Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

Localization Algorithm Performance in Ultra Low Power Active RFID Based Patient Tracking

Indoor personnel localization research has generated a range of potential techniques and algorithms. However, these typically do not account for the influence of the user's body upon the radio channel. In this paper an active RFID based patient tracking system is demonstrated and three localization algorithms are used to estimate the location of a user within a modern office building. It is shown that disregarding body effects reduces the accuracy of the algorithms' location estimates and that body shadowing effects create a systematic position error that estimates the user's location as closer to the RFID reader that the active tag has line of sight to.

À l’intérieur des murs : comprendre la violence en milieu carcéral à partir du point de vue d’hommes incarcérés à l’Unité spéciale de détention

L’étude qui nous concerne vise à mieux comprendre la violence en milieu carcéral. C’est à l’aide d’entrevues menées auprès de treize hommes incarcérés à l’Unité spéciale de détention, une unité canadienne spécifiquement conçue pour loger des personnes qui ont fait usage de violence intra murale ou sont soupçonné de l’avoir fait, que nous avons tenté d’atteindre l’objectif principal de ce projet. Plus spécifiquement, le point de vue des participants a été recueilli sur l’incarcération, sur les moyens utilisés afin de s’accoutumer aux défis de l’enfermement ainsi que la manière dont les individus justifient l’usage de violence dans ce contexte. Les résultats de nos analyses suggèrent que le milieu carcéral est un monde hostile et imprévisible où les individus se perçoivent constamment vulnérables à de multiples formes d’agression. Placés en hyper vigilance et orientés vers la survie, les détenus font usage de diverses stratégies d’adaptation afin de répondre aux situations difficiles qu’ils rencontrent en contexte de perte de liberté. La violence représente donc un des moyens dont disposent les individus pour survivre à l’intérieur des murs. Les diverses formes d’adaptation violente rencontrées en milieu carcéral peuvent ainsi informer sur les enjeux de survie présents dans un milieu et donc, du risque de violence ou de victimisation dans ce milieu, que cette violence soit interpersonnelle, collective, auto dirigée, axée sur la fuite ou contre les biens. Puisque l’usage de violence par une personne engendre une possibilité accrue de choisir la violence pour une autre, et ce, avec les conséquences qui s’en suivent pour les détenus et les membres du personnel, nous avons tenté d’identifier et de comprendre les diverses logiques d’action qui motivent le choix d’avoir recours à la violence dans les institutions carcérales. Or, il appert que certaines caractéristiques des individus tendent à faire augmenter le risque pour une personne d’avoir recours à la violence carcérale. De même, il semble que certaines institutions sont davantage propices à l’usage de violence que d’autres. De surcroît, des éléments appartenant aux individus et au milieu en interrelation semblent favoriser la possibilité qu’un condamné fasse usage de violence intra murale. Ainsi, le recours à la violence est davantage probable si elle est légitimée par les individus et le milieu, si le niveau d’adhésion aux valeurs des sous-cultures délinquantes des individus est élevé et si la philosophie du milieu en favorise le maintien, si des groupes influents en quête de contrôle et de pouvoir sont présents dans le milieu et qu’un individu désire y être affilié, s’il y a présence de marchés illicites comme réponse à la privation et qu’un individu y participe ou encore, si le milieu et l’individu sont pris dans l’engrenage d’un climat de survie. Par conséquent, une réflexion concernant le sentiment de sécurité préoccupant les reclus, sentiment qui est un besoin fondamental chez tous les êtres humains, un retour sur les divers modèles théoriques en fonction des données que nous avons obtenues ainsi qu’une réflexion portant sur les moyens dont disposent les individus et le milieu afin de diminuer les possibilités que la violence soit utilisée, ont été amorcées en conclusion.

Stereo-Based Head Pose Tracking Using Iterative Closest Point and Normal Flow Constraint

In this text, we present two stereo-based head tracking techniques along with a fast 3D model acquisition system. The first tracking technique is a robust implementation of stereo-based head tracking designed for interactive environments with uncontrolled lighting. We integrate fast face detection and drift reduction algorithms with a gradient-based stereo rigid motion tracking technique. Our system can automatically segment and track a user's head under large rotation and illumination variations. Precision and usability of this approach are compared with previous tracking methods for cursor control and target selection in both desktop and interactive room environments. The second tracking technique is designed to improve the robustness of head pose tracking for fast movements. Our iterative hybrid tracker combines constraints from the ICP (Iterative Closest Point) algorithm and normal flow constraint. This new technique is more precise for small movements and noisy depth than ICP alone, and more robust for large movements than the normal flow constraint alone. We present experiments which test the accuracy of our approach on sequences of real and synthetic stereo images. The 3D model acquisition system we present quickly aligns intensity and depth images, and reconstructs a textured 3D mesh. 3D views are registered with shape alignment based on our iterative hybrid tracker. We reconstruct the 3D model using a new Cubic Ray Projection merging algorithm which takes advantage of a novel data structure: the linked voxel space. We present experiments to test the accuracy of our approach on 3D face modelling using real-time stereo images.

Decoding the canada's foreing and security policy: tracking the strategic and ethicliberal approaches of a middle power's behavior

The article attempts to explain the main paradox faced by Canada at formulating its foreign policy on international security. Explained in economic and political terms, this paradox consists in the contradiction between the Canadian ability to achieve its strategic goals, serving to its own national interest and its dependence on the United States. The first section outlines three representative examples to evaluate this paradox: the Canada’s position in North American security regime, the US-Canada economic security relations, and the universe of possibilities for action of Canada as a middle power. The second section suggests that liberal agenda, especially concerning to ethical issues, has been established by this country to minimize this paradox. By pursing this agenda, Canada is able to reaffirm its national identity and therefore its independence on the United States. The third section evaluates both the explained paradox and the reaffirmation of Canadian identity during the Jean Chrétien (1993-2003), Paul Martin (2003-2006) and Stephen Harper’s (2006) governments.

Feature-point detection using distance transforms: Application to tracking tropical convective complexes

The identification, tracking, and statistical analysis of tropical convective complexes using satellite imagery is explored in the context of identifying feature points suitable for tracking. The feature points are determined based on the shape of complexes using the distance transform technique. This approach has been applied to the determination feature points for tropical convective complexes identified in a time series of global cloud imagery. The feature points are used to track the complexes, and from the tracks statistical diagnostic fields are computed. This approach allows the nature and distribution of organized deep convection in the Tropics to be explored.

Line-pack management for producing electric power on peak periods

The distribution of natural gas is carried out by means of long ducts and intermediate compression stations to compensate the pressure drops due to friction. The natural gas compressors are usually driven by an electric motor or a gas turbine system, offering possibilities for energy management, one of these consisting in generating energy for use in-plant or to commercialize as independent power producer. It can be done by matching the natural gas demand, at the minimum pressure allowed in the reception point, and the storage capacity of the feed duct with the maximum compressor capacity, for storing the natural gas at the maximum permitted pressure. This allows the gas turbine to drive an electric generator during the time in which the decreasing pressure in duct is above the minimum acceptable by the sink unit. In this paper, a line-pack management analysis is done for an existing compression station considering its actual demand curve for determining the economic feasibility of maintaining the gas turbine system driver generating electricity in a peak and off-peak tariff structure. The potential of cost reduction from the point of view of energy resources (natural gas and electric costs) is also analyzed. (C) 2010 Elsevier Ltd. All rights reserved.

Security constrained optimal active power flow via network model and interior point method

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An unequivocal normalization-based paradigm to solve dynamic economic and emission active-reactive OPF (optimal power flow)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Interior-exterior point method with global convergence strategy for solving the reactive optimal power flow problem

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Partial discharge in power distribution electrical systems: pulse propagation models and detection optimization

Investigation on impulsive signals, originated from Partial Discharge (PD) phenomena, represents an effective tool for preventing electric failures in High Voltage (HV) and Medium Voltage (MV) systems. The determination of both sensors and instruments bandwidths is the key to achieve meaningful measurements, that is to say, obtaining the maximum Signal-To-Noise Ratio (SNR). The optimum bandwidth depends on the characteristics of the system under test, which can be often represented as a transmission line characterized by signal attenuation and dispersion phenomena. It is therefore necessary to develop both models and techniques which can characterize accurately the PD propagation mechanisms in each system and work out the frequency characteristics of the PD pulses at detection point, in order to design proper sensors able to carry out PD measurement on-line with maximum SNR. Analytical models will be devised in order to predict PD propagation in MV apparatuses. Furthermore, simulation tools will be used where complex geometries make analytical models to be unfeasible. In particular, PD propagation in MV cables, transformers and switchgears will be investigated, taking into account both irradiated and conducted signals associated to PD events, in order to design proper sensors.

USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS

Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

Tracking individual membrane proteins and their biochemistry: The power of direct observation

The advent of single molecule fluorescence microscopy has allowed experimental molecular biophysics and biochemistry to transcend traditional ensemble measurements, where the behavior of individual proteins could not be precisely sampled. The recent explosion in popularity of new super-resolution and super-localization techniques coupled with technical advances in optical designs and fast highly sensitive cameras with single photon sensitivity and millisecond time resolution have made it possible to track key motions, reactions, and interactions of individual proteins with high temporal resolution and spatial resolution well beyond the diffraction limit. Within the purview of membrane proteins and ligand gated ion channels (LGICs), these outstanding advances in single molecule microscopy allow for the direct observation of discrete biochemical states and their fluctuation dynamics. Such observations are fundamentally important for understanding molecular-level mechanisms governing these systems. Examples reviewed here include the effects of allostery on the stoichiometry of ligand binding in the presence of fluorescent ligands; the observation of subdomain partitioning of membrane proteins due to microenvironment effects; and the use of single particle tracking experiments to elucidate characteristics of membrane protein diffusion and the direct measurement of thermodynamic properties, which govern the free energy landscape of protein dimerization. The review of such characteristic topics represents a snapshot of efforts to push the boundaries of fluorescence microscopy of membrane proteins to the absolute limit.

Ground-penetrating radar (GPR) point measurements of ice thickness in Austria

Glacier thickness is an important factor in the course of glacier retreat in a warming climate. Thiese study data presents the results (point data) of GPR surveys on 66 Austrian mountain glaciers carried out between 1995 and 2014. The glacier areas range from 0.001 to 18.4 km**2, and their ice thickness has been surveyed with an average density of 36 points/km**2 . The glacier areas and surface elevations refer to the second Austrian glacier inventory (mapped between 1996 and 2002). According to the glacier state recorded in the second glacier inventory, the 64 glaciers cover an area of 223.3±3.6 km**3. Maps of glacier thickness have been calculated by Fischer and Kuhn (2013) with a mean thickness of 50±3 m and contain an glacier volume of 11.9±1.1 km**3. The mean maximum ice thickness is 119±5 m. The ice thickness measurements have been carried out with the transmitter of Narod and Clarke (1994) combined with restively loaded dipole antennas (Wu and King, 1965; Rose and Vickers, 1974) at central wavelengths of 6.5 (30 m antenna length) and 4.0 MHz (50 m antenna length). The signal was recorded trace by trace with an oscilloscope. 168 m/µs as used by Haeberli et al. (1982), Bauder (2001), and Narod and Clarke (1994), the signal velocity in air is assumed to be 300 m/µs. Details on the method can be are found in Fischer and Kuhn (2013), as well as Span et al. (2005) and Fischer et al. (2007).