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
Niching particle swarm optimization techniques for multimodal buckling maximization of composite laminates
TL;DR: The ring topology based PSO without any niching parameter is suitable and reliable for multimodal optimization of composite structures in comparison with SPSO, FER-PSO and the variant of LIPS.
Journal ArticleDOI
Analysis of Dynamic Characteristic for Solar Arrays in Series and Global Maximum Power Point Tracking Based on Optimal Initial Value Incremental Conductance Strategy under Partially Shaded Conditions
TL;DR: Based on circuit analysis, the number of peak points can be determined by short-circuit currents and maximum-power point currents of all the arrays in series, and the principle is established based on which the peak points are to be determined as mentioned in this paper.
Journal ArticleDOI
The impact of using Particle Swarm Optimisation on the operational characteristics of a stand-alone hydrogen system with on-site water production
TL;DR: The validity of applying Particle Swarm Optimisation (PSO) to size and optimise hydrogen systems is demonstrated and improvements with a PSO optimised PMS depend on system scale, with greater relative benefits arising at smaller scales.
Journal ArticleDOI
Adaptive particle swarm optimization with population diversity control and its application in tandem blade optimization
Zhaoyun Song,Bo Liu,Hao Cheng +2 more
TL;DR: The results indicate APSO-PDC has more preferable searching accuracy, searching reliability, and convergence speed than the other well-established particle swarm optimization variants and shows satisfactory performance in optimizing tandem blade.
Optimal allocation of PV systems to minimize losses in distribution networks using GA and PSO: Masirah Island case study
Mohammed Albadi,Hisham M. Soliman,Mahmood Sabih Awlad Thani,Ahmed Al-Alawi,Said Al-Ismaili,Ahmed Al-Nabhani,Haitham Baalawi +6 more
TL;DR: This study addresses the issue of photovoltaic (PV) systems optimal allocation in electric distribution network by using particle swarm optimization (PSO) and genetic algorithms (GA) to minimize system losses while improving voltage profile.
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.