scholarly journals An Emperor Penguin Optimization and Particle Swarm Optimization Control algorithm for PV with ZSI in Grid Connected System

2021 ◽  
Author(s):  
Vidhya M ◽  
Senthil Kumar R
Keyword(s):  
Particle Swarm Optimization ◽  
Pid Controller ◽  
Maximum Output Power ◽  
Hybrid Approach ◽  
Particle Swarm ◽  
Maximum Power ◽  
Emperor Penguin ◽  
Maximum Output ◽  
Swarm Optimization ◽  
Distributed Controller

Abstract In the paper, a distributed controller for the analysis of SEPIC and Z-Source Inverter (ZSI) based grid-connected Photovoltaic (PV) system. The PV systems are modeled, designed and implemented to given maximum power output with the help of proposed controller. In the paper, a distributed controller is designed to provide maximum output power and to working by changing irradiance and providing various range of active power. An enhanced controller is specified as the Fractional Order PID (FOPID) controller with aid of hybrid approach. The hybrid approach is consisting of Emperor Penguin Optimization (EPO) and Particle Swarm Optimization (PSO). FOPID controller is the advanced PID controller and it gives a better output and robustness than the traditional PID controller. To enhance the performance of the FOPID, the gain parameters are optimized with the utilization of hybrid approach. For achieving the optimal power management and maximum power tracking, the objective function is defined and specified their constraints also. Here, two various methods have been deliberated to changing the inverter operation with constant irradiance and varied irradiance. The proposed method is tested by using MATLAB/Simulink and it is contrasted with the previously developed methods like base model, Ant Colony Optimization (ACO) and PSO algorithm.

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 Anti-synchronization of discrete-time chaotic systems using optimization algorithms

2011 ◽  
pp. 143-147
Author(s):  
Mahdieh Adeli ◽  
Hassan Zarabadipoor
Keyword(s):  
Particle Swarm Optimization ◽  
Pid Control ◽  
Pid Controller ◽  
Chaotic Systems ◽  
Optimization Algorithms ◽  
Particle Swarm ◽  
Optimization Methods ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Modified Particle Swarm Optimization

In this paper, anti-synchronization of discrete chaotic system based on optimization algorithms are investigated. Different controllers have been used for anti-synchronization of two identical discrete chaotic systems. A proportional-integral-derivative (PID) control is used and its parameters is tuned by the four optimization algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO), modified particle swarm optimization (MPSO) and improved particle swarm optimization (IPSO). Simulation results of these optimization methods to determine the PID controller parameters to anti-synchronization of two chaotic systems are compared. Numerical results show that the improved particle swarm optimization has the best result.

Sign in / Sign up

Export Citation Format

Share Document