6 Maximum power point tracking control under partial shading conditions using particle swarm optimization algorithm

2021 ◽  
pp. 185-214
Author(s):  
Jia Shun Koh ◽  
Rodney H. G. Tan ◽  
Wei Hong Lim
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Tracking Control ◽  
Particle Swarm Optimization Algorithm ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

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%.

scholarly journals Accelerated Particle Swarm Optimization for Photovoltaic Maximum Power Point Tracking under Partial Shading Conditions

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 623 ◽  
Author(s):  
Muhannad Alshareef ◽  
Zhengyu Lin ◽  
Mingyao Ma ◽  
Wenping Cao
Keyword(s):  
Particle Swarm Optimization ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Accelerated Particle Swarm Optimization ◽  
Power Point

This paper presents an accelerated particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm to track global maximum power point (MPP) of photovoltaic (PV) generation under partial shading conditions. Conventional PSO-based MPPT algorithms have common weaknesses of a long convergence time to reach the global MPP and oscillations during the searching. The proposed algorithm includes a standard PSO and a perturb-and-observe algorithm as the accelerator. It has been experimentally tested and compared with conventional MPPT algorithms. Experimental results show that the proposed MPPT method is effective in terms of high reliability, fast dynamic response, and high accuracy in tracking the global MPP.

scholarly journals Efficiency Improvement of Photovolataic by Using Maximum Power Point Tracking Based on Particle Swarm Optimization Algorithm Under Normal and Partial Shading

2018 ◽  
Vol 2 (2) ◽  
pp. 71
Author(s):  
Machmud Effendy ◽  
Khusnul Hidayat ◽  
Wahyu Dianto Pramana
Keyword(s):  
Particle Swarm Optimization ◽  
Maximum Power Point Tracking ◽  
Particle Swarm ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Photovoltaic (PV) is a device which is capable to converts solar irradiance into Direct Current (DC) electricity energy. To increase the power result of PV, it needs a method to track the Maximum Power Point(MPP) which is usually called Maximum power Point Tracking(MPPT). So that, the power result increased with low cost. The purpose of this research is to conduct MPPT modeling by Particle Swarm Optimization (PSO). The proposed method is implemented in DC to DC converter. This research used SEPIC converter. The purpose of using SEPIC converter is in order the output of current and voltage have smallest ripple. The modelling system is conducted by using MATLAB 2016b software to find out performance of PSO and SEPIC converter. The evaluation of PSO and SEPIC converter performance has been done. The simulation result shows that the proposed system has been working very well. The PSO has good accurateness in tracking and capable to to track the power produced by PV with velocity around ±4,2 seconds when in conditions STC, ±9,2 seconds when in conditions partial shading, despite a fluctuating irradiance change. While in SEPIC converter is able to reach efficiency of ≥ 80%. 

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