Iranian Journal of Electrical and Electronic Engineering
Volume:6 Issue: 4, Dec 2010

novel low-voltage two-stage operational amplifier employing resistive biasing is presented. This amplifier implements neutralization and correction common mode stability in second stage while employs capacitive dc level shifter and coupling between two stages. The structure reduces the power consumption and increases output voltage swing. The compensation is performed by simple miller method. For each stage an independent common-mode feedback circuits has been used. Simulation results show that power consumption is 2.1 mW at 1V supply. The dc gain of the amplifier is about 70 dB while its output swing is as high as around 1.2V.

This paper presents a modified nine switch inverter with two inputs and two Z-source networks. This inverter has two DC inputs and two AC outputs. Input DC voltages can be boosted to the required level. Amplitude, frequency and phase of AC output voltages can be controlled, independently. The proposed converter can be used in applications with two unregulated DC sources, which require feeding two independent loads. Compared to the conventional structure, the proposed converter requires reduced number of semiconductor switches hence improved converter reliability and less volume. Performance of the proposed inverter is verified by experimental results.

In this paper particle swarm optimization (PSO) is used for a design optimization of a linear permanent magnet synchronous motor (LPMSM) considering ultra low thrust force ripples, low magnet consumption, improved efficiency and thrust. The influence of PM material is discussed, too and the modular poles are proposed to achieve the best characteristic. PM dimensions and material, air gap and motor width are chosen as design variables. Finally 2-D finite element analyses validate the optimization results.

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.

The principle object of this paper is to offer a modified design of Rogowski coil based on its frequency response. The improvement of the integrator circuit for nullifying the phase difference between the waveforms of the measured-current and the corresponding terminal voltage is a further object of this investigation. This paper addresses an accurate, yet more efficient measuring and protecting device for low frequency applications. This requires verification for the simulations by physical descriptions and experimental results. These validate the superior performance of Rogowski coils over conventional current transformers. Keywords: current transformer, frequency response, integrator circuit, mutual inductance, Rogowski coil, terminal resistor

This paper proposes an algorithm for transmission cost allocation (TCA) in a large power system based on nodal pricing approach using the multi-area scheme. The nodal pricing approach is introduced to allocate the transmission costs by the control of nodal prices in a single area network. As the number of equations is dependent on the number of buses and generators, this method will be very time consuming for large power systems. To solve this problem, the present paper proposes a new algorithm based on multi-area approach for regulating the nodal prices, so that the simulation time is greatly reduced and therefore the TCA problem with nodal pricing approach will be applicable for large power systems. In addition, in this method the transmission costs are allocated to users more equitable. Since the higher transmission costs in an area having a higher reliability are paid only by users of that area in contrast with the single area method, in which these costs are allocated to all users regardless of their locations. The proposed method is implemented on the IEEE 118 bus test system which comprises three areas. Results show that with application of multi-area approach, the simulation time is greatly reduced and the transmission costs are also allocated to users with less variation in new nodal prices with respect to the single area approach.

Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss, etc. This paper presents a new methodology using Fuzzy and Artificial Bee Colony algorithm(ABC) for the placement of Distributed Generators(DG) in the radial distribution systems to reduce the real power losses and to improve the voltage profile. A two-stage methodology is used for the optimal DG placement. In the first stage, Fuzzy is used to find the optimal DG locations and in the second stage, ABC algorithm is used to find the size of the DGs corresponding to maximum loss reduction. The ABC algorithm is a new population based meta heuristic approach inspired by intelligent foraging behavior of honeybee swarm. The advantage of ABC algorithm is that it does not require external parameters such as cross over rate and mutation rate as in case of genetic algorithm and differential evolution and it is hard to determine these parameters in prior. The proposed method is tested on standard IEEE 33 bus test system and the results are presented and compared with different approaches available in the literature. The proposed method has outperformed the other methods in terms of the quality of solution and computational efficiency.