scholarly journals Grid Connected PV System with MPPT Scheme Using Particle Swarm Optimization Technique

2021 ◽  
Vol 02 (02) ◽  
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Pv System ◽  
Swarm Optimization ◽  
Particle Swarm Optimization Technique

scholarly journals Particle Swarm Optimization Technique for Photovoltaic System

2020 ◽  
Vol 8 (5) ◽  
pp. 1448-1451
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Pv System ◽  
Swarm Optimization ◽  
Power Extraction ◽  
Pv Panel ◽  
Particle Swarm Optimization Technique

Day by day the dependency on renewable energy uses has been increasing because of no greenhouse emission and abundant in nature available freely, this paper, presents a comparative analysis of an optimization technique called Particle Swarm Optimization (PSO) along with Perturb & Observe (P&O) for the extraction of maximum power from the PV panel. The performances of P&O and PSO techniques were compared for different insolations and temperatures. A detailed and rigorous mathematical model along with simulation results and its performance for maximum power extraction from the panel were analyzed by using P&O and PSO. It has been observed that the maximum power obtained from PSO model is more than the maximum power obtained from P&O for different insolations and temperatures. Thus PSO is much better and more suitable for extracting maximum power from PV system.

Materialized View Selection Using Swap Operator Based Particle Swarm Optimization

2021 ◽  
Vol 13 (1) ◽  
pp. 58-73
Author(s):  
Amit Kumar ◽  
T. V. Vijay Kumar
Keyword(s):  
Particle Swarm Optimization ◽  
Data Warehouse ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Selection Problem ◽  
Data Repository ◽  
Swarm Optimization ◽  
View Selection ◽  
Particle Swarm Optimization Technique ◽  
Swap Operator

The data warehouse is a key data repository of any business enterprise that stores enormous historical data meant for answering analytical queries. These queries need to be processed efficiently in order to make efficient and timely decisions. One way to achieve this is by materializing views over a data warehouse. An n-dimensional star schema can be mapped into an n-dimensional lattice from which Top-K views can be selected for materialization. Selection of such Top-K views is an NP-Hard problem. Several metaheuristic algorithms have been used to address this view selection problem. In this paper, a swap operator-based particle swarm optimization technique has been adapted to address such a view selection problem.

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