Iranian Journal of Electrical and Electronic Engineering
Volume:7 Issue: 4, Dec 2011

This paper proposes an idea to modify the conventional Wilkinson power dividers to have physically spaced output ports. The well-known internal resistor of Wilkinson power divider is now connected to output ports by two additional transmission lines to create a triangular shape power divider. Several modified power dividers are designed at frequency of 1.0 GHz and one of them is fabricated and measured. The measured results of the fabricated diplexer have very good agreement with the theoretical results.

This paper presents the results of Persian handwritten word recognition based on Mixture of Experts technique. In the basic form of ME the problem space is automatically divided into several subspaces for the experts, and the outputs of experts are combined by a gating network. In our proposed model, we used Mixture of Experts Multi Layered Perceptrons with Momentum term, in the classification Phase. We produce three different Mixture of Experts structure. Experimental result for proposed method show an error rate reduction of 6.42 % compare to the mixture of MLPs experts. Comparison with some of the most related methods indicates that the proposed model yields excellent recognition rate in handwritten word recognition.

Abstract: Using robot manipulators for high accuracy applications require precise value of the kinematics parameters. Since measurement of kinematics parameters are usually associated with errors and accurate measurement of them is an expensive task, automatic calibration of robot link parameters makes the task of kinematics parameters determination much easier. In this paper a simple and easy to use algorithm is introduced for correction and calibration of robot kinematics parameters. Actually at several end-effecter positions, the joint variables are measured simultaneously. This information is then used in two different algorithms; least square (LS) and Genetic algorithm (GA) for automatic calibration and correction of the kinematics parameters. This process was also tested experimentally via a three degree of freedom manipulator which is actually used as a coordinate measuring machine (CMM). The experimental Results prove that the Genetic algorithms are better for both parameter identification and calibration of link parameters.

In this paper a novel very high performance current mirror is presented. It favorably benefits from such excellent parameters as: Ultra high output resistance (36.9GΩ), extremely low input resistance (0.0058Ω), low output (~0.18V) and low input voltage (~0.18V) operation, very low power consumption (20μW), very low offset current (1pA), ultra wide current dynamic range (150dB), and ultra high accuracy (error = 0.003%). The circuit has a very simple compact architecture and uses a single 1V power supply. The qualitative performance of the circuit is validated with HSPICE simulations using HSPICE TSMC 0.18μm CMOS technology.

Recently, Inner permanent magnet (IPM) synchronous machines have been introduced as a possible traction motor in hybrid electric vehicle (HEV) and traction applications due to their unique merits. In order to achieve maximum torque per ampere (MTPA), optimization of the motor geometry parameters is necessary. This paper Presents a design method to achieve minimum volume, MTPA and minimum value of cogging torque for traction IPM synchronous machines and simulation in order to extract the output values of motor is done using 3D-Finite Element Model, that has high level of accuracy and gives us a better insight of motor performance. Then presents back EMF, power factor, cogging torque, Flux density, torque per ampere diagram, CPSR (constant power speed ratio), torque per speed diagram in this IPM synchronous machine. This study can help designers in design approach of such motors.

Long-term demand forecasting presents the first step in planning and developing future generation, transmission and distribution facilities. One of the primary tasks of an electric utility accurately predicts load demand requirements at all times, especially for long-term. Based on the outcome of such forecasts, utilities coordinate their resources to meet the forecasted demand using a least-cost plan. In general, resource planning is performed subject to numerous uncertainties. Expert opinion indicates that a major source of uncertainty in planning for future capacity resource needs and operation of existing generation resources is the forecasted load demand. This paper presents an overview of the past and current practice in long- term demand forecasting. It introduces methods, which consists of some traditional methods, neural networks, genetic algorithms, fuzzy rules, support vector machines, wavelet networks and expert systems.

A reliable and accurate diagnosis of inter-turn short circuit faults is a challenging problem in the area of fault diagnosis of electrical machines. The purpose of this challenge is to be more efficient in fault detection and to provide a reliable method with low-cost sensors and simple numerical algorithms which not only detect the occurrence of the fault, but also locate its position in the winding. Hence, this paper presents a novel method for diagnosis of different kinds of inter-turn winding faults in a salient-pole synchronous generator using the change in the magnetic flux linkage. It describes the influence of inter-turn winding faults on the magnetic flux linkage distribution of the generator. The main feature of the proposed method is its capability to identify the faulty coils under two types of inter-turn winding faults. Also, simple algorithm, low cost sensor and sensitivity are the other feature in the proposed technique. In this method, generator air gap flux linkage is measured via search coils sensor installed under the stator wedges. Theoretical approach based on Finite Element Method (FEM) together with experimental results derived from a 4-pole, 380U, 1500 rpm, 50 Hz, 50 KVA, 3-phase salient-pole synchronous generator confirm the validity of the proposed method.

Deregulation of power system in recent years has changed static security assessment to the major concerns for which fast and accurate evaluation methodology is needed. Contingencies related to voltage violations and power line overloading have been responsible for power system collapse. This paper presents an enhanced radial basis function neural network (RBFNN) approach for on-line ranking of the contingencies expected to cause steady state bus voltage and power flow violations. Hidden layer units (neurons) have been selected with the growing and pruning algorithm which has the superiority of being able to choose optimal unit’s center and width (radius). A feature preference technique-based class separability index and correlation coefficient has been employed to identify the relevant inputs for the neural network. The advantages of this method are simplicity of algorithm and high accuracy in classification. The effectiveness of the proposed approach has been demonstrated on IEEE 14-bus power system.

this work studies the effect of neutral earth resistance on the controlling ferroresonance oscillation in the power transformer including MOV surge arrester. A simple case of ferroresonance circuit in a three phase transformer is used to show this phenomenon and the three-phase transformer core structures including nonlinear core losses are discussed. The effect of MOV surge arrester and neutral earth resistance on the onset of chaotic ferroresonance and controlling chaotic transient in a power transformer including nonlinear core losses has been studied. It is expected that these resistances generally cause into ferroresonance control. Simulation has been done on a power transformer rated 50 MVA, 635.1 kV with one open phase. The magnetization characteristic of the transformer is modelled by a single-value two-term polynomial with q=7, 11. The core losses are modelled by third order in terms of voltage. The simulation results reveal that connecting the MOV arrester and neutral resistance to the transformer, exhibits a great impact on ferroresonance over voltages. Copyright © 2009 Praise Worthy Prize S.r.l. - All rights reserved.

In this paper capacity withholding in an oligopolistic electricity market that all Generation Companies (GenCos) bid in a Cournot model is analyzed and the capacity withheld index, the capacity distortion index and the price distortion index are obtained and formulated. Then a new index, Distortion-Withheld Index (DWI), is proposed in order to measure the potential ability of market for capacity withholding. In these indices the impact of demand elasticity on capacity withholding is considered and it is shown that demand elasticity plays an important role for capacity withholding and market power mitigation. Due to the significant role of forward contracts for market power mitigation and risk hedging in power markets, the impacts of these contracts on capacity withholding are considered. The effects of GenCos’ strategic forward contracts on capacity withholding are also discussed. Moreover, the relationship between capacity withholding of GenCos and market price distortion is acquired. A two-settlement market including a forward market and a spot market is used to describe GenCos’ strategic forward contracting and spot market competition.