Abstract: The incorporation of renewable energy sources for the sustainable electricity production is undertaking a more prominent role in electric power systems. Thus, it will be an indispensable incident that the characteristics of future power networks, their prospective stability for instance, get influenced by the imposed features of sustainable energy sources. One of the distinctive attributes of the sustainable energy sources is exhibiting the stochastic behavior. This paper investigates the impacts of this stochastic behavior on the small disturbance rotor angle stability in the upcoming electric power networks. Considering the various types of renewable energy sources and the vast variety of system configurations, the sensitivity analysis can be an efficient breakthrough towards generalizing the effects of new energy sources on the concept of stability. In this paper, the definition of small disturbance angle stability for future power systems and the iterative-stochastic way of its analysis are presented. Also, the effects of system parameters on this type of stability are described by performing a sensitivity analysis for an electric power test system.
Abstract: Robot manipulators are highly coupled nonlinear
systems, therefore real system and mathematical model of dynamics
used for control system design are not same. Hence, fine-tuning of
controller is always needed. For better tuning fast simulation speed
is desired. Since, Matlab incorporates LAPACK to increase the speed
and complexity of matrix computation, dynamics, forward and
inverse kinematics of PUMA 560 is modeled on Matlab/Simulink in
such a way that all operations are matrix based which give very less
simulation time. This paper compares PID parameter tuning using
Genetic Algorithm, Simulated Annealing, Generalized Pattern Search
(GPS) and Hybrid Search techniques. Controller performances for all
these methods are compared in terms of joint space ITSE and
cartesian space ISE for tracking circular and butterfly trajectories.
Disturbance signal is added to check robustness of controller. GAGPS
hybrid search technique is showing best results for tuning PID
controller parameters in terms of ITSE and robustness.
Abstract: An approach to develop the FPGA of a flexible key
RSA encryption engine that can be used as a standard device in the
secured communication system is presented. The VHDL modeling of
this RSA encryption engine has the unique characteristics of
supporting multiple key sizes, thus can easily be fit into the systems
that require different levels of security. A simple nested loop addition
and subtraction have been used in order to implement the RSA
operation. This has made the processing time faster and used
comparatively smaller amount of space in the FPGA. The hardware
design is targeted on Altera STRATIX II device and determined that
the flexible key RSA encryption engine can be best suited in the
device named EP2S30F484C3. The RSA encryption implementation
has made use of 13,779 units of logic elements and achieved a clock
frequency of 17.77MHz. It has been verified that this RSA
encryption engine can perform 32-bit, 256-bit and 1024-bit
encryption operation in less than 41.585us, 531.515us and 790.61us
respectively.
Abstract: On the basis of the linearized Phillips-Herffron model of a single-machine power system, a novel method for designing unified power flow controller (UPFC) based output feedback controller is presented. The design problem of output feedback controller for UPFC is formulated as an optimization problem according to with the time domain-based objective function which is solved by iteration particle swarm optimization (IPSO) that has a strong ability to find the most optimistic results. To ensure the robustness of the proposed damping controller, the design process takes into account a wide range of operating conditions and system configurations. The simulation results prove the effectiveness and robustness of the proposed method in terms of a high performance power system. The simulation study shows that the designed controller by Iteration PSO performs better than Classical PSO in finding the solution.
Abstract: This article is dedicated to development of
mathematical models for determining the dynamics of
concentration of hazardous substances in urban turbulent
atmosphere. Development of the mathematical models implied
taking into account the time-space variability of the fields of
meteorological items and such turbulent atmosphere data as vortex
nature, nonlinear nature, dissipativity and diffusivity. Knowing the
turbulent airflow velocity is not assumed when developing the
model. However, a simplified model implies that the turbulent and
molecular diffusion ratio is a piecewise constant function that
changes depending on vertical distance from the earth surface.
Thereby an important assumption of vertical stratification of urban
air due to atmospheric accumulation of hazardous substances
emitted by motor vehicles is introduced into the mathematical
model. The suggested simplified non-linear mathematical model of
determining the sought exhaust concentration at a priori unknown
turbulent flow velocity through non-degenerate transformation is
reduced to the model which is subsequently solved analytically.
Abstract: ''Cocktail party problem'' is well known as one of the human auditory abilities. We can recognize the specific sound that we want to listen by this ability even if a lot of undesirable sounds or noises are mixed. Blind source separation (BSS) based on independent component analysis (ICA) is one of the methods by which we can separate only a special signal from their mixed signals with simple hypothesis. In this paper, we propose an online approach for blind source separation using the sliding DFT and the time domain independent component analysis. The proposed method can reduce calculation complexity in comparison with conventional methods, and can be applied to parallel processing by using digital signal processors (DSPs) and so on. We evaluate this method and show its availability.
Abstract: This study investigates the performance of radial basis function networks (RBFN) in forecasting the monthly CO2 emissions of an electric power utility. We also propose a method for input variable selection. This method is based on identifying the general relationships between groups of input candidates and the output. The effect that each input has on the forecasting error is examined by removing all inputs except the variable to be investigated from its group, calculating the networks parameter and performing the forecast. Finally, the new forecasting error is compared with the reference model. Eight input variables were identified as the most relevant, which is significantly less than our reference model with 30 input variables. The simulation results demonstrate that the model with the 8 inputs selected using the method introduced in this study performs as accurate as the reference model, while also being the most parsimonious.
Abstract: Insulation used in transformer is mostly oil pressboard insulation. Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharges (PD) cause insulation degradation and premature failure of insulation. Online monitoring of PDs can reduce the risk of catastrophic failure of transformers. There are different techniques of partial discharge measurement like, electrical, optical, acoustic, opto-acoustic and ultra high frequency (UHF). Being non invasive and non interference prone, acoustic emission technique is advantageous for online PD measurement. Acoustic detection of p.d. is based on the retrieval and analysis of mechanical or pressure signals produced by partial discharges. Partial discharges are classified according to the origin of discharges. Their effects on insulation deterioration are different for different types. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal of laboratory simulated partial discharges in oil pressboard insulation system using three different electrode systems. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using discrete wavelet transform analysis and wavelet packet analysis. Energy distribution in different frequency bands of discrete wavelet decomposed signal and wavelet packet decomposed signal is calculated. These analyses show a distinct feature useful for PD classification. Wavelet packet analysis can sort out any misclassification arising out of DWT in most cases.
Abstract: In many applications, magnetic suspension systems
are required to operate over large variations in air gap. As a result,
the nonlinearities inherent in most types of suspensions have a
significant impact on performance. Specifically, it may be difficult to
design a linear controller which gives satisfactory performance,
stability, and disturbance rejection over a wide range of operating
points. in this paper an optimal controller based on discontinuous
mathematical model of the system for an electromagnetic suspension
system which is applied in magnetic trains has been designed .
Simulations show that the new controller can adapt well to the
variance of suspension mass and gap, and keep its dynamic
performance, thus it is superior to the classic controller.
Abstract: Now-a-days, numbers of simulation software are
being used all over the world to solve Computational Fluid
Dynamics (CFD) related problems. In this present study, a
commercial CFD simulation software namely STAR-CCM+ is
applied to analyze the airflow characteristics inside a 2.5" hard
disk drive. Each step of the software is described adequately to
obtain the output and the data are verified with the theories to
justify the robustness of the simulation outcome. This study
gives an insight about the accuracy level of the CFD
simulation software to compute CFD related problems
although it largely depends upon the computer speed. Also
this study will open avenues for further research.
Abstract: Having done in this study, air-conditioning
automation for patisserie shopwindow was designed. In the cooling
sector it is quite important to cooling up the air temperature in the
shopwindow within short time interval. Otherwise the patisseries
inside of the shopwindow will be spoilt in a few days. Additionally
the humidity is other important parameter for the patisseries kept in
shopwindow. It must be raised up to desired level in a quite short
time. Traditional patisserie shopwindows only allow controlling
temperature manually. There is no humidity control and humidity is
supplied by fans that are directed to the water at the bottom of the
shopwindows. In this study, humidity and temperature sensors
(SHT11), PIC, AC motor controller, DC motor controller, ultrasonic
nebulizer and other electronic circuit members were used to simulate
air conditioning automation for patisserie shopwindow in proteus
software package. The simulation results showed that temperature
and humidity values are adjusted in desired time duration by openloop
control technique. Outer and inner temperature and humidity
values were used for control mechanism.
Abstract: This paper presents the use of the predictive fuzzy logic controller (PFLC) applied to attitude control system for agile micro-satellite. In order to reduce the effect of unpredictable time delays and large uncertainties, the algorithm employs predictive control to predict the attitude of the satellite. Comparison of the PFLC and conventional fuzzy logic controller (FLC) is presented to evaluate the performance of the control system during attitude maneuver. The two proposed models have been analyzed with the same level of noise and external disturbances. Simulation results demonstrated the feasibility and advantages of the PFLC on the attitude determination and control system (ADCS) of agile satellite.
Abstract: The purpose of this paper is to present a Dynamic
Time Warping technique which reduces significantly the data
processing time and memory size of multi-dimensional time series
sampled by the biometric smart pen device BiSP. The acquisition
device is a novel ballpoint pen equipped with a diversity of sensors
for monitoring the kinematics and dynamics of handwriting
movement. The DTW algorithm has been applied for time series
analysis of five different sensor channels providing pressure,
acceleration and tilt data of the pen generated during handwriting on
a paper pad. But the standard DTW has processing time and memory
space problems which limit its practical use for online handwriting
recognition. To face with this problem the DTW has been applied to
the sum of the five sensor signals after an adequate down-sampling
of the data. Preliminary results have shown that processing time and
memory size could significantly be reduced without deterioration of
performance in single character and word recognition. Further
excellent accuracy in recognition was achieved which is mainly due
to the reduced dynamic time warping RDTW technique and a novel
pen device BiSP.
Abstract: The High Voltage (HV) transmission mains into the community necessitate earthing design to ensure safety compliance of the system. Concrete poles are widely used within HV transmission mains; which could have an impact on the earth grid impedance and input impedance of the system from the fault point of view. This paper provides information on concrete pole earthing to enhance the split factor of the system; further, it discusses the deployment of concrete structures in high soil resistivity area to reduce the earth grid system of the plant. This paper introduces the cut off soil resistivity SC ρ when replacing timber poles with concrete ones.
Abstract: The Principal component regression (PCR) is a
combination of principal component analysis (PCA) and multiple linear regression (MLR). The objective of this paper is to revise the
use of PCR in shortwave near infrared (SWNIR) (750-1000nm) spectral analysis. The idea of PCR was explained mathematically and
implemented in the non-destructive assessment of the soluble solid
content (SSC) of pineapple based on SWNIR spectral data. PCR achieved satisfactory results in this application with root mean
squared error of calibration (RMSEC) of 0.7611 Brix°, coefficient of determination (R2) of 0.5865 and root mean squared error of crossvalidation
(RMSECV) of 0.8323 Brix° with principal components
(PCs) of 14.
Abstract: In this paper, an approach for finding optimized
layouts for connecting PV units delivering maximum array output
power is suggested. The approach is based on considering the
different varying parameters of PV units that might be extracted from
a general two-diode model. These are mainly, solar irradiation,
reverse saturation currents, ideality factors, series and shunt
resistances in addition to operating temperature. The approach has
been tested on 19 possible 2×3 configurations and allowed to
determine the optimized configurations as well as examine the effects
of the different units- parameters on the maximum output power.
Thus, using this approach, standard arrays with n×m units can be
configured for maximum generated power and allows designing PV
based systems having reduced surfaces to fit specific required power,
as it is the case for solar cars and other mobile systems.
Abstract: This paper introduces an adaptive control scheme to synchronize two identical Chua's systems. Introductory part of the paper is presented in the first part of the paper and then in the second part, a new theorem is proposed based on which an adaptive control scheme is developed to synchronize two identical modified Chua's circuit. Finally, numerical simulations are included to verify the effectiveness of the proposed control method.
Abstract: Diagnostic goal of transformers in service is to detect the winding or the core in fault. Transformers are valuable equipment which makes a major contribution to the supply security of a power system. Consequently, it is of great importance to minimize the frequency and duration of unwanted outages of power transformers. So, Frequency Response Analysis (FRA) is found to be a useful tool for reliable detection of incipient mechanical fault in a transformer, by finding winding or core defects. The authors propose as first part of this article, the coupled circuits method, because, it gives most possible exhaustive modelling of transformers. And as second part of this work, the application of FRA in low frequency in order to improve and simplify the response reading. This study can be useful as a base data for the other transformers of the same categories intended for distribution grid.
Abstract: One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. In this paper, we consider a form of dynamic hand gestures that are characterized by total movement of the hand (arm) in space. For these types of gestures, the shape of the hand (palm) during gesturing does not bear any significance. In our work, we propose a model-based method for tracking hand motion in space, thereby estimating the hand motion trajectory. We employ the dynamic time warping (DTW) algorithm for time alignment and normalization of spatio-temporal variations that exist among samples belonging to the same gesture class. During training, one template trajectory and one prototype feature vector are generated for every gesture class. Features used in our work include some static and dynamic motion trajectory features. Recognition is accomplished in two stages. In the first stage, all unlikely gesture classes are eliminated by comparing the input gesture trajectory to all the template trajectories. In the next stage, feature vector extracted from the input gesture is compared to all the class prototype feature vectors using a distance classifier. Experimental results demonstrate that our proposed trajectory estimator and classifier is suitable for Human Computer Interaction (HCI) platform.
Abstract: In this paper, we propose a new modular approach called neuroglial consisting of two neural networks slow and fast which emulates a biological reality recently discovered. The implementation is based on complex multi-time scale systems; validation is performed on the model of the asynchronous machine. We applied the geometric approach based on the Gerschgorin circles for the decoupling of fast and slow variables, and the method of singular perturbations for the development of reductions models.
This new architecture allows for smaller networks with less complexity and better performance in terms of mean square error and convergence than the single network model.