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Proceedings ArticleDOI

Load flow solution using hybrid particle swarm optimization

TLDR
In this article, an application of particle swarm optimization (PSO) in solving the load flow problem as an optimization problem is presented, which is usually solved using conventional numerical techniques like Newton-Raphson (NR) or GaussSeidel (GS) methods.
Abstract
Load flow (LF) is an important tool in the planning and operation of power systems. It is usually solved using conventional numerical techniques like Newton-Raphson (NR) or GaussSeidel (GS) methods. This paper presents an application of particle swarm optimization (PSO) in solving the load flow problem as an optimization problem. Examples on test systems are given to demonstrate the validity and applicability of the proposed method.

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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

Maximum loadability of power systems using hybrid particle swarm optimization

TL;DR: In this paper, the authors utilized the newly developed evolutionary particle swarm optimization in solving the optimization problem of finding the margin from the current operating point to the maximum loading point of the system.
Journal ArticleDOI

Maximum loadability limit of power system using hybrid differential evolution with particle swarm optimization

TL;DR: The application of DEPSO algorithm to determine the maximum loadability limit of power system is presented and statistical measures like best, mean, standard deviation of results and average computation time over 20 independent trials are considered here.
Journal ArticleDOI

Application of high-order Newton-like methods to solve power flow equations

TL;DR: Using the third-, fourth- and fifth-order Newton-like methods to solve the PF problem in power systems can significantly reduce the computation time and the number of iterations.
Proceedings ArticleDOI

Implementation of non-traditional optimization techniques (PSO, CPSO, HDE) for the optimal load flow solution

TL;DR: This paper presents an approach to obtain the optimal load flow solution using three different intelligent techniques such as particle Swarm optimization (PSO), crazy particle swarm optimization (CPSO) and hybrid differential evolution (HDE) subject to various system constraints.
References
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Journal ArticleDOI

Use of intelligent-particle swarm optimization in electromagnetics

TL;DR: The Intelligent Particle Swarm Optimization (IPSO) algorithm as mentioned in this paper uses concepts such as group experiences, unpleasant memories (tabu to be avoided), local landscape models based on virtual neighbors, and memetic replication of successful behavior parameters.

Use of intelligent-particle swarm optimization in electromagnetics. IEEE Trans Mag

TL;DR: The paper describes a new stochastic heuristic algorithm for global optimization, called intelligent-particle swarm optimization (IPSO), which offers more intelligence to particles by using concepts such as: group experiences, unpleasant memories, local landscape models based on virtual neighbors, and memetic replication of successful behavior parameters.
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