Academic literature on the topic 'Complex power systems'

Le calcul des valeurs propres intervient dans des modèles de maladies d’épidémiques et pourrait être utilisé comme un allié des campagnes de vac- cination dans les actions menées par les organisations de soins de santé. La modélisation épidémique peut être considérée, par analogie, comme celle des viruses d’ordinateur qui dépendent de l’état de graphe sous-jacent à un moment donné. Nous utilisons PageRank comme méthode pour étudier la propagation de l’épidémie et d’envisager son calcul dans le cadre de phé- nomène petit-monde. Une mise en œuvre parallèle de méthode multiple de "implicitly restar- ted Arnoldi method" (MIRAM) est proposé pour calculer le vecteur propre dominant de matrices stochastiques issus de très grands réseaux réels. La grande valeur de "damping factor" pour ce problème fait de nombreux algo- rithmes existants moins efficace, tandis que MIRAM pourrait être promet- teuse. Nous proposons également dans cette thèse un générateur de graphe parallèle qui peut être utilisé pour générer des réseaux synthétisés distri- bués qui présentent des structures "scale-free" et petit-monde. Ce générateur pourrait servir de donnée pour d’autres algorithmes de graphes également. MIRAM est mis en œuvre dans le cadre de trilinos, en ciblant les grandes données et matrices creuses représentant des réseaux sans échelle, aussi connu comme les réseaux de loi de puissance. Hypergraphe approche de partitionnement est utilisé pour minimiser le temps de communication. L’al- gorithme est testé sur un grille national de Grid5000. Les expériences sur les très grands réseaux tels que Twitter et Yahoo avec plus de 1 milliard de nœuds sont exécutées. Avec notre mise en œuvre parallèle, une accélération de 27× est satisfaite par rapport au solveur séquentiel<br>The eigenvalue equation intervenes in models of infectious disease prop- agation and could be used as an ally of vaccination campaigns in the ac- tions carried out by health care organizations. The epidemiological model- ing techniques can be considered by analogy, as computer viral propagation which depends on the underlying graph status at a given time. We point out PageRank as method to study the epidemic spread and consider its calcula- tion in the context of small-world phenomenon. A parallel implementation of multiple implicitly restarted Arnoldi method (MIRAM) is proposed for calculating dominant eigenpair of stochastic matrices derived from very large real networks. Their high damp- ing factor makes many existing algorithms less efficient, while MIRAM could be promising. We also propose in this thesis a parallel graph gen- erator that can be used to generate distributed synthesized networks that display scale-free and small-world structures. This generator could serve as a testbed for graph related algorithms. MIRAM is implemented within the framework of Trilinos, targeting big data and sparse matrices representing scale-free networks, also known as power law networks. Hypergraph partitioning approach is employed to minimize the communication overhead. The algorithm is tested on a nation wide cluster of clusters Grid5000. Experiments on very large networks such as twitter and yahoo with over 1 billion nodes are conducted. With our parallel implementation, a speedup of 27× is met compared to the sequential solver

This research proposes, implements and analyses a novel framework for multiobjective optimisation through evolutionary computing aimed at, but not restricted to, real-world problems in the engineering design domain. Evolutionary algorithms have been used to tackle a variety of non-linear multiobjective optimisation problems successfully, but their success is governed by key parameters which have been shown to be sensitive to the nature of the particular problem, incorporating concerns such as the number of objectives and variables, and the size and topology of the search space, making it hard to determine the best settings in advance. This work describes a real-encoded multi-objective optimising evolutionary algorithm framework, incorporating a genetic algorithm, that uses self-adaptive mutation and crossover in an attempt to avoid such problems, and which has been benchmarked against both standard optimisation test problems in the literature and a real-world airfoil optimisation case. For this last case, the minimisation of drag and maximisation of lift coefficients of a well documented standard airfoil, the framework is integrated with a freeform deformation tool to manage the changes to the section geometry, and XFoil, a tool which evaluates the airfoil in terms of its aerodynamic efficiency. The performance of the framework on this problem is compared with those of two other heuristic MOO algorithms known to perform well, the Multi-Objective Tabu Search (MOTS) and NSGA-II, showing that this framework achieves better or at least no worse convergence. The framework of this research is then considered as a candidate for smart (electricity) grid optimisation. Power networks can be improved in both technical and economical terms by the inclusion of distributed generation which may include renewable energy sources. The essential problem in national power networks is that of power flow and in particular, optimal power flow calculations of alternating (or possibly, direct) current. The aims of this work are to propose and investigate a method to assist in the determination of the composition of optimal or high-performing power networks in terms of the type, number and location of the distributed generators, and to analyse the multi-dimensional results of the evolutionary computation component in order to reveal relationships between the network design vector elements and to identify possible further methods of improving models in future work. The results indicate that the method used is a feasible one for the achievement of these goals, and also for determining optimal flow capacities of transmission lines connecting the bus bars in the network.

Discussing, defining and engaging with ‘terrorism’ has long been limited to the narrowly framed situations in which parties to an asymmetric conflict resort to the use of force and to the legitimacy they have in doing so. The problem with the limited understanding of ‘terrorism’ and ‘counterterrorism’ as ‘facts of objective reality’ is the lack of attention to the role of the extreme asymmetry of power in conflicts involving ‘terrorism’ that does not lend itself to analysis readily. This thesis introduces a new theoretical concept, the Terrorism Complex that signifies the complexity of power/knowledge relations and the complexity of power/knowledge practices that operate on a discursive and non-discursive level through time and are affected by the mechanisms of power that stem from the asymmetry of power between the actors involved in a conflict. The research into the Terrorism Complex involves an ontological and epistemological widening of the research focus to account for these effects of the interplay between power and knowledge on the production, construction and perception of ‘terrorism’. I draw on postmodern scholarship and the Critical Terrorism Studies to present a theoretical and methodological framework that is used to examine the production of knowledge in relation to the asymmetries of power. The Israeli–Palestinian conflict is used as a case study for the study of power asymmetry in the political field that determines who will be labelled a ‘terrorist’ and who will be able to claim the moral high ground. The research also reveals the surprising extent to which the power over discourse obscures the role of the systemic terrorising exercise of state power in inducing ‘terrorism’. The final chapter concentrates on the media’s role in the Terrorism Complex. It applies the findings from other chapters to observe the Terrorism Complex in action.

Doctor of Philosophy<br>Computing and Information Sciences<br>Scott A. DeLoach<br>As sensor prices drop and computing devices continue to become more compact and powerful, computing capabilities are being embedded throughout our physical environment. Connecting these devices in cyber-physical systems (CPS) enables applications with significant societal impact and economic benefit. However, engineering CPS poses modeling, architecture, and engineering challenges and, to fully realize the desired benefits, many outstanding challenges must be addressed. For the cyber parts of CPS, two decades of work in the design of autonomous agents and multiagent systems (MAS) offers design principles for distributed intelligent systems and formalizations for agent-oriented software engineering (AOSE). MAS foundations offer a natural fit for enabling distributed interacting devices. In some cases, complex control structures such as holarchies can be advantageous. These can motivate complex organizational strategies when implementing such systems with a MAS, and some designs may require agents to act in multiple groups simultaneously. Such agents must be able to manage their multiple associations and assignments in a consistent and unambiguous way. This thesis shows how designing agents as systems of intelligent subagents offers a reusable and practical approach to designing complex systems. It presents a set of flexible, reusable components developed for OBAA++, an organization-based architecture for single-group MAS, and shows how these components were used to develop the Adaptive Architecture for Systems of Intelligent Systems (AASIS) to enable multigroup agents suitable for complex, multigroup MAS. This work illustrates the reusability and flexibility of the approach by using AASIS to simulate a CPS for an intelligent power distribution system (IPDS) operating two multigroup MAS concurrently: one providing continuous voltage control and a second conducting discrete power auctions near sources of distributed generation.

La vulnérabilité des systèmes électriques est l'un des problèmes liés à leur complexité. Il a fait l’objet d’une attention croissante des chercheurs au cours des dernières décennies. Malgré cela, les phénomènes fondamentaux qui régissent la vulnérabilité du système ne sont pas encore bien compris.Comprendre comment la vulnérabilité des réseaux électriques émerge de leur topologie est la motivation principale du présent travail. Pour cela, le présent travail de recherché propose une nouvelle méthode pour évaluer la vulnérabilité des systèmes électriques et identifier leurs éléments les plus critiques. La méthode permet d’avoir une bonne compréhension des liens entre la topologie d’un réseau et sa vulnérabilité à des pertes d’ouvrages (lignes ou transformateurs).La première partie de ce travail consiste en une analyse critique des approches rencontrées dans la littérature, s’appuyant sur la théorie des graphes, pour analyser la vulnérabilité des réseaux électriques. Les résultats fournis par ces approches pour quatre réseaux IEEE sont comparés à ceux fournis par une analyse de contingence de référence, basée sur une résolution d’un load-flow AC. Des avantages et inconvénients de chaque approche est tirée une méthode améliorée pour l'évaluation de la vulnérabilité des réseaux électriques aux pertes d’ouvrage. Cette méthode est basée sur une approximation courant continue du load flow.La deuxième partie propose une nouvelle approche basée sur la théorie spectrale des graphes et son utilisation pour la résolution d’un load flow DC. Elle permet de mieux comprendre comment la vulnérabilité des réseaux électriques et leurs composants critiques émergent de la topologie du graphe sous-jacent au réseau<br>The vulnerability of electrical systems is one of the problems related to their complexity. It has received increasing attention from researchers in recent decades. Despite this, the fundamental phenomena that govern the vulnerability of the system are still not well understood.Understanding how the vulnerability of power systems emerges from their complex organization is, therefore, the main motivation of the present work. It proposes the definition of a standard method to assess the vulnerability of power systems and identify their most critical elements. The method enables a better understanding of the links between the topology of the grid and the line outage vulnerabilities.The first part of this research work offers a critical review of literature approaches used to assess system vulnerability. The results provided by these approaches for four IEEE test systems are confronted to a reference contingency analysis using AC power flow calculations. From these analyses, pros and cons of each approach are outlined. An improved method for assessment of system vulnerability to line outages is defined from this confrontation. It is based on DC load flow and graph theory.The second part proposes a new approach based on spectral graph theory and solving of DC power flow to identify how system vulnerability and critical components emerge from the power network topology

The main performance objective in an electric power grid entails timely and efficient generation and delivery to the time-varying electricity demand. As the electricity industry is witnessing proliferation of the mainstream renewables, the minute-by-minute variations in wind and solar power generation may result in temporary electricity scarcity that jeopardizes grid stability and quality of service. The evolving electricity markets are aimed at incentivizing the conventional generators to reinforce their operating flexibility. This dissertation concerns the goal of enhancing the dynamic response rates of interconnected controllable resources by means of a multi-layered fuel input control of electrically coupled heterogeneous energy conversion components. Both power engineering and large-scale control contributions are made in support of this enhancement. First, improved fuel input controls are designed to enable flexible physics-based energy conversion dynamics required by the interconnected grid. To efficiently utilize the resources load-following and regulation problems are stated. The efficacy of proposed fuel input control designs in enhancing the dynamic response rates is illustrated on IEEE 14-bus system. Second, the problem is formalized as multi-input multioutput time-varying trajectory tracking based on a decentralized spatiotemporal composite control design. The concepts of vector-Lyapunov function and singular perturbation are invoked to formalize model decompositions, over space and time, respectively. Next, the assumptions for model simplifications are relaxed and the problem of parametric uncertainty is addressed. A minimumcost resilient co-design approach is introduced for storage-sensors-communication channels in a complex electric power grid. The notion of selective strong structural fixed modes is explored as a characterization of feasible decentralized control laws for an arbitrary system realization satisfying a pre-specified structure. Finally, it is proposed that planning of generation portfolio must be driven by the objective of maintaining adequate operating flexibility in the system. The goal is to ensure sufficient ramp capacity to sustain the significant integration of intermittent renewable resources.