektering och fjärrstyrning för snabbare felsökning och sektionering vid fel. I denna studie har dessa möjligheter utretts och även de potentiella vinsterna i kortare avbrottstider mätt i indikatorn SAIDI. Studien har resulterat i ett förslag för fortsatt investering i feldetektering och fjärrstyrning i Umeå Energis elnät. Den metod som använts är att beräkna SAIDI för det värsta felscenariot för varje matande linje som tittats på, både med och utan elnätsautomation. Det förslag som tagits fram har utgått ifrån de enskilda matningarna förutsättningar vad gäller kundantal, antal nätstationer och nättopologi och har sedan jämförts med två standardalternativ, med detektering i samtliga nätstationer samt detektering i mitten av linjen. Resultatet visar att det förslag som lämnats till Umeå Energi har potential att sänka det summerade SAIDI-värdet vid värsta felscenario från 37 minuter till 10 minuter i de matningar som undersökts. Detta till en kostnad av mindre än två miljoner kronor, eller en kostnad per potentiellt minskad SAIDI-minut på ca. 70 000 kr. Studien har tittat på 16 matande linjer med totalt ca. 17 000 kunder.

Over the past decades, the concepts and methods for reliability assessment have evolved from analysing the ability of individual components to operate without faults and as intended during their lifetime, into the comprehensive approaches for evaluating various engineering strategies for system planning, operation and maintenance studies. The conventional reliability assessment procedures now receive different perspectives in different engineering applications and this thesis aims to improve existing approaches by incorporating in the analysis: a) a more detailed and accurate models of LV and MV networks and their reliability equivalents, which are important for the analysis of transmission and sub-transmission networks, b) the variations in characteristics and parameters of LV and MV networks in different areas, specified as “generic” UK/Scottish highly-urban, urban, sub-urban and rural network models, c) the relevant requirements for network reliability performance imposed by Regulators on network operators, d) the actual aggregate load profiles of supplied customers and their correlation with typical daily variations of fault probabilities and repair times of considered network components, and e) some of the expected “smart grid” functionalities, e.g., increased use of network automation and reconfiguration schemes, as well as the higher penetration levels of distributed generation/storage resources. The conventional reliability assessment procedures typically do not include, or only partially include the abovementioned important factors and aspects in the analysis. In order to demonstrate their importance, the analysis presented in the thesis implements both analytical and probabilistic reliability assessment methods in a number of scenarios and study cases with improved and more detailed “generic” LV and MV network models and their reliability equivalents. Their impact on network reliability performance is analysed and quantified in terms of the frequency and duration of long and short supply interruptions (SAIFI and SAIDI), as well as energy not supplied (ENS). This thesis addresses another important aspect of conventional approaches, which often, if not always, provide separate indicators for the assessment of system-based reliability performance and for the assessment of customer-based reliability performance. The presented analysis attempts to more closely relate system reliability performance indicators, which generally correspond to a fictitious “average customer”, to the actual “best-served” and “worst-served” customers in the considered networks. Here, it is shown that a more complex metric than individual reliability indicators should be used for the analysis, as there are different best-served and worst-served customers in terms of the frequency and duration of supply interruptions, as well as amounts of not supplied energy. Finally, the analysis in the thesis considers some aspects of the anticipated transformation of existing networks into the future smart grids, which effectively require to re-evaluate the ways in which network reliability is approached at both planning and operational stages. Smart grids will feature significantly higher penetration levels of variable renewable-based distributed generation technologies (with or without energy storage), as well as the increased operational flexibility, automation and remote control facilities. In this context, the thesis evaluates some of the considered smart grid capabilities and functionalities, showing that improved system reliability performance might result in a deterioration of power quality performance. This is illustrated through the analysis of applied automation, reconfiguration and automatic reclosing/remote switching schemes, which are shown to reduce frequency and duration of long supply interruptions, but will ultimately result in more frequent and/or longer voltage sags and short interruptions. Similarly, distributed generation/storage resources might have strong positive impact on system reliability performance through the reduced power flows in local networks and provision of alternative supply points, even allowing for a fully independent off-grid operation in microgrids, but this may also result in the reduced power quality levels within the microgrids, or elsewhere in the network, e.g. due to a higher number of switching transfers and transients.

This thesis has contributed to the design of suitable decision-making techniques for energy management in the smart grid with emphasis on energy efficiency and uncertainty analysis in two smart grid applications. First, an energy trading model among distributed microgrids (MG) is investigated, aiming to improve energy efficiency by forming coalitions to allow local power transfer within each coalition. Then, a more specific scenario is considered that is how to optimally schedule Electric Vehicles (EV) charging in a MG-like charging station, aiming to match as many as EV charging requirements with the uncertain solar energy generation. The solutions proposed in this thesis can give optimal coalition formation patterns for reduced power losses and achieve optimal performance for the charging station. First, several algorithms based on game theory are investigated for the coalition formation of distributed MGs to alleviate the power losses dissipated on the cables due to power transfer. The seller and buyer MGs can make distributed decisions whether to form a coalition with others for energy trading. The simulation results show that game theory based methods that enable cooperation yield a better performance in terms of lower power losses than a non-cooperative approach. This is because by forming local coalitions, power is transferred within a shorter distance and at a lower voltage. Thus, the power losses dissipated on the transmission lines and caused by power conversion at the transformer are both reduced. However, the merge-and-split based cooperative games have an inherent high computational complexity for a large number of players. Then, an efficient framework is established for the power loss minimization problem as a college admissions game that has a much lower computational complexity than the merge-and-split based cooperative games. The seller and buyer MGs take the role of colleges and students in turn and apply for a place in the opposite set following their preference lists and the college MGs’ energy quotas. The simulation results show that the proposed framework demonstrates a comparable power losses reduction to the merge-and-split based algorithms, but runs 700 and 18000 times faster for a network of 10 MGs and 20 MGs, respectively. Finally, the problem of EV charging using various energy sources is studied along with their impact on the charging station’s performance. A multiplier k is introduced to measure the effect of solar prediction uncertainty on the decision-making process of the station. A composite performance index (the Figure of Merit, FoM) is also developed to measure the charging station’s utility, EV users charging requirements and the penalties for turning away new arrivals and for missing charging deadlines. A two-stage admission and scheduling mechanism is further proposed to find the optimal trade-off between accepting EVs and missing charging deadlines by determining the best value of the parameter k under various energy supply scenarios. The numerical evaluations give the solution to the optimization problem and show that some of the key factors such as shorter and longer deadline urgencies of EVs charging requirements, stronger uncertainty of the prediction error, storage capacity and its initial state will not affect significantly the optimal value of the parameter k.