The PSO Based Global Maximum Power Point Tracker

Kircioğlu, Onur; Ünlü, Murat; Çamur, Sabri

doi:10.1109/ecai46879.2019.9041926

Cited by 6 publications

(2 citation statements)

References 5 publications

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“…With the evolution in intelligence technique, there have been a number of MPPT algorithms developed in recent years on the basis of soft computing. Among these evolutionary techniques, the likes of fuzzy logic control (FLC) [15], artificial neural network (ANN) [16], genetic algorithm (GA) [17], particle swarm optimization (PSO) [18] are found to be explored immensely in this new era of MPPT. According to Nemours and Chowdhury [19], a FLC based MPPT scheme has been implemented which shows good tracking capability for load variations as well.…”

Section: Introductionmentioning

confidence: 99%

Enhanced model based algorithm to reinforce PV system with dynamic MPPT capability

Ehtesham

2021

IJAAS

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<p>Photovoltaic (PV) power has emerged as the most attractive resource in form of a clean and green energy. However, one major challenge associated with PV interfacing is its intermittent output characteristic which varies dramatically with the operating conditions. Thus designing an effective maximum power point tracking (MPPT) algorithm is a key aspect for optimizing PV system performance. Numerous MPPT algorithms have been proposed earlier having their own specific advantages. However, these are found to have two major limitations which have to be essentially addressed. Firstly, they become ineffective in the dynamic conditions where there is rapid change in environmental parameters like insolation and temperature. Secondly, they fail to discriminate between global and local peaks under partial shading conditions. Therefore, to achieve a reliable and efficient system operation, this paper presents an enhanced model-based (MB) algorithm that overcomes both these deficiencies. Based on new governing equations and precised estimation technique, it predetermines the MPP analytically. First simulated results are obtained where it is tested for dynamic variations of all the three parameters. Then the experimental validation is carried out on a 2 KW installed panel where real time data is recorded through CR1000 data logger and environmental parameters are sensed with elements like pyranometer and humidity sensor. A large number of experimental results are obtained for tracked MPP in the dynamic conditions, which are then summarized in tabular forms. These are finally plotted and compared with simulated results to illustrate the effectiveness of proposed MB algorithm.</p>

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Section: Introductionmentioning

confidence: 99%

Enhanced model based algorithm to reinforce PV system with dynamic MPPT capability

Ehtesham

2021

IJAAS

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“…Among the evolutionary techniques based on soft computing, the likes of fuzzy logic control (FLC) (Rezk et al , 2019), artificial neural network (ANN) (Ali, 2018), genetic algorithm (GA) (Lee et al , 2018), particle swarm optimization (PSO) (Kirsioglu et al , 2019) are found to be explored immensely in this new era of MPPT. The biggest advantage of FLC based techniques is the speed of tracking, as they can reduce the settling time (Nemours and Choudhary, 2019).…”

Section: Introductionmentioning

confidence: 99%

Control techniques for enhancing performance of PV system under dynamic conditions

Ehtesham

Jamil

2020

IJESM

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Purpose The purpose of this paper is to focus on two major areas of concern for the Photovoltaic (PV) system, i.e. power quality and maximum power point tracking (MPPT). Novel control strategies have been proposed for both these issues, and their respective superiorities over the existing techniques have been established. On the other hand, as far as MPPT is concerned, two limitations are found in the available techniques. One is the inability of effective MPPT in dynamic conditions where the environmental parameters changes very rapidly. Second one is the ineffective tracking of global maxima under partial shading conditions. Design/methodology/approach Here, modified Kalman filtering approach has been applied for estimating the reference current of active power filter, incorporated for power quality improvement. The proposed Kalman algorithm introduces a weighted matrix, which advances the estimated values of state variables. This paper presents a simple and enhanced model-based (MB) MPPT algorithm that has the capability of tracking MPPT effectively in both these working conditions. The proposed MB algorithm uses the mathematical modelling, and based on precised estimation of parameters, it pre-determines the MPP analytically. Findings It has been tested successfully for dynamic variations of insolation, temperature and partial shading, where all these three parameters are rigorously varied over the full scale of practical values. The results have been also investigated experimentally and compared with the simulated one. A close matching of both the results has been shown through the plots, which validates the effectiveness of proposed algorithms. Originality/value This research paper is part of the original research work carried out in Lab. Simulated results are obtained in MATLAB/Simulink platform, whereas these are further validated experimentally on 2-KW panel constituted with all types of commercial products, namely, mono, poly and thin-film.

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A Comparative Study of Different MPPT Algorithms and Implementation of Single Axis Solar Tracker

Harini

Krishna

Reddy

et al. 2022

2022 International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics ( DISCOVER)

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The PSO Based Global Maximum Power Point Tracker

Cited by 6 publications

References 5 publications

Enhanced model based algorithm to reinforce PV system with dynamic MPPT capability

Enhanced model based algorithm to reinforce PV system with dynamic MPPT capability

Control techniques for enhancing performance of PV system under dynamic conditions

A Comparative Study of Different MPPT Algorithms and Implementation of Single Axis Solar Tracker

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