Header menu link for other important links
Investigation of Bacterial Foraging Algorithm Applied for PV Parameter Estimation, Selective Harmonic Elimination in Inverters and Optimal Power Flow for Stability
J Prasanth Ram, Ram J.P,
Published in Springer International Publishing
Volume: 16
Pages: 135 - 167
Inspired by the foraging behavior in bacteria (e-coli), Bacterial Foraging Algorithm (BFA) is designed for solving global optimization problems. Being unique in optimization, BFA has already received universal attention from researchers to apply for various engineering application. In order to investigate the BFA performance, mathematical equations for unimodal and multimodal functions are investigated for minimization problem and the optimal results are reported in this regard. Performance indices of BFA method are comprehensively gauged for all functions and a comparative study with standard algorithms like Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Geometric Search Optimization (GSO) Algorithm is reported. Finding more suitable to optimize non-linear problems, the modified BFA in fusion with nelder- meed method is also introduced. This chapter binds the collective knowledge on BFA that aids the researchers to apply for their research application. Taking BFA as their optimization tool, few authors have attained their research objectives in following areas: (i) PV parameter estimation (2) Selective Harmonic Elimination in inverters and (3) a modified BFA method for optimal power flow to maintain load stability. To have an interior understanding the applications, the simulation results of the above study are also presented more in detail. In all the cases, the due role of BFA to attain accurate results is always appreciated. © 2020, Springer Nature Switzerland AG.
About the journal
JournalData powered by TypesetNature-Inspired Methods for Metaheuristics Optimization Modeling and Optimization in Science and Technologies
PublisherData powered by TypesetSpringer International Publishing
Open Access0