Volume 61 (2010): Issue 4 (July 2010)

This paper presents a DC distribution system which has been supplied by external AC systems as well as local DG units in order to demonstrate an overall solution to power quality issue. In this paper, the proposed operation method is demonstrated by simulation of power transfer between external AC systems, DG units, AC and DC loads. The power flow control in DC distribution system has been achieved by network converters and DG converters. Also, the mathematical model of the network, DG and load converters are obtained by using the average technique, which allows converter systems accurately simulated and control strategies for this converters is achieved. A suitable control strategy for network converters has been proposed that involves DC voltage droop regulator and novel instantaneous power regulation scheme. Also, a novel control technique has been proposed for DG converters. In this paper, a novel control system based on stationary and synchronously rotating reference frame has been proposed for load converters for supplying AC loads connected to the DC bus by balanced voltages. The several case studies have been studied based on proposed methods. The simulation results show that DC distribution systems including DG units can improve the power quality at the point of common coupling (PCC) in the power distribution system or industrial power system.

This paper presents small-signal analysis of isolated as well as interconnected autonomous hybrid distributed generation system for sudden variation in load demand, wind speed and solar radiation. The hybrid systems comprise of different renewable energy resources such as wind, photovoltaic (PV) fuel cell (FC) and diesel engine generator (DEG) along with the energy storage devices such as flywheel energy storage system (FESS) and battery energy storage system (BESS). Further ultracapacitors (UC) as an alternative energy storage element and interconnection of hybrid systems through tie-line is incorporated into the system for improved performance. A comparative assessment of deviation of frequency profile for different hybrid systems in the presence of different storage system combinations is carried out graphically as well as in terms of the performance index (PI), ie integral square error (ISE). Both qualitative and quantitative analysis reflects the improvements of the deviation in frequency profiles in the presence of the ultracapacitors (UC) as compared to other energy storage elements.

Nano-aluminium particles are produced through the wire explosion process in different gas medium. The particles produced by wire explosion process, in helium medium are of smaller size compared to argon/nitrogen medium. The nano aluminium powder on reaction with water forms oxides having bayerite and boehmite structure. It is observed that nano aluminium on reaction with KOH solution at room temperature it forms bayerite. The results of the study were confirmed through Wide Angle X-ray diffraction (WAXD) and by Transmission Electron Microscope (TEM) studies. The reaction of nano aluminium powder with KOH solution/water indicates that the rate of hydrogen generation is high when nano aluminium powder reacts with KOH solution than with water. The rate of hydrogen generation gets reduced drastically when the nano aluminium powder which is exposed to air medium for some period is used for reaction with KOH/water. It is also observed that the rate of hydrogen generation is high with nano size aluminium particles compared with ultrafine particles.

The paper deals with the design of a new digital CNN (Cellular Neural Network) architecture for pattern recognition. The main parameters of the new design were the area consumption of the chip and the speed of calculation in one iteration. The CNN was designed as a digital synchronous circuit. The largest area of the chip belongs to the multiplication unit. In the new architecture we replaced the parallel multiplication unit by a simple AND gate performing serial multiplication. The natural property of this method of multiplication is rounding. We verified some basic properties of the proposed CNN such as edge detection, filling of the edges and noise removing. At the end we compared the designed network with other two CNNs. The new architecture allows to save till 86% gates in comparison with CNN with parallel multipliers.

The paper discusses the possibilities of acquiring and processing the dielectric data in the range of very low frequency (VLF) and also design and construction of an impedance analyzer for measurements in this frequency range. The impedance measurements in the VLF range were used for investigation of the influence of radiation on the cross-linked polyethylene cable dielectric. An expressive β-type relaxation process was found in this type of cable. Most of the dielectric response parameters of the process depend significantly on the absorbed dose of radiation. The analysis of the process parameters showed that the most probable reason of the structural changes in cross-linked polyethylene was additional cross-linking. The results also proved that the impedance measurements in the VLF range could be effectively used in practice for estimation of the absorbed dose in the cross-linked polyethylene cables stressed by radiation.t data only. In order to identify or classify motion, data processing in real time is needed.

In this paper, the modified wavelet based artificial neural network (ANN) is implemented and tested for power signal disturbances. The power signal is decomposed by using modified wavelet transform and the classification is carried by using ANN. Discrete modified wavelet transforms based signal decomposition technique is integrated with the back propagation artificial neural network model is proposed. Varieties of power quality events including voltage sag, swell, momentary interruption, harmonics, transient oscillation and voltage fluctuation are used to test the performance of the proposed approach. The simulation is carried out by using MATLAB software. The simulation results show that the proposed scheme offers superior detection and classification compared to the conventional approaches.

Nanocomposites consist nowadays a major field of research. This paper investigates the interpretational possibilities of two models developed, namely, Tsagaropoulos' model and Tanaka's model. The two models were developed separately and independently from each other. They both consider various layers around the nanoparticles. They both consider well bonded and more loosen layers. Similarities and differences between the two models are pointed out as well as possibilities for further research in order to shed light on some aspects of electrical phenomena in these materials.

There is a lot of redundant data for image processing in an image, in motion picture as well. The more data for image processing we have, the more time is needed for preprocessing it. That is why we need to work with important data only. In order to identify or classify motion, data processing in real time is needed.

In this work we explore the mathematical correspondence between the Langevin equation that describes the motion of a Brownian particle (BP) and the equations for the time evolution of the charge in electric circuits, which are in contact with the thermal bath. The mean quadrate of the fluctuating electric charge in simple circuits and the mean square displacement of the optically trapped BP are governed by the same equations. We solve these equations using an efficient approach that allows us converting the stochastic equations to ordinary differential equations. From the obtained solutions the autocorrelation function of the current and the spectral density of the current fluctuations are found. As distinct from previous works, the inertial and memory effects are taken into account.