Bacterial Foraging Technique-Based Optimized Active Power Filter for Load Compensation

Mishra, Sukumar; Bhende, Chandrashekhar N.

doi:10.1109/tpwrd.2006.876651

Cited by 211 publications

(95 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The BIA inspired from the foraging behaviour of bacteria (E.coli) is called Bacterial Foraging Optimization Algorithm (BFOA), proposed by Passino ([23]; [24]). Since its inception BFOA has been widely accepted as global optimization algorithm for real world problems such as transmission loss reduction [25], learning of artificial neural networks [26], active power filters [27], optimal controller design ( [23]), and harmonic estimation [28]. Foraging is a process of moving the bacteria towards more nutrients region through neutral medium, and avoiding the poisonous substances.…”

Section: Bacterial-foraging Optimization Algorithmmentioning

confidence: 99%

Distribution Network Reconfiguration for Power Loss Minimization Using Bacterial Foraging Optimization Algorithm

Mam¹,

G²,

Saxena³

2016

International Journal of Engineering and Manufacturing

View full text Add to dashboard Cite

This paper presents a distribution network reconfiguration based on bacterial foraging optimization algorithm (BFOA) along with backward-forward sweep (BFS) load flow method and geographical information system (GIS). Distribution network reconfiguration (DNR) is a complex, non-linear, combinatorial, and nondifferentiable constrained optimization process aimed at finding the radial structure that minimized network power loss while satisfying all operating constraints. BFOA is used to obtain the optimal switching configuration which results in a minimum loss, BFS is used to optimize the deviation in node voltages, and GIS is used for planning and easy analysis purposes. Simulation is performed on the 33-bus system and results are compared with the other approaches. The obtained results show that the proposed approach is better in terms of efficiency and having good convergence criteria.

show abstract

Section: Bacterial-foraging Optimization Algorithmmentioning

confidence: 99%

Distribution Network Reconfiguration for Power Loss Minimization Using Bacterial Foraging Optimization Algorithm

Mam¹,

G²,

Saxena³

2016

International Journal of Engineering and Manufacturing

View full text Add to dashboard Cite

show abstract

“…The E-coli bacterium has a control system that enables it to search for food and try to avoid noxious substances [ [18][19][20][21][22]. This bacteria distributed motion can modeled as four stages.…”

Section: Bacterial Foraging Optimization Algorithmmentioning

confidence: 99%

Paper Machine Industrial Analysis on Moisture Control Using BF-PSO Algorithm and Real Time Implementation Setup through Embedded Controller

Kumar¹,

Mahadevan²

2016

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

-Proportional Integral Derivative (PID) controller tuning is an area of interest for researchers in many areas of science and engineering. This paper presents a new algorithm for PID controller tuning based on a combination of bacteria foraging and particle swarm optimization. BFO algorithm has recently emerged as a very powerful technique for real parameter optimization. To overcome delay in an optimization, combine the features of BFOA and PSO for tuning the PID controller. This new algorithm is proposed to combine both the algorithms to get better optimization values. The real time prototype model of paper machine is designed and controlled by using PIC microcontroller embedded with the programming in C language.

show abstract

“…In 2002, inspired by the researches on the foraging behavior of E. coli bacteria, Prof. K. M. Passino proposed Bacterial Foraging Optimization Algorithm (BFOA) [4], which also has been applied to many engineering problems [5][6][7][8][9]. In the foraging process, if bacteria find no better food in the original direction, it will turn to a new direction.…”

Section: B Social Foragingmentioning

confidence: 99%

Adaptive Bacterial Foraging Optimization Algorithm Based on Social Foraging Strategy

Shen¹,

Zhu²

2014

JNW

View full text Add to dashboard Cite

Bacterial Foraging Technique-Based Optimized Active Power Filter for Load Compensation

Cited by 211 publications

References 12 publications

Distribution Network Reconfiguration for Power Loss Minimization Using Bacterial Foraging Optimization Algorithm

Distribution Network Reconfiguration for Power Loss Minimization Using Bacterial Foraging Optimization Algorithm

Paper Machine Industrial Analysis on Moisture Control Using BF-PSO Algorithm and Real Time Implementation Setup through Embedded Controller

Adaptive Bacterial Foraging Optimization Algorithm Based on Social Foraging Strategy

Contact Info

Product

Resources

About