A fuzzy logic based MPPT method for solar power generation

Due to the nonlinear nature of photovoltaic (PV) cells and the dependence of the maximum achievable power on environmental conditions, a robust nonlinear controller is essential to warrant maximum power point tracking (MPPT) by managing the nonlinearities of the system and making it robust against varying environmental conditions. Most methods used to obtain MPPT have some disadvantages; one of them is the oscillation around the operating point. In this paper, to minimize these problems, a robust nonlinear sliding mode controller based on the power curve of a PV (SMC-PCPV) was proposed to determine the maximum power point (MPP) of a PV panel, for a quasi Z-source inverter (qZSI) as a single-stage inverter. Single-stage inverters have lower components and prices, smaller sizes, more simplicity, and higher efficiency than two-stage inverters. One of the important features of this controller is its ease of implementation compared to other methods presented in the articles. To show the effectiveness and robustness of the proposed scheme, the SMC-PCPV was carried out on computer simulations and laboratory prototypes. The simulation and experimental results showed that the proposed controller was properly resistant to changes in input parameters, such as temperature and radiation, and controlled the converter at the best point to obtain the most power from the PV panel, and it had good speed in response to the changing environmental condition.

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“…It also had an acceptable ST and ripple. 2.17 2.9 3.2 0.23% FLBC [39] 2.17 3 8.4 1.2% SMC-PCPV 0.9 3.1 3.84 1.07%…”

Section: Comparison Of the Dynamic Responsementioning

confidence: 99%

Applying a Sliding Mode Controller to Maximum Power Point Tracking in a Quasi Z-Source Inverter Based on the Power Curve of a Photovoltaic Cell

2022

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“…Therefore, artificial intelligence-based techniques have been used to address these problems [27,28]. The FL technique is attractive in PV systems because it does not require complex mathematics, its efficiency and convergence speed are higher than the classic techniques, and less oscillation around the MPP [29,30]. However, this technique still suffers from the problem of drifting from the MPP under sudden changes in climatic conditions.…”

Section: Introductionmentioning

confidence: 99%

Comparative Performance Analysis of a Feed-Forward Neural Network-Based MPPT for Rapidly Changing Climatic Conditions

Omar

2023

Konya Journal of Engineering Sciences

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Rapid and abrupt changes in climatic conditions present a challenge to classical MPPT techniques as they drift from the MPP, resulting in loss of power. This paper presents a new MPPT technique based on a feed-forward artificial neural network (FFANN) and a direct control technique. In the proposed approach, FFAAN estimates the optimum value of the PV output voltage V_MPP, while the direct control technique achieves an optimal adjustment of the duty cycle making the operating point at MPP. To evaluate the performance of the proposed technique, the accurate electrical model of the system parts was built and simulated in MATLAB/Simulink environment. The simulation results are collected under rapidly changing climatic conditions. Simulation results show that the proposed MPPT technique achieves higher performance in terms of tracking efficiency and convergence speed compared to both the IC-based MPPT and FL-based MPPT systems. The results show that the proposed technique accurately estimates V_MPP, achieving a tracking efficiency of 99.9%, while the tracking efficiency is 94% when using FL-based MPPT and 91.5% when using IC-based MPPT. This demonstrates that the proposed technique exhibits superior performance under rapidly changing climatic conditions and increases energy production efficiency compared to classical techniques.

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“…In order to increase the efficiency of PV systems, many MPPT methods have been presented in the literature. Apart from traditional methods such as perturbation and observation (P&O), incremental conductance (IC) (Putri et al,2015), there are also new intelligent MPPT methods such as optimum gradient control (Gui et al, 2012), fuzzy logic controller (Prasad et al,2017;Algarin et al, 2017), type-2 fuzzy logic controller (Kececioglu et al, 2020), neural networks (Messalti et al, 2017). (Cetin et al, 2018) presents a different perspective with this study, by controlling the inverter instead of the converter, unlike other methods.…”

Section: Introductionmentioning

confidence: 99%

Two-Stage Three-Phase Grid-Tied Photovoltaic System with MPPT Method

Dayioğlu

Oğuz

Yönetken

2021

Afyon Kocatepe Üniversitesi Uluslararası Mühendislik Teknolojileri Ve Uygulamalı Bilimler Dergisi

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Bu çalışma, fotovoltaik (FV) sistem tarafından üretilen gücün, üç fazlı alternatif akım (AA) güç şebekesine maksimum verimle iki aşamada kontrol edilerek aktarılmasını incelemektedir. Tasarlanan FV sistemi ile güç kararlılığını sağlamak için kaynaktan yüksek verimle alınan enerjinin maksimum güç noktası izleme (MGNT) yöntemi kullanılarak ağa aktarılması amaçlanmaktadır. Ayrıca ikinci bir kontrol mekanizması ile evirici çıkışındaki akım anlık olarak kontrol edilmekte ve üretilen gücün gerilim değeri sabit tutulmaktadır. Bu kontrol sistemi sayesinde güneş enerjisi, elektrik enerjisi üretiminden elektrik şebekesine aktarılmasına kadar kontrol altında tutulmuştur. Üretilen gücün kalitesinin tahmin edilebilmesi için bilgisayar ortamında yapılan simülasyonlar sonucunda FV sistem çıkışındaki akımın toplam harmonik bozulma (THB) oranı belirlenmiştir. Simüle edilen FV sisteminin, farklı güneş ışınım seviyeleri değerlerine göre, şebekeye aktarılacak gücün voltaj değerini istenilen seviyede sabit tutma eğiliminde olduğu ve maksimum güç üretimi sırasında THB değerinin yüzde üçün altına düşürüldüğü görülmektedir.

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A fuzzy logic based MPPT method for solar power generation

Cited by 13 publications

References 10 publications

Applying a Sliding Mode Controller to Maximum Power Point Tracking in a Quasi Z-Source Inverter Based on the Power Curve of a Photovoltaic Cell

Applying a Sliding Mode Controller to Maximum Power Point Tracking in a Quasi Z-Source Inverter Based on the Power Curve of a Photovoltaic Cell

Comparative Performance Analysis of a Feed-Forward Neural Network-Based MPPT for Rapidly Changing Climatic Conditions

Two-Stage Three-Phase Grid-Tied Photovoltaic System with MPPT Method

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