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Articles by S.M. Abd-Elazim
Total Records ( 2 ) for S.M. Abd-Elazim
  E.S. Ali and S.M. Abd-Elazim
  Social foraging behavior of Escherichia coli bacteria has recently been explored to develop a novel algorithm for distributed optimization and control. The Bacterial Foraging Optimization Algorithm (BFOA) as it is called now is currently gaining popularity in the community of researchers for its effectiveness in solving certain difficult real world optimization problems. This study proposes BFOA based Static Var Compensator (SVC) for the suppression of oscillations in power system. The proposed design problem of SVC over a wide range of loading conditions and different disturbances is formulated as an optimization problem. BFOA is employed to search for optimal controller parameters by minimizing the time domain objective function. The performance of the proposed technique has been evaluated with the performance of the conventional controller tuned by Ziegler-Nichols (ZN) and Genetic Algorithm (GA) in order to demonstrate the superior efficiency of the proposed BFOA in tuning SVC controller. Simulation results emphasis on the better performance of the optimized SVC controller based on BFOA in compare to optimized SVC controller based on GA and conventional one over wide range of operating conditions.
  E.S. Ali and S.M. Abd-Elazim
  Social foraging behaviour of Escherichia coli bacteria has recently been explored to develop a novel algorithm for optimization and control. One of the major driving forces of Bacterial Foraging Optimization Algorithm (BFOA) is the chemotactic movement of a virtual bacterium that models a trial solution of the optimization problem. However during the process of chemotaxis, the BFOA depends on random search directions which may lead to delay in reaching the global solution. This study comes up with a hybrid approach involving Particle Swarm Optimization (PSO) and BFOA algorithm called Bacterial Swarm Optimization (BSO) for designing Static Synchronous Series Compensator (SSSC) in a power system. In BSO, the search directions of tumble behaviour for each bacterium are oriented by the individualís best location and the global best location of PSO. The proposed hybrid algorithm has been extensively compared with BFOA and PSO. Simulation results have shown the validity of the proposed BSO in tuning SSSC compared with BFOA and PSO. Moreover, the results are presented to demonstrate the effectiveness of the proposed controller to improve the power system stability over a wide range of loading conditions.
 
 
 
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