Islamic Azad University at Anar

www.anariau.ac.ir
Kerman, Iran

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Gadari H.,Islamic Azad University at Anar
8th International Conference on Power Electronics - ECCE Asia: "Green World with Power Electronics", ICPE 2011-ECCE Asia | Year: 2011

In this article, a new evolutionary algorithm presented in order to optimally design stabilizers of multi-machine power system. This article utilizes Hybrid Particle Swarm Optimization (HPSO) technique to search for optimized amounts of power system stabilizer (PSS). The strength of presented method to create initial amounts was proved. Efficiency and capability of HPSOPSS was tested under different turbulences and loading modes for different multi-machine systems. Data analysis and results of nonlinear simulations, delineated the usefulness of HPSOPSS in damping local and in-area frequency modes; and this coordination has a remarkable effect on execution of loading modes and arrangement of power system. Totally, potential and priority of the presented method in proportion to other common methods was proved. © 2011 IEEE.


Noormohamadi H.,Islamic Azad University at Anar | Niknafs S.,Islamic Azad University at Anar | Gharaveisi A.A.,Shahid Bahonar University of Kerman
International Review of Electrical Engineering | Year: 2010

Automatic Generation Control (AGC) is a means of automatically controlling the outputs of power-generating units to accomplish economic dispatch, and maintain system frequency and power flows over tie lines at desired levels. In order to maintain the frequency in nominal boundaries, some parameters must be adjusted. In an automatic generation control system the most important parameter is the coefficients of conventional integral controllers. This paper deals with automatic generation control of a multi-area non-reheat thermal system. For optimization the coefficients of the integrators, the Bacterial Foraging Algorithm (BFA) is proposed. Simulation results can show clearly a desirable performance of the proposed system within a wide range of variation for specified parameters and indicate the effectiveness of the proposed algorithm for AGC system destination. © 2010 Praise Worthy Prize S.r.l.


Eslami M.,Islamic Azad University at Anar | Shareef H.,National University of Malaysia | Mohamed A.,National University of Malaysia | Khajehzadeh M.,Islamic Azad University at Tehran
Przeglad Elektrotechniczny | Year: 2011

In this study, simultaneous coordinated designing of power system stabilizer and static VAR compensator damping controller is investigated. The particle swarm optimization (PSO) is used to search for optimal controller parameters, by incorporating chaos. PSO with chaos is hybridized to form a chaotic PSO, which reasonably combines the population-based evolutionary searching ability of PSO and chaotic searching behavior. The efficiency of the proposed controllers is exhibited through the eigenvalue analysis and nonlinear time-domain simulation. The results of these studies show that the proposed coordinated controllers have an excellent capability in damping interarea oscillations.


Nazari A.,Islamic Azad University at Yazd | Montazer M.,Amirkabir University of Technology | Moghadam M.B.,Allame Tabatabaee University | Anary-Abbasinejad M.,Islamic Azad University at Anar
Carbohydrate Polymers | Year: 2011

Cationization is a novel treatment on cotton to produce fabric with new characteristics. Bleached cotton fabric has already been treated with nanoTiO2 (NTO) to create fabric with self-cleaning properties. However treatment of cationized cotton with NTO has not been reported. In this research, the self-cleaning properties of bleached and cationized cotton treated by NTO were compared and optimized using a statistical model. The bleached cotton was first cationized with 3-chloro-2-hydroxypropyl trimethyl ammonium chloride (Quat-188). The NTO particles were stabilized on the cotton surface using butane tetra carboxylic acid (BTCA) in the presence of sodium hypophosphite (SHP) under different curing conditions including UV irradiation (UV), high temperature (High temp) and a combination of UV and high temperature (UV-Temp). The central composite design (CCD) was used for different variables based on Design of Expert software. The appropriate model was obtained for each condition to create optimum color difference. The X-ray diffraction (XRD) and scanning electron microscopy (SEM) were also employed to indicate the NTO particles on the fabric surface including the size of nanoparticles and their crystallinity. © 2010 Elsevier Ltd. All rights reserved.


Eslami M.,Islamic Azad University at Kermān | Shareef H.,National University of Malaysia | Taha M.R.,National University of Malaysia | Khajehzadeh M.,Islamic Azad University at Anar
International Journal of Electrical Power and Energy Systems | Year: 2014

An adaptive particle swarm optimization based on nonlinear time-varying acceleration coefficients (NTVAC-PSO) is proposed for solving global optimization problems and damping of power system oscillations. The new method aims to control the global exploration ability of the original PSO algorithm and to increase its convergence rate with an acceptable solution in less iteration. A set of 10 well-known benchmark optimization problems is utilized to validate the performance of the NTVAC-PSO as a global optimization algorithm and to compare with similar methods. The numerical experiments show that the proposed algorithm leads to a significantly more accurate final solution for a variety of benchmark test functions faster. In addition, the simultaneous coordinated design of unified power flow controller-based damping controllers is presented to illustrate the feasibility and effectiveness of the new method. The performance of the proposed algorithm is compared with other methods through eigenvalue analysis and nonlinear time-domain simulation. The simulation studies show that the controllers designed using NTVAC-PSO performed better than controllers designed by other methods. Moreover, experimental results confirm superior performance of the new method compared with other methods. © 2013 Elsevier Ltd. All rights reserved.


Khajehzadeh M.,Islamic Azad University at Anar | Taha M.R.,National University of Malaysia | El-Shafie A.,National University of Malaysia | Eslami M.,Islamic Azad University at Anar
Journal of Zhejiang University: Science A | Year: 2011

This paper deals with the economically optimized design and sensitivity of two of the most widely used systems in geotechnical engineering: spread footing and retaining wall. Several recent advanced optimization methods have been developed, but very few of these methods have been applied to geotechnical problems. The current research develops a modified particle swarm optimization (MPSO) approach to obtain the optimum design of spread footing and retaining wall. The algorithm handles the problem-specific constraints using a penalty function approach. The optimization procedure controls all geotechnical and structural design constraints while reducing the overall cost of the structures. To verify the effectiveness and robustness of the proposed algorithm, three case studies of spread footing and retaining wall are illustrated. Comparison of the results of the present method, standard PSO, and other selected methods employed in previous studies shows the reliability and accuracy of the algorithm. Moreover, the parametric performance is investigated in order to examine the effect of relevant variables on the optimum design of the footing and the retaining structure utilizing the proposed method. © 2011 Zhejiang University and Springer-Verlag Berlin Heidelberg.


Najafi M.,Islamic Azad University at Anar
Canadian Journal of Chemistry | Year: 2013

The radical scavenger activity of X1-and X2- substituted ethoxyquin derivatives has been investigated in the gas phase and water. The reaction enthalpies of radical scavenger activity of the studied derivatives have been calculated and compared with corresponding values of ethoxyquin. Results show that electron-withdrawing group substituents increase the bond dissociation enthalpy and ionization potential, while electron-donating group substituents cause a rise in the proton affinity. The ethoxyquin derivatives with the lowest bond dissociation enthalpy, ionization potential, and proton affinity values were identified as the compounds with high radical scavenger activity. Results show that the substituents in the X1 position have high potential for synthesis of novel ethoxyquin derivatives. Results show that ethoxyquin derivatives can process their protective role via hydrogen atom transfer and sequential proton loss electron transfer mechanisms in the gas phase and solvent, respectively. The calculated reaction enthalpies of the substituted ethoxyquins have linear dependences with Hammett constants and energy of the highest occupied molecular orbital that can be utilized in the selection of suitable substituents for the synthesis of novel radical scavengers based on ethoxyquin. © 2013 Published by NRC Research Press.


Eslami M.,National University of Malaysia | Shareef H.,National University of Malaysia | Mohamed A.,National University of Malaysia | Khajehzadeh M.,Islamic Azad University at Anar
International Review of Electrical Engineering | Year: 2010

In this study, the application and performance comparison of particle swarm optimization (PSO) and Genetic algorithms (GA) optimization methods, for power system stabilizer (PSS) design is presented. Recently, GA and PSO methods have attracted considerable attention among different modern heuristic optimization methods. The GA has been popular in academia and the industry, mostly because of its intuitiveness, ease of implementation, and the capability to efficiently solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO method is a relatively new heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. Since the two approaches are supposed to find a solution to a given objective function but utilize different strategies and computational effort, it is appropriate to compare their performance. The design objective is to increase the power system stability. The design problem of the PSS parameters is formulated as an optimization problem and both PSO and GA optimization methods are used to search for optimal PSS parameters. The two-area multi-machine power system, under a wide range of system configurations and operation conditions is investigated to illustrate the performance of the both PSO and GA. The performance of both optimization methods is compared with the conventional power system stabilizer (CPSS) in terms of parameter accuracy and computational time. The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the methods in optimal tuning of PSS, to enhance power system stability. © 2010 Praise Worthy Prize S.r.l.- All rights reserved.


Eslami M.,Islamic Azad University at Anar | Shareef H.,National University of Malaysia | Mohamed A.,National University of Malaysia
International Review of Electrical Engineering | Year: 2011

This paper proposes a novel optimization technique for simultaneous coordinated designing of power system stabilizer (PSS) and static VAR compensator (SVC) as a damping controller in the multi-machine power system. PSO and chaos theory is hybridized to form a chaotic PSO (CPSO), which reasonably combines the population-based evolutionary searching ability of PSO and chaotic searching behavior. The coordinated design problem of PSS and SVC controllers over a wide range of loading conditions are formulated as a multi-objective optimization problem which is the aggregation of the two objectives related to the damping ratio and damping factor. The proposed damping controllers are tested on a weakly connected power system. The effectiveness of the proposed controllers is demonstrated through the eigenvalue analysis and nonlinear time-domain simulation. The results of these studies show that the proposed coordinated controllers have an excellent capability in damping power system inter- area oscillations and enhance greatly the dynamic stability of the power system. Moreover, it is superior to both the manually coordinated stabilizers of the PSS and the SVC damping controller. © 2011 Praise Worthy Prize S.r.l. - All righs reserved.


Eslami M.,National University of Malaysia | Shareef H.,National University of Malaysia | Khajehzadeh M.,Islamic Azad University at Anar
International Journal of Electrical Power and Energy Systems | Year: 2013

This paper integrates the artificial bee colony (ABC) algorithm with the sequential quadratic programming (SQP) to create the new hybrid optimization algorithm, ABC-SQP, for solving global optimization problems and damping of low frequency oscillations in power system stability analyses. The new algorithm combines the global exploration ability of ABC to converge rapidly to a near optimum solution and the accurate local exploitation ability of SQP to accelerate the search process and find an accurate solution. A set of well-known benchmark optimization problems is used to validate the performance of the ABC-SQP as a global optimization algorithm and to facilitate a comparison with the classical ABC. Numerical experiments demonstrate that the hybrid algorithm converges faster to a significantly more accurate final solution for a variety of benchmark test functions. Power system stabilizers and supplementary static VAR compensator controllers are designed for two-area-four-machine and five-area-sixteen-machine systems to illustrate the feasibility and effectiveness of the new method in power systems. The performance of the proposed ABC-SQP algorithm is compared with the classic ABC and the genetic algorithm (GA) through eigenvalue analysis and nonlinear time-domain simulation. The simulation results indicate that the controllers designed by the ABC-SQP perform better than those designed by ABC and GA. © 2013 Elsevier Ltd. All rights reserved.

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