The Modares Journal of Electrical Engineering
Volume:10 Issue: 2, 2010

Detection & Classification of power quality (PQ) disturbances are the most important problems in distribution systems. In this paper, a new approach for the detection and classification of single and combined PQ disturbances is proposed which utilizes fuzzy logic and particle swarm optimization (PSO) algorithms. In this approach, first suitable features of the waveform of PQ disturbances are extracted. Extraction of these specifications is done based on the Fourier and Wavelet transforms. Then, the proposed Fuzzy systems make decision about the type of each of the PQ disturbances by employing these specifications. The PSO algorithm is used for accurate determination of each parameter of the membership functions of the systems. To test the proposed approach, the waveform of PQ disturbances was assumed to be in a sampled form from single and combined categories. Impulse, interruption, swell, sag, notch, transient, harmonic, and flicker phenomena are considered as single disturbances for voltage signal. More over, harmonic with swell, swell with harmonic, swell with transient, harmonic with sag, sag with harmonic and sag with transient are considered as combined disturbances for the voltage signal. Simulation results denote capability of the proposed approach for identification of single and combined disturbances with about 99% accuracy.

One of the problems associated with adaptive FIR filters in the identification of systems with long impulse responses, is their excessive computational complexity. Recently a new kind of adaptive filters, based on three-level clipping of the input signal has been presented for reduction of their computational complexity. In this paper, a theoretical analysis of the steady-state misalignment of adaptive filter equipped with the LMS algorithm, based on three-level clipping, is presented and by using it the minimum mean square error is achieved. This analysis can be a basis in the design of the above mentioned filters with appropriate clipping levels and proper step-sizes for system identification applications.

Some of the important mechanical loads in the civil and military industries are variable speed and power and their efficiency. Mechanical coupling of two different electric motors is suitable for These types of application. Using this technique reduces energy consumption of submarine’s motion system and submarine range would be increased. But the use of this technique requires a complex controller. Setting the desired speed for the mechanical load-axis and sharing power on two motors are the main objectives of control. Previously controllers divided load power between two motors as non-optimal controller. This article presents a new controller that can perform the above objectives and is divided between two motors as optimal controller for all speeds. The method of this article will increase efficiency for all speeds, increase the range of submarine and reduce energy consumption for Paper industry and other similar cases. Simulation results have identified new control benefits than the previous model and tested a sample of 13% increase in efficiency.

Most of the methods that have been proposed for speed estimation of induction machines require the rotor and the Stator resistance to change in the normal operating range. On the other hand, estimation of the rotor resistance requires rotor speed. In this paper, after studying conditions for simultaneous estimation of rotor speed and rotor resistance, a method for simultaneous estimation of rotor speed, rotor resistance and stator resistance is proposed. In this method, an additional frequency component is injected to the reference flux and Fast Fourier Transform is used to estimate rotor speed and rotor resistance. Stator resistance is estimated from estimated stator flux using a fuzzy estimator. Finally, effectiveness of the sensorless speed controlled induction machine drive with simultaneous rotor and stator resistance estimation has been verified with simulation results under various operating conditions, especially at low speed and generating conditions.

Voltages and currents are induced into electronic circuit boards as electromagnetic waves are radiated on them. The strength of induction depends on the wavefront and the circuit board characteristics. In this paper, by solving Maxwell’s equations using FDTD method and then by extending it by three dimensional simulation using the GPML criteria for boundary conditions and TF/SF technique, effect of wave propagation characteristics on induction into microstrip lines of the circuit board and its surrounding was investigated. Converting electrical equations into electromagnetic counterparts in the Gummel-Poon model has then provided the possibility of performance analysis of BJT with wave equations. Comparison of experimental and simulation results have shown that for the analysis of electromagnetic wave effects on electronic circuits one can use active electronic component models in simulation with FDTD methods.

Double layer ZnO/SnO2 thin film resistive gas sensors were fabricated by successive PVD of those oxides onto porcelain substrates. The metallic contacts were provided by electron beam evaporation of platinum onto substrates prior to deposition of the gas sensitive layers. Deposits were thermally annealed at different temperatures. It was shown that the activation energy of electrical conduction in the double layer depends on the annealing temperature. Higher annealing temperatures result in larger activation energies. The sensitivity of the double layer devices to ethanol vapor was measured and compared to that of single layer SnO2 sensors fabricated at similar conditions. It was shown for the first time that the gas sensitivity of ZnO/SnO2 thin film gas sensors can be adjusted by controlling parameters of the thermal annealing process.

Network expansion studies normally offer new power lines, new substations or expansion of existing substations. They are generally proposed based on technical requirements, but financial restrictions are not considered. Because of financial restrictions, ranking of network expansion plans is required. In this paper an algorithm for such ranking, based on technical and financial view points and proposes suitable parameters. This algorithm may be used to compliment static or dynamic expansion planning studies of electric power networks.