Implementation of Particle Swarm Optimization for Maximum Power Absorption From Photovoltaic System Using Energy Extraction Circuit

2019 ◽  
Author(s):  
L.P. Sivakumar ◽  
S. Sivakumar ◽  
A. Prabha ◽  
A. Rajapandiyan
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Energy Extraction ◽  
Swarm Optimization ◽  
Power Absorption

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.

scholarly journals Application of mutant particle swarm optimization for MPPT in photovoltaic system

2020 ◽  
Vol 19 (2) ◽  
pp. 600
Author(s):  
Thom Thi Hoang ◽  
Thi Huong Le
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Operating Efficiency ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Power Point

<span>The P –V characteristic of a photovoltaic system (PVs) is non-linear and de-pends entirely on the extreme environmental condition, thus a large amount PV energy is lost in the environment. To enhance the operating efficiency of the PVs, a maximum power point tracking (MPPT) controller is normally equipped in the system. This paper proposes a new mutant particle swarm optimization (MPSO) algorithm for tracking the maximum power point (MPP) in the PVs. The MPSO-based MPPT algorithm not only surmounts the steady-state oscillation (SSO) around the MPP, but also tracks accurately the optimum power under different varying environmental conditions. To demonstrate the effectiveness of the proposed method, MATLAB simulations are implemented in three challenging scenarios to the PV system, including changing irradiation, load variation and partial shading condition (PSC). Furthermore, the obtained results are compared to some of the con-ventional MPPT algorithms, such as incremental conductance (INC) and clas-sical particle swarm optimization (PSO) in order to show the superiority of the proposed approach in improving the efficiency of PVs. </span>

scholarly journals Maximum Power Point Tracking Method for Photovoltaic System Based on Enhanced Particle Swarm Optimization Algorithm Under Partial Shading Condition

2020 ◽  
Vol 13 (6) ◽  
pp. 241-254
Author(s):  
Anas Kamil ◽  
◽  
Mahmoud Nasr ◽  
Shamam Alwash ◽  
◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Maximum Power ◽  
Global Maximum ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Power Point

The maximum power point tracking (MPPT) is an essential key to ensure that the photovoltaic (PV) system is operated at the highest possible power generation. This paper presents an efficient MPPT method for the PV system based on an enhanced particle swarm optimization algorithm to track the location of the global maximum power point, whatever its location changes in the search space under all environmental conditions, including the partial shading on strings. In this paper, the formulation of the conventional particle swarm optimization algorithm is enhanced to decrease the searching time and the oscillation of the generated output power as well as the power losses in the online tracking process. This enhancement can be achieved by utilizing a special time-varying weighting coefficient and removing the effect of some other coefficients in the conventional particle swarm optimization algorithm (PSO) that cause winding of the particles during the online tracking process. Test results verified the accuracy of the proposed method to track the global maximum power point with considering the effect of partial shading condition. The proposed method was also compared with other MPPT methods to verify the superiority of the proposed work. The obtained results reveal that the proposed method is effective to improve the tracking efficiency and reduce the tracking time and the number of iterations for the different irradiances and load conditions. The maximum number of iterations was 11 iteration and the highest tracking time was 0.273s with tracking efficiency of about 99.98%.

Sign in / Sign up

Export Citation Format

Share Document