The Modares Journal of Electrical Engineering
Year:2010 | Volume:10 | Issue:3|Papers Count:8

The new competitive environment changes the paradigm of power system operation. In the transmission area, open access process provides fair accessibility for all market participants. Congestion management is one of the most important side effects of this new process. This paper proposes a new approach for congestion management which is based on both active and reactive re-dispatch of the network critical buses. The critical buses including both generation and interruptible loads, are determined through a sensitivity analysis. Due to the important effects of the market pricing rules on the congestion cost and its allocation, two types of these rules, namely uniform and pay as bid pricing are investigated in the paper. The numerical results of case studies show the effectiveness of the proposed approach.

In this paper, genetic programming is applied for quality improvement of noisy speech signal. Therefore, a system including both spectral subtraction and genetic programming is implemented for speech enhancement. In the proposed method, first noise is reduced by spectral subtraction. In the next step, genetic programming trees are trained for more enhancement of noisy signal by mapping the signal obtained by spectral subtraction to clean data. The proposed hybrid method improves signal to noise ratio about 2 to 6.5 dB. Comparison of genetic programming, multi-layer perceptron neural network, spectral subtraction, and the proposed hybrid method for speech enhancement indicates that the combination of spectral subtraction and genetic programming presents much better quality for enhanced signal compared to the other methods studied in this paper.

We compare performance of adaptive schemes which are based on radial-basis functions and Kalman filters for fast extraction of auditory evoked potentials. Moreover, we propose a new method based on evoked potential modeling in the Kalman filter framework, which can improve the accuracy compared to the existing methods. Simulation results show that adaptive schemes and the Kalman method are not significantly different in reducing the number of trials needed for accurate extract on of auditory evoked potentials, and that the proposed method significantly improves the extraction accuracy of the evoked potentials even when the number of trials is small.

This paper introduces a novel approach to improve performance of speech recognition systems using a combination of features obtained from speech reconstructed phase space (RPS) and frequency domain analysis. By choosing an appropriate value for the dimension, reconstructed phase space is assured to be topologically equivalent to the dynamics of the speech production system, and could therefore include information that may be absent in analysis approaches based on linear methods. Also, complicated systems such as speech production system can present cyclic and oscillatory patterns and Poincare sections could be used as an effective tool in analysis of such trajectories. In this research, a statistical modeling approach based on Gaussian Mixture models (GMM) was applied to the Poincare sections of speech RPS. The final feature set is obtained from a feature selection stage among parameters of GMM model and the usual Mel Frequency Cepstral coefficients (MFCC). An HMM-based speech recognition system and the TIMIT speech database are used to evaluate performance of the proposed feature extraction system for isolated and continuous speech recognition. Experiments represent about 5.7% absolute isolated phoneme recognition accuracy improvements in isolated phoneme recognition performance. The new approach is shown to be a viable and effective alternative to traditional feature extraction methods, particularly for signals such as speech with strong nonlinear characteristics.

Antenna structures with low side lobe levels are normally the main goal during antenna design. In this paper, a new method for reduction of radiation pattern side lobe level in phased array antenna with uniform and non-uniform weighting is presented. In this method, by changing the array elements weight or adding several elements, such as SLC technique, the pattern with low side lobe level can be achieved. According to the design, in an array with uniform weighting, the value of SLL in third side lobe to next more than -10 dB can be reduced so that main beam width changes less than 3% and variations of gain is negligible. Since in applications non - uniform weighting is used, here a new method for side lobe level reduction in phased array antennas radiation pattern by Taylor weighting is presented. In this method, by use of uniform weighting results, the weight vector of array modify so that side lobe reduction in resultant pattern is perceptible. In this method, the value of SLL in third side lobe to next, ratio to primary Taylor weighting can be reduced so that main beam width approximately 1-2% changes and variation of array gain is negligible. Since in phased array antennas, location of main lobe can be set electronically by applying proper phase in arbitrary angle, performance of this method in pattern scanning is considered and shown in both ways that this method is independent of the main lobe location.

Although in recent two decades, the concept of Dielectric Barrier Discharges (DBDs) have been developed in ozone production well, air pollution control, plasma screens and control of chemical, and biological and medical processes, employment of this concept for high voltage applications to improve insulation performance as an alternative to the pressurized gas-insulated systems (GIS) utilizing SF6, is still in research phase. In this paper, the enhancement of insulation performance using DBD and with increasing charge densities on the barrier surfaces in uniform electric filed has been statically modeled. This means that the dynamics of the development of space charges and the manner they sit on the barrier surfaces are ignored and only DBD concepts considering different amounts of surface charges on the barrier surfaces are evaluated. Also the influence of various parameters, such as permeability of the dielectric material, its thickness, and length of air gap, on the enhancement of insulation performance is evaluated. Then an algorithm for the formation of space charges, settling on the barrier surfaces and electric filed modification in the air gap for three types of voltage including DC, AC and lightning impulse, is simulated and evaluated using MATLAB. In this modeling, dielectrics are considered as non-insulating with some electrical conductivity.

Condition monitoring of BLDC motors due to their important applications is gaining more and more significance. Rotor eccentricity is one of the most important sources of faults in these motors. Up to now, detection methods of this fault under nonstationary conditions are limited to complicated and time-consuming methods using wavelets and Cohen class algorithms which are difficult to implement and need heavy computations to run. In this paper a novel method based on the modified Motor Current Signature Analysis method is proposed to detect the rotor eccentricity fault of BLDC motor operating under varying speed conditions. Stator current of healthy and faulty motor which are modeled by the Finite Element Method are simulated. By changing the representation of stator current from time basis to angle basis, the current signal will become stationary. Thus there is no need for methods using time-frequency analysis. Afterwards the Order Analysis Method is applied to the simulated healthy and faulty angle-based current signal and the results are compared with each other. Finally, the fault is detected by this comparison.