Journal ArticleDOI
Review article: A review of particle swarm optimization and its applications in Solar Photovoltaic system
Anula Khare,Saroj Rangnekar +1 more
- Vol. 13, Iss: 5, pp 2997-3006
TLDR
Issues related to parameter tuning, dynamic environments, stagnation, and hybridization are discussed, including a brief review of selected works on particle swarm optimization, followed by application of PSO in Solar Photovoltaics.Abstract:
Particle swarm optimization is a stochastic optimization, evolutionary and simulating algorithm derived from human behaviour and animal behaviour as well. Special property of particle swarm optimization is that it can be operated in continuous real number space directly, does not use gradient of an objective function similar to other algorithms. Particle swarm optimization has few parameters to adjust, is easy to implement and has special characteristic of memory. Paper presents extensive review of literature available on concept, development and modification of Particle swarm optimization. This paper is structured as first concept and development of PSO is discussed then modification with inertia weight and constriction factor is discussed. Issues related to parameter tuning, dynamic environments, stagnation, and hybridization are also discussed, including a brief review of selected works on particle swarm optimization, followed by application of PSO in Solar Photovoltaics.read more
Citations
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Journal ArticleDOI
Review on applications of particle swarm optimization in solar energy systems
TL;DR: The literature review used in this study indicates that the PSO is a very promising method to enhance the performance of solar energy systems.
Journal ArticleDOI
Metaheuristic algorithms for PV parameter identification: A comprehensive review with an application to threshold setting for fault detection in PV systems
Dhanup S. Pillai,N. Rajasekar +1 more
TL;DR: Inspired by this review, an unidentified gateway between parameter extraction and fault detection in PV systems have been identified; and this review is a valuable gathering of statistics from the various researches carried out in PV parameter extraction which can assist enhanced researches for fault detection.
Journal ArticleDOI
Geometric optimization on optical performance of parabolic trough solar collector systems using particle swarm optimization algorithm
TL;DR: It is revealed that optimization results agree well with the reference data (Cheng et al., 2014), proving that the PSO–MCRT method and model used in the present study are feasible and reliable.
Journal ArticleDOI
Particle Swarm Optimization: A Comprehensive Survey
TL;DR: Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms in the literature as mentioned in this paper , and many researchers have been modifying it resulting in a large number of PSO variants with either slightly or significantly better performance.
Journal ArticleDOI
Identification of unknown parameters of a single diode photovoltaic model using particle swarm optimization with binary constraints
Sangram Bana,R.P. Saini +1 more
TL;DR: A particle swarm optimization (PSO) technique with binary constraints has been presented to identify the unknown parameters of a single diode model of solar PV module and it has been found that PSO algorithm yields a high value of accuracy irrespective of temperature variations.
References
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Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Proceedings ArticleDOI
A new optimizer using particle swarm theory
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
Proceedings ArticleDOI
A modified particle swarm optimizer
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.
Proceedings ArticleDOI
Particle swarm optimization: developments, applications and resources
TL;DR: Developments in the particle swarm algorithm since its origin in 1995 are reviewed and brief discussions of constriction factors, inertia weights, and tracking dynamic systems are included.
Book ChapterDOI
Parameter Selection in Particle Swarm Optimization
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: This paper first analyzes the impact that inertia weight and maximum velocity have on the performance of the particle swarm optimizer, and then provides guidelines for selecting these two parameters.