Operation and control of a DVR in the presence of interharmonics

The paper discusses the operating principles and control characteristics of a dynamic voltage restorer (DVR). It is assumed that the source voltages contain interharmonic components in addition to fundamental components. The main aim of the DVR is to produce a set of clean balanced sinusoidal voltages across the load terminals irrespective of unbalance, distortion and voltage sag/swell in the supply voltage. An algorithm has been discussed for extracting fundamental phasor sequence components from the samples of three-phase voltages or current waveforms having integer harmonics and interharmonics. The DVR operation based on extracted components is demonstrated. The switching signal is generated using a deadbeat controller. It has been shown that the DVR is able to compensate these interharmonic components such that the load voltages are perfectly regulated. The DVR operation under deep voltage sag is also discussed. The proposed DVR operation is verified through the computer simulation studies using the MATLAB software package.

Modeling, stability analysis and control of microgrid

With the increase in the level of global warming, renewable energy based distributed generators (DGs) will increasingly play a dominant role in electricity production. Distributed generation based on solar energy (photovoltaic and solar thermal), wind, biomass, mini-hydro along with use of fuel cells and micro turbines will gain considerable momentum in the near future. A microgrid consists of clusters of load and distributed generators that operate as a single controllable system. The interconnection of the DG to the utility/grid through power electronic converters has raised concern about safe operation and protection of the equipments. Many innovative control techniques have been used for enhancing the stability of microgrid as for proper load sharing. The most common method is the use of droop characteristics for decentralized load sharing. Parallel converters have been controlled to deliver desired real power (and reactive power) to the system. Local signals are used as feedback to control converters, since in a real system, the distance between the converters may make the inter-communication impractical. The real and reactive power sharing can be achieved by controlling two independent quantities, frequency and fundamental voltage magnitude. In this thesis, an angle droop controller is proposed to share power amongst converter interfaced DGs in a microgrid. As the angle of the output voltage can be changed instantaneously in a voltage source converter (VSC), controlling the angle to control the real power is always beneficial for quick attainment of steady state. Thus in converter based DGs, load sharing can be performed by drooping the converter output voltage magnitude and its angle instead of frequency. The angle control results in much lesser frequency variation compared to that with frequency droop. An enhanced frequency droop controller is proposed for better dynamic response and smooth transition between grid connected and islanded modes of operation. A modular controller structure with modified control loop is proposed for better load sharing between the parallel connected converters in a distributed generation system. Moreover, a method for smooth transition between grid connected and islanded modes is proposed. Power quality enhanced operation of a microgrid in presence of unbalanced and non-linear loads is also addressed in which the DGs act as compensators. The compensator can perform load balancing, harmonic compensation and reactive power control while supplying real power to the grid A frequency and voltage isolation technique between microgrid and utility is proposed by using a back-to-back converter. As utility and microgrid are totally isolated, the voltage or frequency fluctuations in the utility side do not affect the microgrid loads and vice versa. Another advantage of this scheme is that a bidirectional regulated power flow can be achieved by the back-to-back converter structure. For accurate load sharing, the droop gains have to be high, which has the potential of making the system unstable. Therefore the choice of droop gains is often a tradeoff between power sharing and stability. To improve this situation, a supplementary droop controller is proposed. A small signal model of the system is developed, based on which the parameters of the supplementary controller are designed. Two methods are proposed for load sharing in an autonomous microgrid in rural network with high R/X ratio lines. The first method proposes power sharing without any communication between the DGs. The feedback quantities and the gain matrixes are transformed with a transformation matrix based on the line R/X ratio. The second method involves minimal communication among the DGs. The converter output voltage angle reference is modified based on the active and reactive power flow in the line connected at point of common coupling (PCC). It is shown that a more economical and proper power sharing solution is possible with the web based communication of the power flow quantities. All the proposed methods are verified through PSCAD simulations. The converters are modeled with IGBT switches and anti parallel diodes with associated snubber circuits. All the rotating machines are modeled in detail including their dynamics.

Identification and control of induction machines using artificial neural networks

The use of artificial neural networks (ANNs) to identify and control induction machines is proposed. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics, and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Both systems are inherently adaptive as well as self-commissioning. The current controller is a completely general nonlinear controller which can be used together with any drive algorithm. Various advantages of these control schemes over conventional schemes are cited, and the combined speed and current control scheme is compared with the standard vector control scheme

Identification and control of induction machines using artificial neural networks

This paper proposes the use of artificial neural networks (ANNs) to identify and control an induction machine. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics; and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Various advantages of these control schemes over other conventional schemes are cited and the performance of the combined speed and current control scheme is compared with that of the standard vector control scheme

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

Operation and control of hybrid microgrid with angle droop controller

This paper compares the performance of two droop control schemes in a hybrid microgrid. With presence of both converter interfaced and inertial sources, the droop controller share power in a decentralized fashion. Both the droop controllers facilitate reactive power sharing based on voltage droop. However in frequency droop control, the real power sharing depends on the frequency, while in angle droop control, it depends on output voltage angle. For converter interfaced sources this reference voltage is tracked while for inertial DG, reference power for the prime mover is calculated from the reference angle with the proposed angle control scheme. This coordinated control scheme shows significant improvement in system performance. The comparison with the conventional frequency droop shows that the angle control scheme shares power with much lower frequency deviation. This is a significant improvement particularly in a frequent load changing scenario.

Ability of silver-impregnated contact lenses to control microbial growth and colonisation

Purpose: To examine the ability of silver nano-particles to prevent the growth of Pseudomonas aeruginosa and Staphylococcus aureus in solution or when adsorbed into contact lenses. To examine the ability of silver nano-particles to prevent the growth of Acanthamoeba castellanii. ----- ----- Methods: Etafilcon A lenses were soaked in various concentrations of silver nano-particles. Bacterial cells were then exposed to these lenses, and numbers of viable cells on lens surface or in solution compared to etafilcon A lenses not soaked in silver. Acanthamoeba trophozoites were exposed to silver nano-particles and their ability to form tracks was examined. ----- ----- Results: Silver nano-particle containing lenses reduced bacterial viability and adhesion. There was a dose-dependent response curve, with 10 ppm or 20 ppm silver showing > 5 log reduction in bacterial viability in solution or on the lens surface. For Acanthamoeba, 20 ppm silver reduced the ability to form tracks by approximately 1 log unit. ----- ----- Conclusions: Silver nanoparticles are effective antimicrobial agents, and can reduce the ability of viable bacterial cells to colonise contact lenses once incorporated into the lens.----- ----- Resumen: Objetivos: Examinar la capacidad de las nanopartículas de plata para prevenir el crecimiento de Pseudomonas aeruginosa y Staphylococcus aureus en soluciones para lentes de contacto o cuando éstas las adsorben. Examinar la capacidad de las nanopartículas de plata para prevenir el crecimiento de Acanthamoeba castellanii.----- ----- Métodos: Se sumergieron lentes etafilcon A en diversas concentraciones de nanopartículas de plata. Las células bacterianas fueron posteriormente expuestas a dichas lentes, y se compararon cantidades de células viables en la superficie de la lente o en la solución con las presentes en lentes etafilcon A que no habían sido sumergidas en plata. Trofozoítos de Acanthamoeba fueron expuestos a nanopartículas de plata y se examinó su capacidad para formar quistes.----- ----- Resultados: Las lentes que contienen nanopartículas de plata redujeron la viabilidad bacteriana y la adhesión. Hubo una curva de respuesta dependiente de la dosis, en la que 10 ppm o 20 ppm de plata mostró una reducción logarítmica > 5 en la viabilidad bacteriana tanto en la solución como en la superficie de la lente. Para Acanthamoeba, 20 ppm de plata redujeron la capacidad de formar quistes en aproximadamente 1 unidad logarítmica.----- ----- Conclusiones: Las nanopartículas de plata son agentes antimicrobianos eficaces y pueden reducir la capacidad de células bacterianas viables para colonizar las lentes de contacto una vez que se han incorporado en la lente.

Effects of reduced contrast on the perception and control of speed when driving

Misperception of speed under low-contrast conditions has been identified as a possible contributor to motor vehicle crashes in fog. To test this hypothesis, we investigated the effects of reduced contrast on drivers’ perception and control of speed while driving under real-world conditions. Fourteen participants drove around a 2.85 km closed road course under three visual conditions: clear view and with two levels of reduced contrast created by diffusing filters on the windscreen and side windows. Three dependent measures were obtained, without view of the speedometer, on separate laps around the road course: verbal estimates of speed; adjustment of speed to instructed levels (25 to 70 km h-1); and estimation of minimum stopping distance. The results showed that drivers traveled more slowly under low-contrast conditions. Reduced contrast had little or no effect on either verbal judgments of speed or estimates of minimum stopping distance. Speed adjustments were significantly slower under low-contrast than clear conditions, indicating that, contrary to studies of object motion, drivers perceived themselves to be traveling faster under conditions of reduced contrast. Under real-world driving conditions, drivers’ ability to perceive and control their speed was not adversely affected by large variations in the contrast of their surroundings. These findings suggest that perceptions of self-motion and object motion involve neural processes that are differentially affected by variations in stimulus contrast as encountered in fog.