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Journal ArticleDOI

A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation

TLDR
This work presents a new algorithm based on the foraging behavior of E. coli bacteria in the authors' intestine to estimate the harmonic components present in power system voltage/current waveforms, presenting the hybrid method.
Abstract
Harmonic estimation for a signal distorted with additive noise has been an area of interest for researchers in many disciplines of science and engineering. This work presents a new algorithm based on the foraging behavior of E. coli bacteria in our intestine to estimate the harmonic components present in power system voltage/current waveforms. The basic foraging strategy is made adaptive, through a Takagi-Sugeno fuzzy scheme, depending on the operating condition to make the convergence faster. Besides, the harmonic estimation is linear in amplitude and nonlinear in phase. As the proposed algorithm does not rely on Newton-like gradient descent methods, this is used for phase estimation whereas the linear least square scheme estimates the amplitude, thereby presenting the hybrid method. The improvement in %error, as well as the processing time compared with the conventional discrete Fourier transform and genetic algorithm method is demonstrated in this paper. Besides, the performance is quite acceptable even in the presence of decaying dc component as well as to change in amplitude and phase angle of harmonic components.

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Citations
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Journal ArticleDOI

Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems

TL;DR: This paper presents a detailed overview of the basic concepts of PSO and its variants, and provides a comprehensive survey on the power system applications that have benefited from the powerful nature ofPSO as an optimization technique.
Journal ArticleDOI

A survey on nature inspired metaheuristic algorithms for partitional clustering

TL;DR: An up-to-date review of all major nature inspired metaheuristic algorithms employed till date for partitional clustering and key issues involved during formulation of various metaheuristics as a clustering problem and major application areas are discussed.
Book ChapterDOI

Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications

TL;DR: This chapter presents a new adaptive variant of BFOA, where the chemotactic step size is adjusted on the run according to the current fitness of a virtual bacterium, and discusses the hybridization of B FOA with other optimization techniques.
Journal ArticleDOI

New inspirations in swarm intelligence: a survey

TL;DR: This tutorial highlights the most recent nature-based inspirations as metaphors for swarm intelligence meta-heuristics and describes the biological behaviours from which a number of computational algorithms were developed.
Journal ArticleDOI

Maiden Application of Bacterial Foraging-Based Optimization Technique in Multiarea Automatic Generation Control

TL;DR: In this article, a maiden attempt is made to examine and highlight the effective application of bacterial foraging (BF) to optimize several important parameters in automatic generation control (AGC) of interconnected three unequal area thermal systems, such as integral controller gains (KIi) for the secondary control, governor speed regulation parameters (Ri), and frequency bias parameters (Bi), and compare its performance to establish its superiority over GA and classical methods.
References
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Journal ArticleDOI

Biomimicry of bacterial foraging for distributed optimization and control

TL;DR: A computer program that emulates the distributed optimization process represented by the activity of social bacterial foraging is presented and applied to a simple multiple-extremum function minimization problem and briefly discusses its relationship to some existing optimization algorithms.
Journal ArticleDOI

Optimal power flow using particle swarm optimization

TL;DR: In this paper, an evolutionary-based approach to solve the optimal power flow (OPF) problem is presented. And the proposed approach has been examined and tested on the standard IEEE 30bus test system with different objectives that reflect fuel cost minimization, voltage profile improvement, and voltage stability enhancement.
Journal ArticleDOI

Optimal des'ign of Power System Stabilizers Using Particle Swarm Opt'imization

TL;DR: In this paper, a novel evolutionary algorithm-based approach to optimal design of multimachine power system stabilizers (PSSs) is proposed, which employs the particle swarm optimization (PSO) technique to search for optimal settings of PSS parameters.
Journal ArticleDOI

Nonlinear parameter estimation via the genetic algorithm

TL;DR: A modified genetic algorithm is used to solve the parameter identification problem for linear and nonlinear IIR digital filters and the estimation error is shown to converge in probability to zero.
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