Synergy of Bacterial Foraging Algorithm and Particle Swarm optimization for Secure Power System Operation

2019 ◽  
Author(s):  
Ahmed Hafez
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Particle Swarm ◽  
System Operation ◽  
Swarm Optimization ◽  
Power System Operation ◽  
Bacterial Foraging ◽  
Bacterial Foraging Algorithm

Bacterial Foraging Algorithm Based on Quantum-Behaved Particle Swarm Optimization for Global Optimization

2013 ◽  
Vol 655-657 ◽  
pp. 948-954 ◽  
Author(s):  
Ling Li ◽  
Xiong Fa Mai
Keyword(s):  
Global Optimization ◽  
Particle Swarm Optimization ◽  
Local Minimum ◽  
Random Search ◽  
Particle Swarm ◽  
Bacterial Foraging Optimization ◽  
Swarm Optimization ◽  
Bacterial Foraging ◽  
Bacterial Foraging Algorithm ◽  
Simulation Results

Bacterial Foraging Optimization(BFA) algorithm has recently emerged as a very powerful technique for real parameter optimization,but the E.coli algorithm depends on random search directions which may lead to delay in reaching the global solution.The quantum-behaved particle swarm optimization (QPSO) algorithm may lead to possible entrapment in local minimum solutions. In order to overcome the delay in optimization and to further enhance the performance of BFA,a bacterial foraging algorithm based on QPSO(QPSO-BFA) is presented.The new algorithm is proposed to combines both algorithms’ advantages in order to get better optimization values. Simulation results on eight benchmark functions show that the proposed algorithm is superior to the BFA,QPSO and BF-PSO.

scholarly journals Hybrid Bacteria Foraging Particle Swarm Optimization based Optimal Reactive Power Dispatch for the Alleviation of Voltage Deviations

2019 ◽  
Vol 9 (2) ◽  
pp. 5350-5354
Keyword(s):  
Particle Swarm Optimization ◽  
Hybrid Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Bacterial Foraging ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Bacterial Foraging Algorithm ◽  
Reactive Power Dispatch

This paper presents a hybrid algorithm for optimal reactive power dispatch by combining two popular evolutionary computation algorithms; Bacterial Foraging algorithm and Particle Swarm Optimization. The Hybrid algorithm combines velocity and position updating strategy of Particle swarm optimization algorithm and reproduction and elimination dispersal of Bacterial foraging algorithm. The proposed algorithm is applied to solve optimal power flow with the objective of minimization of Sum of squares of voltage deviations of all load buses. The proposed approach has been evaluated on a standard IEEE 30 bus test system and 24 bus EHV southern region equivalent Indian power system. The results obtained by the proposed Hybrid algorithm are compared with their basic counter parts and superiority of the proposed hybrid algorithm is demonstrated

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