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
Modeling and performance analysis of nuclear-renewable micro hybrid energy system based on different coupling methods
TL;DR: In this article, the authors proposed three methods, called Direct Coupling, Single Resource and Multiple Products-based Coupling and Multiple Resources and Multiple products-based coupling, of hybridization for optimal planning of nuclear-Renewable Micro Hybrid Energy System (N-R MHES).
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Micro Nuclear Reactors: Potential Replacements for Diesel Gensets within Micro Energy Grids
TL;DR: In this paper, the authors investigated an alternative source as an economical and environmental replacement for diesel gensets that can reduce GHG emissions and ensure system reliability in an off-grid micro energy grid.
Journal ArticleDOI
Artificial Intelligence and Bio-Inspired Soft Computing-Based Maximum Power Plant Tracking for a Solar Photovoltaic System under Non-Uniform Solar Irradiance Shading Conditions—A Review
Amjad Ali,Kashif Irshad,Mohammad Farhan Khan,Moinul Hossain,Ibrahim N. A. Al-Duais,Muhammad Zeeshan Malik +5 more
TL;DR: In this article, a comprehensive review of articles on soft computing-based maximum power point tracking (SC-MPPT) techniques under non-uniform irradiance conditions along with their operating principles, block/flow diagram is presented.
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Motion planning with adaptive motion primitives for modular robots
TL;DR: A novel motion planning algorithm for modular robots moving in environments with diverse terrain conditions and a novel schema called RRT-AMP (Rapidly Exploring Random Trees with Adaptive Motion Primitives) for adapting the motion primitives is introduced.
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Optimal Sizing an SPV/Diesel/Battery Hybrid System for a Remote Railway Station in India
Anula Khare,Saroj Rangnekar +1 more
TL;DR: In this article, the authors present a methodology for calculation of the sizing and optimization of a stand-alone SPV/diesel/battery hybrid system proposed for a small railway station.
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.