As part of power distribution network verification, one should check if the voltage fluctuations exceed some critical threshold. The traditional simulation-based solution to this problem is intractable due to the large number of possible circuit behaviors. This approach also requires full knowledge of the details of the underlying circuitry, not allowing one to verify the power distribution network early in the design flow. In this work, we consider the power and ground grids together (i.e. dual grid) and formulate the problem of computing the worst-case voltage fluctuations of the dual grid under the framework of current constraints. Then, we present a solution technique in which tight lower and upper bounds on worst-case voltage fluctuations are computed via linear programs. Experimental results indicate that the proposed technique results in errors in the range of a few mV . We also present extensions to single grid (i.e. only power grid) verification techniques.

The grid orientation effect is a long-standing problem plaguing reservoir simulators that employ finite difference schemes. A rotation of the computational grids yields a substantially different solution under certain circumstances. For example, in a five-spot pattern, the predicted recovery, water cut performance and the locations of the fronts depend on the type of grid system used. A Cartesian grid with one axis parallel to the line joining an injector and producer gives a solution significantly different from a grid that has the axes oriented at 45° to this line. This study develops a unique grid-block assignment where rectangular grid blocks are interspersed with octagonal grid blocks. This grid block system is called the Hybrid Grid Block (HGB) system. The objective of this study is to evaluate the grid orientation effect of the HGB grid to see whether it is an improvement over the conventional Cartesian grid system. In HGB, flow can progress in four directions in the octagonal grid blocks and two in the square grid blocks. The increase in the number of flow directions in the octagonal grid blocks is expected to reduce the grid orientation effect in the model. Hence, this study also evaluates the grid orientation effect of the HGB and compares it with the Cartesian grid system. To test the viability of HGB, a general purpose finite difference IMPES-formulated two-dimensional black oil simulator was developed in this study, while retaining the familiar finite-difference discretization of the flow equations. Several simulation cases were conducted to compare HGB and conventional grid block systems. Comparisons with commercial simulator are also made. Despite the fact that the reservoir is isotropic and homogeneous, grid orientation effect was still observed when rectangular Cartesian grid models are run at mobility ratio, M = 1.0. Grid refinement can help to reduce the grid orientation effect in rectangular Cartesian grid models when there are favorable mobility ratios, i.e. M = 1.0 or less. However, at an unfavorable mobility ratio of M = 10.0, it is found that neither parallel nor diagonal orientation can be used reliably for the displacement problems run in this study. This is because as the number of grid blocks is increased, the performance of diagonal and parallel models actually diverges for the grid spacings investigated here. On the other hand, HGB grid is able to reduce the grid orientation effect even for unfavorable mobility ratio displacement problems (up to M = 50.0), with maximum relative difference in pore volume recovered of 6% between parallel and diagonal HGB grid models for all the cases run in this study. Comparisons between the conventional Cartesian and HGB grid show that the HGB grid is more effective in reducing the grid orientation effect than the Cartesian grid. The HGB grid performs better by consistently giving a smaller relative difference between HGB parallel grid and HGB diagonal grid in pore volume recovered (6.0, 4.5, 3.3, and 2.2%) compared to the relative difference between Cartesian parallel grid and Cartesian diagonal grid in pore volume recovered (17.0, 13.0, 9.3, 7.9%) at similar averaged area per grid block for all the four comparison cases studied.

<p>We study techniques to enforce and provision differentiated service levels in <i>Computational Grid</i> systems. The Grid offers simplified provisioning of peak-capacity for applications with computational requirements beyond local machines and clusters, by sharing resources across organizational boundaries. Current systems have focussed on access control, i.e., managing who is allowed to run applications on remote sites. Very little work has been done on providing differentiated service levels for those applications that are admitted. This leads to a number of problems when scheduling jobs in a fair and efficient way. For example, users with a large number of long-running jobs could starve out others, both intentionally and non-intentionally. We investigate the requirements of High Performance Computing (HPC) applications that run in academic Grid systems, and propose two models of service-level management. Our first model is based on global real-time quota enforcement, where projects are granted resource quota, such as CPU hours, across the Grid by a centralized allocation authority. We implement the SweGrid Accounting System to enforce quota allocated by the Swedish National Allocations Committee in the SweGrid production Grid, which connects six Swedish HPC centers. A flexible authorization policy framework allows provisioning and enforcement of two different service levels across the SweGrid clusters; high-priority and low-priority jobs. As a solution to more fine-grained control over service levels we propose and implement a <i>Grid</i> <i>Market </i>system, using a market-based resource allocator called Tycoon. The conclusion of our research is that although the Grid accounting solution offers better service level enforcement support than state-of-the-art production Grid systems, it turned out to be complex to set the resource price and other policies manually, while ensuring fairness and efficiency of the system. Our Grid Market on the other hand sets the price according to the dynamic demand, and it is further incentive compatible, in that the overall system state remains healthy even in the presence of strategic users.</p>

Pour les véhicules intelligents, un système de perception est un élément clé pour caractériser en temps réel un modèle de l’environnement de conduite autour du véhicule. Lors de la modélisation de l’environnement, les informations relatives aux obstacles doivent être gérées prioritairement car les collisions peuvent être mortelles pour les autres usagers de la route ou pour les passagers à bord du véhicule considéré. La caractérisation de l’espace occupé est donc cruciale mais pas suffisante pour les véhicules autonomes puisque le système de contrôle a besoin de trouver l’espace navigable pour assurer une planification sure de trajectoire. En effet, afin de naviguer sur les routes publiques avec d’autres utilisateurs, le véhicule doit aussi suivre les règles de circulation qui sont décrites, par exemple, par des marquages au sol peints sur la chaussée. Dans ce travail, nous nous concentrons sur une approche fondée sur des grilles égocentrées pour modéliser l’environnement. L’objectif est d’obtenir un modèle unifié contenant les informations d’obstacle avec des règles sémantiques de la route. Pour modéliser les informations d’obstacle, l’occupation est assurée par l’interprétation des informations des différents capteurs comme les valeurs des cellules. Pour modéliser la sémantique de l’espace navigable, nous proposons d’introduire la notion de grille de voies qui consiste à intégrer l’information sémantique de voie dans les cellules de la grille. La combinaison de ces deux niveaux d’information donne ainsi un modèle d’environnement plus raffiné. Lors de l’interprétation des données des capteurs en information d’obstacle, il faut manipuler des incertitudes dues à de l’ignorance ou des erreurs. L’ignorance est liée à la perception des nouveaux espaces dans la zone de perception et les erreurs proviennent de mesures bruitées et d’estimations imprécises de la pose. Dans cette recherche, la théorie de la fonction de croyance est adoptée pour faire face aux incertitudes et nous proposons des modèles évidentiels pour différents types de capteurs comme des lidars et des caméras. Les grilles de voie contiennent des informations sémantiques sur les voies provenant des marquages au sol, par exemple. À cette fin, nous proposons d’utiliser une carte a priori qui contient des informations détaillées sur la route comme l’orientation de la route et les marquages des voies. Ces informations sont extraites de la carte en utilisant une estimation de pose fournie par un système de localisation. Dans le modèle proposé, nous intégrons dans les grilles les informations de voie en tenant compte de l’incertitude de la pose estimée. Les algorithmes proposés ont été implémentés et testés sur des données réelles obtenues sur des routes publiques. Nous avons développé des algorithmes Matlab et C ++ avec le logiciel PACPUS développé au laboratoire. / For intelligent vehicle applications, a perception system is a key component to characterize in real-time a model of the driving environment at the surrounding of the vehicle. When modeling the environment, obstacle information is the first feature that has to be managed since collisions can be fatal for the other road users or for the passengers on-board the considered vehicle. Characterization of occupation space is therefore crucial but not sufficient for autonomous vehicles since the control system needs to find the navigable space for safe trajectory planning. Indeed, in order to run on public roads with other users, the vehicle needs to follow the traffic rules which are, for instance, described by markings painted on the carriageway. In this work, we focus on an ego-centered grid-based approach to model the environment. The objective is to include in a unified world model obstacle information with semantic road rules. To model obstacle information, occupancy is handled by interpreting the information of different sensors into the values of the cells. To model the semantic of the navigable space, we propose to introduce the notion of lane grids which consist in integrating semantic lane information into the cells of the grid. The combination of these two levels of information gives a refined environment model. When interpreting sensor data into obstacle information, uncertainty inevitably arises from ignorance and errors. Ignorance is due to the perception of new areas and errors come from noisy measurements and imprecise pose estimation. In this research, the belief function theory is adopted to deal with uncertainties and we propose evidential models for different kind of sensors like lidars and cameras. Lane grids contain semantic lane information coming from lane marking information for instance. To this end, we propose to use a prior map which contains detailed road information including road orientation and lane markings. This information is extracted from the map by using a pose estimate provided by a localization system. In the proposed model, we integrate lane information into the grids by taking into account the uncertainty of the estimated pose. The proposed algorithms have been implemented and tested on real data acquired on public roads. We have developed algorithms in Matlab and C++ using the PACPUS software framework developed at the laboratory.

This diploma thesis deals with the principle of photovoltaic phenomenon and the distribution of photovoltaic systems. It also informs the reader about the possibilities of using the "Green Savings" subsidy within the program "New Green Savings" of the Ministry of the Environment. Last, but not least, it maps the energetic demands of the family house and, on the basis of it, presents the possible design of the photovoltaic system, including the estimation of the economic return.

We study techniques to enforce and provision differentiated service levels in Computational Grid systems. The Grid offers simplified provisioning of peak-capacity for applications with computational requirements beyond local machines and clusters, by sharing resources across organizational boundaries. Current systems have focussed on access control, i.e., managing who is allowed to run applications on remote sites. Very little work has been done on providing differentiated service levels for those applications that are admitted. This leads to a number of problems when scheduling jobs in a fair and efficient way. For example, users with a large number of long-running jobs could starve out others, both intentionally and non-intentionally. We investigate the requirements of High Performance Computing (HPC) applications that run in academic Grid systems, and propose two models of service-level management. Our first model is based on global real-time quota enforcement, where projects are granted resource quota, such as CPU hours, across the Grid by a centralized allocation authority. We implement the SweGrid Accounting System to enforce quota allocated by the Swedish National Allocations Committee in the SweGrid production Grid, which connects six Swedish HPC centers. A flexible authorization policy framework allows provisioning and enforcement of two different service levels across the SweGrid clusters; high-priority and low-priority jobs. As a solution to more fine-grained control over service levels we propose and implement a Grid Market system, using a market-based resource allocator called Tycoon. The conclusion of our research is that although the Grid accounting solution offers better service level enforcement support than state-of-the-art production Grid systems, it turned out to be complex to set the resource price and other policies manually, while ensuring fairness and efficiency of the system. Our Grid Market on the other hand sets the price according to the dynamic demand, and it is further incentive compatible, in that the overall system state remains healthy even in the presence of strategic users. / QC 20101116

Many distributed energy resource (DER) systems are remotely located and are often interfaced at low or medium voltage levels through power electronics converters such as voltage-sourced converters (VSC). Therefore, a weak-grid situation is encountered where the voltage and frequency at the point of DER coupling can experience fluctuations. A power converter designed to operate in normal and strong grid conditions may not perform satisfactorily during such weak and distorted grid conditions. Hence, considering the full dynamics of the system during weak-grid conditions in the design of converter control is indispensable to ensure the stability of the DER and the grid. For instance, the phase-locked loop (PLL) has been identified as a critical component of the VSC controller that can compromise the DER performance during weak-grid conditions. This dissertation investigates and enhances the performances of inverters connected to weak and polluted grids. It primarily presents a novel approach of enhancing the inverter current controller by including the PLL state variables among the entire system state and use them to optimally generate the control input for the VSC. This mitigates the loop interactions between the PLL and other control loops resulting in a mitigation of the oscillations that could cause system instabilities. The procedure is accomplished using the recently developed linear model of the enhanced PLL (EPLL) for single-phase applications and using a model of the three-phase PLL developed in this dissertation. Extensive simulation and experimental results are presented to evaluate and validate the proposed control approaches. Full practical models of all system components are considered for simulation studies. The experimental tests are done on a practical inverter connected to the utility grid. Significant improvement of the inverter performance in weak-grid conditions is confirmed. This dissertation offers a systematic way of integrating and designing the PLL and controller in a VSC to achieve a robust performance in weak-grid conditions.

As the world is increasingly dependent on energy for the economic and social development and China’s Total Net Electricity Generation （TNEG） has remained the highest since 1996 due to its rapid economic growth, it is important to closely examine the operations of China’s electric power market, particularly the State Grid Corporation of China (SGCC) since it is the largest Electric Power Grid Operator (EPGO) in both China and the world. This research has addressed the problem and the urgent needs for the development of a sound framework and methodology for the effective regulation and optimization of the operations and quality management of the SGCC. Based on the critical literature review, the aspects and steps of the solution to the problem have been progressively presented. Firstly, a Country Wealth (CW) curve has been developed to characterize electricity generation in terms of TNEG, with China’s unique position identified. Further, the data has clearly indicated that China’s TNEG has also been closely correlated with the economic growth and the carbon emissions during the 30 years period of 1980-2010. Secondly, compared with the Equilibrium Energy Regulation Model, there are clear deficiencies and problems with the current regulation of China’s electric power market. The improvements in the integration of regulation strategies and the formation of one single effective regulator have been identified and proposed. Thirdly, a uniform regulation structure and framework based on fractal theory and QFD (quality function deployment) has been developed to integrate the existing and future electric power strategies, including smart grid strategy and sustainable development strategy(etc.). Through the use of QFD, the EPGO (SGCC) functions and operations can be prioritized and appropriately designed. Finally, the QFD methodology has been extended to achieve the optimization of quality and service operations given the target cost of the business processes. The methodology can be applied to both business and technical processes of the EPGOs since quality may be interpreted as a total quality involving the needs and expectations of various customers or stakeholders.

Com o crescimento constante da infraestrutura do sistema de distribuição de baixa tensão, tem-se a necessidade de um monitoramento mais preciso das grandezas elétricas no ponto de conexão com os clientes. O impacto da implantação de sistemas smart grids são positivos, visto que para o lado do consumidor o acompanhamento do consumo de forma online permite realizar um melhor planejamento, e para o lado da concessionária, o levantamento de perfil dos clientes e planejamento de demanda, visto que os medidores podem fornecer os dados em tempo real de horários de maior consumo e acompanhamento dos níveis, de forma a adequar conforme os níveis de qualidade de energia definidos pelo módulo 8 PRODIST. Além do acompanhamento, das variáveis e limites, este projeto poderá atuar de forma a auxiliar as companhias elétricas a comparar os pontos de cargas estimadas com o fornecimento para detectar possíveis fraudes no ponto de distribuição. Outro aspecto importante é tornar possível a integração com uma rede de clientes que além de consumidores podem tornar-se pequenas unidades geradoras, alimentando o sistema maior. / With the constant growth of the infrastructure of the low voltage distribution system, there is a need for a more refined monitoring of the electrical quantities in the distribution network. The impact of the implementation of smart grids systems are positive, since for the consumer side the monitoring of consumption in an online way allows to carry out consumption planning, and for the side of the concessionaire, customer profile survey and demand planning, Since the meters can provide the real time data of schedules of greater consumption and monitoring of the levels, in order to adapt according to the levels of quality of energy defined by the module 8 PRODIST. In addition to the monitoring of variables and limits, this project may act in a way that helps utilities compare the estimated load points with the supply to detect possible fraud at the distribution point. Another important aspect is to make it possible to integrate with a network of customers that in addition to consumers can become small generating units, feeding the larger system.

Today many computing resources distributed geographically are idle much of time. The aim of the grid computing is collecting these resources into a single system. It helps to solve problems that are too complex for a single PC. Scheduling plays a critical role in the efficient and effective management of resources to achieve high performance on grid computing environment. Due to the heterogeneity and highly dynamic nature of grid, developing scheduling algorithms for grid computing involves some challenges. In this work, we concentrate on efficient scheduling of distributed tasks on grid. We propose a novel scheduling heuristic for bag-of-tasks applications. The proposed algorithm primarily makes use of history based runtime estimation. The history stores information about the applications whose runtimes and other specific properties are recorded during the previous executions. Scheduling decisions are made according to similarity between the applications. Definition of similarity is an important aspect of this approach, apart from the best resource allocation. The aim of this scheduling algorithm (HISA-History Injected Scheduling Algorithm) is to define and find the similarity, and assign the job to the most suitable resource, making use of the similarity. In our evaluation, we use Grid simulation tool called GridSim. A number of intensive experiments with various simulation settings have been conducted. Based on the experimental results, the effectiveness of HISA scheduling heuristic is studied and compared to the other scheduling algorithms embedded in GridSim. The results show that history injection improves the performance of future job submissions on a grid.