A Comparison of Perturb &amp; Observe and Fuzzy-Logic Based MPPT Methods for Uniform Environment Conditions

Kandemir, Ekrem; Çetin, Numan Sabit; Börekçi, Selim

doi:10.21533/pen.v5i1.67

Cited by 7 publications

(9 citation statements)

References 8 publications

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“…Among the much used algorithms, we have the P&O, used by many authors. Its few code lines and simplicity make it easy to deploy [9]. The disadvantage of this algorithm is that in some cases, especially under partial shading, the algorithm cannot find the maximum power point.…”

Section: Pando Algorithm For Mppt Controlmentioning

confidence: 99%

A cascaded H-bridge multilevel inverter with photovoltaic MPPT control

Ezzouitine¹,

Boulezhar²,

Afou³

2019

PEN

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This article presents the five levels H-Bridge cascaded multilevel inverter with photovoltaic MPPT control. The power source is composed of photovoltaic panels used as DC inputs for the cascaded H-Bridge Multilevel Inverter. The present work aims to present a control strategy to produce the best output quality possible. The algorithm P&O extract from the panels the maximum power while the supervision system tends to control the DC levels in the CHMLI inputs. Each panel possesses its own MPPT module and the cascaded H-Bridge Multi-Level Inverter uses the modules as entries to produce a staircase waveform output. A simulation using matlab/simulink is realized to verify the system performance.

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Section: Pando Algorithm For Mppt Controlmentioning

confidence: 99%

A cascaded H-bridge multilevel inverter with photovoltaic MPPT control

Ezzouitine¹,

Boulezhar²,

Afou³

2019

PEN

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“…Figure 1 displays a PV cell equivalent circuit model and a PV panel with 9 PV cells. [17]. Variation of solar irradiance and/or temperature affects PV panel power value.…”

Section: Pv Modelling and Equivalent Circuit Modelmentioning

confidence: 99%

Conventional and Soft-Computing Based MPPT Methods Comparisons in Direct and Indirect Modes for Single Stage PV Systems

Kandemir¹,

Börekçi²,

Çetin³

2018

ElAEE

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Improving power efficiency for a Photovoltaic (PV) system becomes important issue for researchers. To achieve maximum power extraction from PV panels, different kinds of Maximum Power Point Tracking (MPPT) methods have been investigating in the literature. In all techniques, direct and indirect mode approaches can be implemented. Based on the physical application of the PV system under different condition, the efficiency and convergence speed become important. In this paper, a grid connected simple single stage PV system by using different MPPT methods in direct and indirect modes has been analysed to find out the best mode and technique for a specific PV system application. Three of the most preferred MPPT algorithms: the perturb & observe (P&O), incremental conductance (Inc. Cond.) and fuzzy logic control (FLC) have been performed in MATLAB Simulink and compared their performance in direct and indirect modes in terms of convergence speed and tracking accuracy by the proposed single stage PV system. The results show that direct mode MPPTs have better tracking accuracy but less convergence speed than indirect MPPTs. Therefore, indirect mode MPPTs present better performance for the rapid atmospheric changing applications. Additionally, FLC based MPPT exhibits almost best tracking performance for direct and indirect modes.

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“…The main purpose of this study is to investigate and test whether the accuracy of probabilistic credit risk assessment of corporates, evaluated with logistic regression, can be improved using soft and hard data modeling, followed by soft-hard data fusion, in particular using Uncertainty Balance Principle. In literature one can find various methods on how to integrate fuzzy and random data in meaningful ways [34][35][36]53], as well as about the area of "random fuzzy sets" and "fuzzy random variables", as well as various "fuzzy" applications [e.g., 1-2, 5, 11-20, 22-24, 33, 37, 39-45, 47-52]. However, this study does not deal with aforementioned.…”

Section: Introductionmentioning

confidence: 99%

Soft-hard data fusion using uncertainty balance principle – Evidence from corporate credit risk assessment in commercial banking

Brkic¹,

Hodzic²,

Dzanic³

2019

PEN

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This study introduces Uncertainty Balance Principle (UBP) as a new concept/method for incorporating additional soft data into probabilistic credit risk assessment models. It shows that soft banking data, used for credit risk assessment, can be expressed and decomposed using UBP and thus enabling more uncertainty to be handled with a precise mathematical methodology. The results show that this approach has relevance to credit risk assessment models in the sense that it proved its usefulness for the purpose of soft-hard data fusion, it modified Probability of Default with soft data modeled using possibilistic (fuzzy) distributions and fused with hard probabilistic data via UBP and it obtained better classification prediction results on the overall sample. This was demonstrated on a simple example of one soft variable, two experts and a small sample and thus this is an approach/method that requires further research, enhancements and rigorous statistical testing for the application to a complete scoring and/or rating system

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A Comparison of Perturb & Observe and Fuzzy-Logic Based MPPT Methods for Uniform Environment Conditions

Cited by 7 publications

References 8 publications

A cascaded H-bridge multilevel inverter with photovoltaic MPPT control

A cascaded H-bridge multilevel inverter with photovoltaic MPPT control

Conventional and Soft-Computing Based MPPT Methods Comparisons in Direct and Indirect Modes for Single Stage PV Systems

Soft-hard data fusion using uncertainty balance principle – Evidence from corporate credit risk assessment in commercial banking

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