IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY TRANSACTION B- ENGINEERING
Year:2007 | Volume:31 | Issue:B3|Papers Count:8

Employing an admittance representation in the form of a black box model approximated by rational functions for linear power system components or network equivalents to be included in electromagnetic transient studies is a well-known method which improves calculation efficiency. All of the methods that have been proposed to solve the rational approximation problem have made efforts to overcome the problem of preserving the passivity of the final model. Passivity is a vital property, since a non-passive model may lead to an unstable transient simulation in the time domain. In this paper a post-processing technique for passivity enforcement through an iterative process for the detection and compensation of passivity violations is presented. The passivity violation regions are detected via a purely algebraic approach based on the existence of purely imaginary eigenvalues in the Hamiltonian matrix. Then a compensation technique via the perturbation of residues of the rational function is applied. Some examples are used to illustrate the characteristics of the proposed technique in terms of accuracy and efficiency by comparison with the Quadratic Programming (QP) method.

Voltage security and congestion management are crucial issues in power systems, especially under heavily loaded conditions. In the new scheme of electricity restructuring, voltage security problems become even more serious. Due to the increase in stability margins, FACTS devices are the best option to mitigate voltage instability by reactive power management. The main purpose of this paper is to identify the optimal location and capacity of the Static Synchronous Compensator (STATCOM) to enhance voltage security and identify the capacity of a properly placed IPFC to manage transmission network congestion simultaneously. Artificial intelligence is implemented as a heuristic technique to this complicated constrained optimization problem. The proposed method demonstrates the improvement of the voltage security margin, as well as solving congestion management problems. Significant results through a modified IEEE 14-bus case study show the effectiveness of the proposed algorithm.

This paper describes a procedure that uses particle swarm optimization (PSO) combined with the simulated annealing (SA) to analyze the bidding strategy of Generating Companies (Gencos) in an electricity market where they have incomplete information about their opponents.In the proposed methodology, Gencos prepare their strategic bids according to the Supply Function Equilibrium (SFE) model and they change their bidding strategies until Nash equilibrium points are obtained. Nash equilibrium points constitute a central solution concept in the game theory and are computed with solving a global optimization problem. In this paper a new computational intelligence technique is introduced that can be used to solve the Nash optimization problem. This new procedure, namely PSO-SA is based on the PSO algorithm and SA method. SA method is used to avoid becoming trapped in local minima or maxima and improve the velocity’s function of particles. The performance of the PSO-SA procedure is compared with the results of other computational intelligence techniques such as PSO, Genetic Algorithm (GA), and a mathematical method (GAMS/DICOPT).

This paper presents the design of a complete self-tunable method for detecting the rotor position at low, high, and standstill speeds under different motor power ratings in a switched reluctance motor (SRM). In this method, high frequency diagnostic pulses with different pulse widths are applied to the three-stator pole windings and then the proper size pulse width is determined for that particular motor at standstill. At low speeds, the rotor positions are then sensed with the selected pulse width by applying the pulse to the un-energized phase winding while sensing the rotor position from the resulting phase winding current magnitude. At high speeds) beyond motor rated speed) the rotor position is detected by the current magnitude produced by the injected pulse and at the same time advancing the phase on time according to the motor speed. The designed controller is tested on different motor ratings ranging from 20 W to 2 KW. In order to demonstrate the feasibility and practicability of the method, this controller is applied in a vacuum cleaner with a switched reluctance motor.

The existing theoretically derived order selection criteria for autoregressive (AR) processes have poor performance in the finite sample case. In this paper, the least-squares-forward (LSF) is considered as the AR parameter estimation method, and new theoretical approximations are derived for the expectations of residual variance and prediction error. These approximations are especially useful in the finite sample case and are derived for AR processes with arbitrary statistical distributions. New order selection criteria for AR processes are derived using these approximations. In a simulation study, the performance of the proposed criteria relative to other criteria is examined in the finite sample case. Simulation results show that the performance of the proposed criteria is much better than the other theoretically derived criteria.

In this paper, an adaptive detection scheme for fluctuating targets with a swerling I model in AR interference is presented. Since the proposed detector uses more information from the target signal in its structure, it has better performance compared with those detectors which do not use the target amplitude model. Performance improvement of this detector compared with the previously AR model based adaptive detector (ARGLR) is shown by simulation results. Besides, another detector is proposed for the known amplitude situation whose performance can be used as an upper bound for all similar detectors.

In this paper, we present a new technique for separating two speech signals received from one microphone or one communication channel. In this special case, the separation problem is too ill-conditioned to be handled with common blind source separation techniques. The proposed technique is a generalized approach to model-based speaker-dependent single channel speech separation techniques in which a priori knowledge of the underlying speakers is used to separate speech signals. The proposed technique not only preserves the advantages of model-based speaker dependent single channel speech separation algorithms (i.e. high separability), but also is able to separate the speech signals of an unlimited number of speakers given the speakers' models) i.e. generality). The whole algorithm consists of three stages: classification, identification, and separation. The identities of speakers speech signals form the mixed signal are first determined at the classification and identification stages. Identified speakers' model is then used to separate the underlying signals using a novel approach consisting of Gaussian mixture modeling, maximum likelihood estimation and Wiener filtering. Evaluation results conducted on a database consisting of 100 mixed speech signals with target-to-interference ratios (TIR) ranging from -9 dB to +9 dB show significant performance improvements over those techniques which use a single model for separation

Microstrip Patch Antennas (MPAs) with circular polarization are used in many communication and radar systems. There are several methods and models to analyze and design these antennas. The Multiport Network Model (MNM) is considered one of the best models for MPAs. This model includes several interconnected circuit networks, each of which represents one characteristic of the MPA. The solution of this model is equivalent to the calculation of the input and radiation parameters of the antenna. In this paper, a circularly polarized 2×2 array antenna with sequentially rotated microstrip elements is designed using MNM. In order to produce the circular polarization, besides the sequentially rotation technique, two probe feeds are used in the E-plane and H-plane of each element. These probes are fed by current sources with equal amplitudes and a 90 degree phase difference.