Iranian Journal of Electrical and Electronic Engineering

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In this paper we first show that standard BP algorithm cannot yeild to a uniform information distribution over the neural network architecture. A measure of sensitivity is defined to evaluate fault tolerance of neural network and then we show that the sensitivity of a link is closely related to the amount of information passes through it. Based on this assumption, we prove that the distribution of output error caused by s-a-0 (stuck at 0) faults in a MLP network has a Gaussian distribution function. UDBP (Uniformly Distributed Back Propagation) algorithm is then introduced to minimize mean and variance of the output error. Simulation results show that UDBP has the least sensitivity and the highest fault tolerance among other algorithms such as WRTA, N-FTBP and ADP. Then a MLP neural network trained with UDBP, contributes in an Algorithm Based Fault Tolerant (ABFT) scheme to protect a nonlinear data process block. The neural network is trained to produce an all zero syndrome sequence in the absence of any faults. A systematic real convolution code guarantees that faults representing errors in the processed data will result in notable nonzero values in syndrome sequence. A majority logic decoder can easily detect and correct single faults by observing the syndrome sequence. Simulation results demonstrating the error detection and correction behavior against random s-a-0 faults are presented too.

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A modified circular patch antenna design has been proposed in this paper, the bandwidth of this antenna is optimized using the genetic algorithm (GA) based on fuzzy decision-making. This design is simulated with HP HFSS Program that based on finite element method. This method is employed for analysis at the frequency band of 1.4 GHz- 2.6 GHz. It gives good impedance bandwidth of the order of 15.5% at the frequency band of 1.67GHz- 1.95GHz and 10.6% at 2.23GHz- 2.48GHz. It means that impedance bandwidth increases above 4.9% than the impedance bandwidth of ordinary circular patch antennas and band width rise from 1.78GHz- 1.98GHz (10.6%) to 1.67GHz- 1.95GHz (15.5%) and 2.23GHz- 2.48GHz (10.6%). The antenna fabricated with two slots on circular patch antenna. The measured results of the optimized antenna validate a high compatibility between the simulation and the measurements.

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Medium-term modeling of electricity market has essential role in generation expansion planning. On the other hand, uncertainties strongly affect modeling and consequently, strategic analysis of generation firms in the medium term. Therefore, models considering these uncertainties are highly required. Among uncertain variables considered in the medium term generation planning, demand and hydro inflows are of the greatest importance. This paper proposes a new approach for simulating the operation of power market in medium-term, taking into account demand and hydro inflows uncertainties. The demand uncertainty is considered using Monte-Carlo simulations. Standard Deviation over Expected Profit (SDEP) of generation firms based on simulation results is introduced as a new index for analyzing the influence of the demand uncertainty on the behavior of market players. The correlation between capacity share of market players and their SDEP is also demonstrated. The uncertainty of inflow as a stochastic variable is dealt using scenario tree representation. Rational uncertainties as strategic behavior of generation firms, intending to maximize their expected profit, is considered and Nash-Equilibrium is determined using the Cournot model game. Market power mitigation effects through financial bilateral contracts as well as demand elasticity are also investigated. Case studies confirm that this representation of electricity market provides robust decisions and precise information about electricity market for market players which can be used in the generation expansion planning framework.

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This paper presents a parametric low differential order model, suitable for mathematically analysis for Induction Machines with faulty stator. An adaptive Kalman filter is proposed for recursively estimating the states and parameters of continuous–time model with discrete measurements for fault detection ends. Typical motor faults as interturn short circuit and increased winding resistance are taken into account. The models are validated against winding function induction motor modeling which is well known in machine modeling field. The validation shows very good agreement between proposed method simulations and winding function method, for short-turn stator fault detection.

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In this paper, we propose a new chaos-based communication scheme using the observers. The novelty lies in the masking procedure that is employed to hide the confidential information using the chaotic oscillator. We use a combination of the addition and inclusion methods to mask the information. The performance of two observers, the proportional observer (P-observer) and the proportional integral observer (PI-observer) is compared that are employed as receivers for the proposed communication scheme. We show that the P-observer is not suitable scheme since it imposes unpractical constraints on the messages to be transmitted. On the other hand, we show that the PI-observer is the better solution because it allows greater flexibility in choosing the gains of the observer and does not impose any unpractical restrictions on the message.

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The main theme of this paper is to present novel controller, which is a genetic based fuzzy Logic controller, for interior permanent magnet synchronous motor drives with direct torque control. A radial basis function network has been used for online tuning of the genetic based fuzzy logic controller. Initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition, a genetic algorithm is used to optimize fuzzy logic parameters in closed-loop direct torque control scheme. In other words, the genetic algorithm finds optimum input and output scaling factors and optimum number of membership functions. This optimization procedure is utilized to obtain the minimum speed deviation, minimum settling time, zero steady-state error. The control scheme has been verified by simulation tests with a prototype interior permanent magnet synchronous motor.

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In this paper, we have investigated the effects of asymmetry in the source and drain capacitance of metallic island single electron transistors. By comparing the source and drain Fermi levels, in the ground and source referenced biasing configurations, with the island’s discrete charging energy levels for various gate voltages, we have derived a set of closed form equations for the device threshold voltage. Extending our technique, for the first time, we have also modeled the “kink effect” appearing in the device ID-VDS characteristic, next to the threshold voltage. To demonstrate how accurate the calculated values of the threshold and kink voltages obtained from the analytically derived formulas are, next, we have used the master equation based on the orthodox theory to simulate the device parameters, numerically. Comparisons of the numerical results, obtained from both techniques, have demonstrated the tolerances in our analytical calculations, for the worst case, are less than 1%.

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In this paper, using the neural space mapping (NSM) concept, we present a SPICE-compatible modeling technique to modify the conventional MOSFET equations, to be suitable for ballistic carbon nanotube transistors (CNTTs). We used the NSM concept in order to correct conventional MOSFET equations so that they could be used for carbon nanotube transistors. To demonstrate the accuracy of our model, we have compared our results with those obtained by using open-source software known as FETToy. This comparison shows that the RMS errors in our calculated IDS, under various conditions, are smaller than the RMS errors in IDS values calculated by the existing analytical models published by others.

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The recent trends in electrical power distribution system operation and management are aimed at improving system conditions in order to render good service to the customer. The reforms in distribution sector have given major scope for employment of distributed generation (DG) resources which will boost the system performance. This paper proposes a heuristic technique for allocation of distribution generation source in a distribution system. The allocation is determined based on overall improvement in network performance parameters like reduction in system losses, improvement in voltage stability, improvement in voltage profile. The proposed Network Performance Enhancement Index (NPEI) along with the heuristic rules facilitate determination of feasible location and corresponding capacity of DG source. The developed approach is tested with different test systems to ascertain its effectiveness.

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We present an optimized design for GaAs/AlGaAs quantum cascade lasers operating at ‎‎4.1THz. This was based on a three-well active module with diagonal radiative transition. This ‎was performed by modifying the existing model structure, to reduce the parasitic anticrossings ‎‎(leakage currents) as well as the optical gain linewidth. While the gain FWHM was reduced by ‎more than 50% the gain peak was increased by about 23.3%.‎

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We report the simulation results for impact of nonlinear Kerr effect on band structures of a ‎two dimensional photonic crystal (2D-PhC) with no defect, a PhC based W1-waveguide ‎‎(W1W), and also Coupled-Cavity Waveguides (CCWs). All PhC structres are assumed to a ‎square lattice of constant a made of GaAs rods of radius r=0.2a, in an air background. The ‎numerical simulation was performed using the nonlinear finite difference time domain ‎‎(NFDTD) technique. To study the impact of Kerr effect on the photonic band structures, E-‎polarized lights of peak input intensities 0.5 GW-cm−2≤I≤25 GW-cm−2 have been used. The ‎numerical results have shown that as the input light intensity increases, the band edges for all ‎PhC waveguide structures considered experience red shifts. These numerical results for CCWs ‎also show that the larger the light input intensity, the smaller is the corresponding maximum ‎light group velocity.‎

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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.

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Time domain analysis of multilayer graphene nanoribbon (MLGNR) interconnects, based on ‎transmission line modeling (TLM) using a six-order linear parametric expression, has been ‎presented for the first time. We have studied the effects of interconnect geometry along with ‎its contact resistance on its step response and Nyquist stability. It is shown that by increasing ‎interconnects dimensions their propagation delays are increased and accordingly the system ‎becomes relatively more stable. In addition, we have compared time responses and Nyquist ‎stabilities of MLGNR and SWCNT bundle interconnects, with the same external dimensions. ‎The results show that under the same conditions, the propagation delays for MLGNR ‎interconnects are smaller than those of SWCNT bundle interconnects are. Hence, SWCNT ‎bundle interconnects are relatively more stable than their MLGNR rivals.‎

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Resolvers are widely used in electric driven systems especially in high precision servomechanisms. Both encapsulated and pancake resolvers suffer from a major drawback: static eccentricity (SE). This drawback causes a significant increase in resolver output position error (RPE) which could not be corrected electronically. To reduce RPE, this paper proposes a novel structure with axial flux. Proposed topology, design guidelines, optimization procedure and several key features to improve the sensitivity of axial flux resolver (AFR) against SE are studied. Furthermore, to minimize RPE an optimized design is attained. The machines are investigated in detail by using d-q model and 3D time stepping finite-element analysis. The results of theses two methods are compared and both prototype machines (proposed and optimized) are built. In order to evaluate proposed topologies, an experimental test setup is devised. Finally, the experimental results of the prototype machines verified the analysis results.

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The purpose of this paper is to present a new approach based on the Least Squares Error method for estimating the unknown parameters of the nonlinear 3rd order synchronous generator model. The proposed method uses the mathematical relationships between the machine parameters and on-line input/output measurements to estimate the parameters of the nonlinear state space model. The field voltage is considered as the input and the rotor angle and the active power are considered as the generator outputs. In fact, the third order nonlinear state space model is converted to only two linear regression equations. Then, easy-implemented regression equations are used to estimate the unknown parameters of the nonlinear model. The suggested approach is evaluated for a sample synchronous machine model. Estimated parameters are tested for different inputs at different operating conditions. The effect of noise is also considered in this study. Simulation results show that the proposed approach provides good accuracy for parameter estimation.

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Phasor Measurement Units (PMUs) are in growing attention in recent power systems because of their paramount abilities in state estimation. PMUs are placed in existing power systems where there are already installed conventional measurements, which can be helpful if they are considered in PMU optimal placement. In this paper, a method is proposed for optimal placement of PMUs incorporating conventional measurements of zero injection buses and branch flow measurements using a permutation matrix. Furthermore, the effect of single branch outage and single PMU failure is included in the proposed method. When a branch with a flow measurement goes out, the network loses one observability path (the branch) and one conventional measurement (the flow measurement). The permutation matrix proposed here is able to model the outage of a branch equipped with a flow measurement or connected to a zero injection bus. Also, measurement redundancy, and consequently measurement reliability, is enhanced without increasing the number of PMUs this implies a more efficient usage of PMUs than previous methods. The PMU placement problem is formulated as a mixed-integer linear programming that results in the global optimal solution. Results obtained from testing the proposed method on four well-known test systems in diverse situations confirm its efficiency.

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In this paper, a novel technique for the design of two-channel Quadrature Mirror Filter (QMF) banks with linear phase in frequency domain is presented. To satisfy the exact reconstruction condition of the filter bank, low-pass prototype filter response in pass-band, transition band and stop band is optimized using unconstrained indirect update optimization method. The objective function is formulated as a weighted sum of pass-band error and stop-band residual energy of low-pass prototype filter, and the square error of the distortion transfer function of the QMF bank at the quadrature frequency. The performance of the proposed algorithm is evaluated in terms of Peak Reconstruction Error (PRE), mean square error in pass-band and stop-band regions and stop-band edge attenuation. Design examples are included to illustrate the performance of the proposed algorithm and the quality of the filter banks that can be designed.

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This paper aims to measure and analyze of the leakage current of 20 kV polymer and porcelain metal oxide surge arresters under humid ambient conditions by applying different voltages to the arresters terminal. The characteristics of the leakage currents at that stage have been investigated when changes in the ambient humidity were introduced in an artificial fog chamber. It is assumed that magnitude of the noise level during the tests is constant. The frequency and resistive component peak efficient analysis can then be done on the leakage current signal. The idea behind this is to get indicators for investigating of surge arrester behavior in humid conditions. Two important indicators were obtained to evaluate the behavior of the surge arrester in humid conditions

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One of the instruments for determination of position used in several applications is the Global Positioning System (GPS). With a cheap GPS receiver, we can easily find the approximate position of an object. Accuracy estimation depends on some parameters such as dilution of precision, atmospheric error, receiver noise, and multipath. In this study, position accuracy with GPS receiver is classified in three classes. Nine classification methods are utilized and compared. Finally, a new method is selected for classification. Results are verified with experimental data. Success rate for classificationis approximately 84%.

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Congestion and overloading for lines are the main problems in the exploitation of power grids. The consequences of these problems in deregulated systems can be mentioned as sudden jumps in prices in some parts of the power system, lead to an increase in market power and reduction of competition in it. FACTS devices are efficient, powerful and economical tools in controlling power flows through transmission lines that play a fundamental role in congestion management. However, after removing congestion, power systems due to targeting security restrictions may be managed with a lower voltage or transient stability rather than before removing. Thus, power system stability should be considered within the construction of congestion management. In this paper, a multi-objective structure is presented for congestion management that simultaneously optimizes goals such as total operating cost, voltage and transient security. In order to achieve the desired goals, locating and sizing of series FACTS devices are done with using components of nodal prices and the newly developed grey wolf optimizer (GWO) algorithm, respectively. In order to evaluate reliability of mentioned approaches, a simulation is done on the 39-bus New England network.