Evaluation of Incremental conductance and Firefly algorithm for PV MPPT application under partial shade condition

Yetayew, Tefera T.; Jyothsna, T. R.; Kusuma, G.

doi:10.1109/icpes.2016.7584089

Cited by 26 publications

(17 citation statements)

References 17 publications

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“…The behaviors of fireflies is that they communicate, search for prey, and find mates. In order to simplify the algorithm, three assumptions are considered (Yang, 2010;Yetayew et al, 2016;Dhivya and Kumar, 2017;Teshome et al, 2017): 1. There is no gender in fireflies and every firefly is attracted to other fireflies without considering their gender.…”

Section: Firefly Algorithmmentioning

confidence: 99%

Pv Si̇stemlerde Kismi̇ Gölgelenme Koşullarinda Esnek Hesaplama Tabanli Maksi̇mum Güç Noktasi İzleme Tekni̇kleri̇ni̇n Karşilaştirilmasi

Bingöl

Özkaya

2019

Mühendislik Bilimleri Ve Tasarım Dergisi

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Nowadays, solar or photovoltaic energy is the most commonly used renewable energy resources in the world. Despite its advantages such as freely available, low maintenance cost, pollution-free, inexhaustible, and reliable, its low conversion efficiency is a major drawback. To increase the efficiency of the photovoltaic system, all photovoltaic modules in the array must be operated at maximum power point. Therefore, maximum power point tracking technique is used for predicting and tracking the maximum power point. In the literature, maximum power point tracking techniques are generally classified as soft computing and conventional. Soft computing techniques are more preferred from both of them, because they can accurately track maximum power point of photovoltaic systems. In this study, an extensive review of soft computing based maximum power point tracking techniques under partial shading conditions until today is presented. The techniques are compared from the point of photovoltaic array dependency, sensors required, tracking efficiency, tracking speed, algorithm complexity, and oscillation around maximum power point.

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Section: Firefly Algorithmmentioning

confidence: 99%

Pv Si̇stemlerde Kismi̇ Gölgelenme Koşullarinda Esnek Hesaplama Tabanli Maksi̇mum Güç Noktasi İzleme Tekni̇kleri̇ni̇n Karşilaştirilmasi

Bingöl

Özkaya

2019

Mühendislik Bilimleri Ve Tasarım Dergisi

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“…Artificial intelligence (AI)-based MPPT algorithms are proposed in [26][27][28][29], which include particle swarm optimization (PSO), ant colony, and firefly algorithms. The PSO algorithm is popular for MPPT because of its simplicity of the mathematical structure and implementation [30,31].…”

Section: Introductionmentioning

confidence: 99%

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

Alshareef

Lin

et al. 2019

Energies

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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.

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“…Flow chart of conventional INC algorithm Basic idea of incremental conductance method on a P-V curve of a shows the basic principle of INC algorithm on the slope of a P-V curve of a solar panel. The idea behind INC algorithm resides on the fact that the derivative of the power with respect to the voltage becomes zero at MPP; negative at right side of MPP and positive at left side of MPP[5] [6]. The PV panel characteristics may undergo any one of the following three conditions during the initial operation.…”

mentioning

confidence: 99%

Study of the Importance of MPPT Algorithm for Photovoltaic Systems under Abrupt Change in Irradiance and Temperature Conditions

Pilakkat

Kanthalakshmi

2020

Wseas Transactions on Power Systems

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In order to understand the importance of MPPT algorithms, modeling and simulation of a PV system with and without MPPT algorithm using MATLAB/SIMULINK under different irradiance and temperature variations are analyzed in this chapter. The MPPT technique used is Incremental Conductance (INC) algorithm. First of all, the P-V (power-voltage) and I-V (Current-Voltage) characteristics are noticed for different values of solar irradiance while keeping the cell temperature constant. Later on, for different temperature values with constant irradiance levels the characteristics of PV panel has been studied. The effect of temperature and irradiance on power, current, voltage and duty ratio of the PV system with and without INC MPPT algorithm is analyzed for understanding the importance of MPPT techniques in PV systems

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Evaluation of Incremental conductance and Firefly algorithm for PV MPPT application under partial shade condition

Cited by 26 publications

References 17 publications

Pv Si̇stemlerde Kismi̇ Gölgelenme Koşullarinda Esnek Hesaplama Tabanli Maksi̇mum Güç Noktasi İzleme Tekni̇kleri̇ni̇n Karşilaştirilmasi

Pv Si̇stemlerde Kismi̇ Gölgelenme Koşullarinda Esnek Hesaplama Tabanli Maksi̇mum Güç Noktasi İzleme Tekni̇kleri̇ni̇n Karşilaştirilmasi

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

Study of the Importance of MPPT Algorithm for Photovoltaic Systems under Abrupt Change in Irradiance and Temperature Conditions

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