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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 16 Documents
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Search results for , issue "Vol 2, No 1: February 2012" : 16 Documents clear
Fuzzy based Power Flow control of Two Area Power System K Manickavasagan
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 1: February 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (443.545 KB)

Abstract

This paper deals with the novel approach of fuzzy based power flow control of two area power system. Interconnected operation enables utilities to share the generation from one area to other areas. In each area, all the generators are synchronized at same frequency. The change in system load within the area causes frequency deviation in the generating buses and tie line error in the tie lines connecting neighboring areas. The control of interconnected power system is achieved by Automatic Generation Control (AGC), which maintains the balance between generation and load. In this paper, the components of AGC, frequency deviation (DF), tie line error (DPtie) and the output change in generations (DPgi) are calculated by steady state power flow analysis using decoupled Newton Raphson method. The control action is performed by conventional method using participation factor and Fuzzy Logic Controller (FLC). The DF and DPtie are the inputs to the conventional controller and Fuzzy Logic Controller (FLC). The proposed method is tested with modified IEEE 30 bus system and the results are compared. Analysis reveals that FLC is quite capable of suppressing the frequency deviation and tie line error effectively as compared to that obtained with conventional controller.DOI:http://dx.doi.org/10.11591/ijece.v2i1.219 
Adaptive Neuro-fuzzy Inference System Based Control of puma 600 Robot Manipulator Ouamri Bachir; Ahmed-Foitih Zoubir
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 1: February 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (241.431 KB)

Abstract

The strong dependence of the computed torque control of dynamic model of the robot manipulator makes this one very sensitive to uncertainties of modelling and to the external disturbances. In general, the vector of Coriolis torque, centrifugal and gravity is very complicated, consequently, very difficult to modelled. Fuzzy Logic Controller can very well describe the desired system behavior with simple “if-then” relations owing the designer to derive “if-then” rules manually by trial and error. On the other hand, Neural Networks perform function approximation of a system but cannot interpret the solution obtained neither check if its solution is plausible. The two approaches are complementary. Combining them, Neural Networks will allow learning capability while Fuzzy-Logic will bring knowledge representation (Neuro-Fuzzy). This paper presents the control of puma 600 robot arm using Adaptive Neuro Fuzzy Inference System (ANFIS) based computed torque controller (type PD). Numerical simulation using the dynamic model of puma 600 robot arm shows the effectiveness of the approach in improving the computed torque method. Comparative evaluation with Fuzzy computed torque (type PD) control is presented to validate the controller design. The results presented emphasize that a satisfactory trajectory tracking precision and stabilility could be achieved using ANFIS controller than Fuzzy controller. Keywords: Fuzzy computed torque control, Robot control, Adaptive neuro-fuzzy inference system (ANFIS).DOI:http://dx.doi.org/10.11591/ijece.v2i1.116
Simulation of the Different Transmission Line Faults for a Grid Connected Wind Farm with Different Types of Generators Helmy Mohammed Abdel-Mageed
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 1: February 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (378.409 KB)

Abstract

This paper aims to simulate a wind farm model that includes a wind turbine and three different types of generators , which are three-phase synchronous generator, three-phase squirrel-cage induction generatorand three-phase doubly-fed induction generator ,these generators are the main machines that generally used in the field of wind energy generation. All generators are connected in parallel at the point of common coupling(pcc) and connected to the utility grid . This model is a simple representation of the actual model of zafarana, which is the biggest wind farm in Egypt and further to use it in different kinds of simulations, and display the difference in response among all generators with thesame power rating (500 kw) and subjected to the same operating conditions and faults. This paper describes the simulation of the differentfaults that occur along the transmission line of the power system such as single-line fault, line to line fault, double lines to ground fault, and finally three line faults. The response of the wind turbine and the different generators will be analyzed and discussed to compare the transient response of all generators at the different types of faults, where the fault period is selected to be 300 ms. The model is created in MATLAB software that enables the dynamic and static simulations of electric, electromagnetic and electromechanical systems. The machines are standard blocks in the software library.DOI:http://dx.doi.org/10.11591/ijece.v2i1.113
Implimentation of Evolutionary Particle Swarm Optimization in Distributed Generation Sizing J.J. Jamian; M.W. Mustafa; H. Mokhlis; M.A. Baharudin
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 1: February 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (482.434 KB)

Abstract

The size of Distributed Generation (DG) is very important in order to reduce the impact of installing a DG in the distribution Network. Without proper connection and sizing of DG, it will cause the power loss to increase and also might cause the voltage in the network to operate beyond the acceptable limit. Therefore, most researchers have concentrated on the optimization technique to regulate the DG’s output to compute its optimal size. In this paper, the concept of Evolutionary Particle Swarm Optimization (EPSO) method is implemented in sizing the DG units. By substituting the concept of Evolutionary Programming (EP) in some part of Particle Swarm Optimization (PSO) algorithm process, it will make the process of convergence become faster. The algorithm has been tested in 33bus distribution system with 3 units of DG that operate in PV mode. Its performance was compared with the performance when using the traditional PSO and without using any optimization method. In terms of power loss reduction and voltage profile, the EPSO can give similar performance as PSO. Moreover, the EPSO requires less number of iteration and computing time to converge. Thus, it can be said that the EPSO is superior in term of speed, while maintaining the same performance.DOI:http://dx.doi.org/10.11591/ijece.v2i1.227
Comparative Performance Investigations of Stochastic and Genetic Algorithms Under Fast Dynamically Changing Environment in Smart Antennas Jafar Ramadhan Mohammed
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 1: February 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (153.786 KB)

Abstract

In a mobile communication systems, the number of observation data (snapshots) used for covariance matrix estimation can be insufficient, which often occurs due to fast dynamically changing environment or signal characteristics are rapidly changing. In these situations, the performance of the standard adaptive algorithms such as LMS are known to degrade substantially. In this paper, we propose the use of a Genetic Algorithm (GA) to perform the adaptation control of the system parameters under dynamically changing environments The GA-based beamformer has nearly optimal interference cancellation under dynamic conditions, and makes the output SINR consistently close to the optimal one regardless of the number of snapshot used. Other advantages of the GA is its simplicity and fast convergence provided that the parameters are appropriately chosen, which makes it a practical algorithm for beamforming in smart antenna. Simulation results validate substantial performance improvements relative to other standard adaptive algorithms. Although, the use of GA is not new in smart antenna technology, the performance evaluation of the genetic optimization under fast dynamically changing environment has not been investigated to the best of my knowledge and it is of great practical significance.DOI:http://dx.doi.org/10.11591/ijece.v2i1.119
Performance of Governor System on Minimizing Frequency Fluctuations with Wind Power Generation Dr. Md. Rafiqul Islam Sheikh; Md. Mejbaul Haque; M.A. Hossain
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 1: February 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (680.817 KB)

Abstract

As wind turbine output is proportional to the cube of wind speed, the wind turbine generator output fluctuates due to wind speed variations. Hence, if the power capacity of wind power generators becomes large, wind power generator output can have an influence on the power system frequency. Therefore, this study investigates the influence of governor control systems of synchronous generators (SGs) for minimizing frequency fluctuations with high wind power penetration level, when a total capacity of SGs is considered as 100 MVA. It is seen that when both SGs operate as governor free (GF) operation, system perform better frequency control. But it can not be maintained to the acceptable level when SGs operate at GF-LFC or LFC-GF operation with wind power capacity about 5% of total capacity. Finally, it is seen that when several interconnected SGs are operated with different control modes, system frequency become more severe for 10% capacity of wind power.DOI:http://dx.doi.org/10.11591/ijece.v2i1.180

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