Comparative Study Between the Different MPPT Techniques

Mokhlis, Mohcine; Ferfra, M.; Hemeyine, Ahmed Vall; idrissi, Rafika El; Ahmed, Cheikhne Cheikh; Taouni, Abderrahim

doi:10.1109/redec49234.2020.9163591

Cited by 11 publications

(3 citation statements)

References 13 publications

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“…In the past studies of the most recent tracking algorithms, it has been well known that the P&O is easier to implement when compared to an INC method. However, it degrades from its lower accuracy results when tracking the MPP, regardless of the testing environmental conditions whether being constant or non-constant [21], [22]. On the other hand, the INC method can provide better accuracy as compared to the P&O algorithm however for the price of being more complex mechanism and slower convergence time.…”

Section: Introductionmentioning

confidence: 99%

Optimizing The Maximum Power of Photovoltaic System Using Modified Incremental Conductance Algorithm Operating Under Varying Dynamic Climatic Conditions

M. Elzein,

Kurdi,

Harrye

2024

IJCDS

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In a photovoltaic system the challenge is to contentiously searching for the maximum power point to generate the maximum power (Pmax) within the system. In this study a hybrid maximum power point tracking module (MPPT) consisting of a well-known incremental conductance algorithm (INC) is being adapted to operate along with fuzzy logic controller (FLC). The new design focused on applying variable voltage step size estimations based on analyzing the degree of incremental and decremental of power to voltage relation. To achieve this, five effective regions were introduced around the maximum PV power point and FLC controlled the tunning and accurate adjustments of the duty ratio cycle step size by relying on the inputs of fuzzy logic controller to reach a zero oscillation around the MPP point. To adjust the duty cycle step size, fuzzy logic is established based on the position of the fuzzy input points which are derived from the current and voltage proportions and their derivatives, whereas the membership functions and rules are shaped. Matlab simulations were used under different irradiance levels to test the efficiency of tracking the maximum power. Based on the simulated results, the integration of fuzzy logic controller with incremental conductance algorithm provided enhanced performance in tracking the Pmax, and notable fast convergence time and provided the least oscillation around the maximum power point and thus maintained the overall tracking accuracy, and applying the proper step size to drive the operating point at the P-V curve in reaching Pmax under the effects of various environmental dynamic changes in temperature and irradiance.

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Section: Introductionmentioning

confidence: 99%

Optimizing The Maximum Power of Photovoltaic System Using Modified Incremental Conductance Algorithm Operating Under Varying Dynamic Climatic Conditions

M. Elzein,

Kurdi,

Harrye

2024

IJCDS

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“…However, their efficiency and convergence speed are low, and they suffer from oscillation around the MPP. 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].…”

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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“…The MPPT technique based on the P&O-Backstepping command strategy is designed in [6] in order to improve the tracking performances of the classical algorithms P&O [7]- [8]- [9] and InC [10]- [11]). The P&O-Backstepping command strategy includes two controllers, the P&O algorithm and a nonlinear command based on the Backstepping controller.…”

Section: Introductionmentioning

confidence: 99%

Experimental Test Bench of Photovoltaic Panel Under Partial Shading Effect Using the SLG-Backstepping technique

Mokhlis

Ferfra

Chennoufi

2021

IJRER

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Under the partial shading effect, the Power-Voltage curve of a photovoltaic panel includes several maximum power points divided between the local maximums and a global maximum. The most known Maximum Power Point Tracking techniques are unable to distinguish the global maximum power point. Thus, they result in a considerable drop in power. In fact, the Global Maximum Power Point Tracking technique based on the SLG-Backstepping command strategy is able to distinguish and track the global maximum power point. In the previous works, this command strategy has proven its tracking performances (accuracy and rapidity) when it is tested under Matlab/Simulink environment. In this work, this paper focuses on the real-time experimental assessment of the newest SLG-Backstepping command strategy, these tests are carried out in order to prove the ability of this command strategy to provide the desired performances, to detect any change of meteorological conditions and to track the global maximum in the real time. This strategy command is compared to the Maximum Power Point Tracking technique based on the P&O-Backstepping command strategy. In fact, these two controllers are implemented on the Arduino Mega 2560 board. Effectively, according to the experimental results, the SLG-Backstepping command strategy is able to detect the presence of partial shading and to track the global maximum under the partial shading effect. In addition, this strategy command shows tracking performances better than the P&O-Backstepping controller when they are compared under uniform meteorological conditions. In fact, as affirm results, the proposed command strategy tracks the maximum power point in approximately 0.7s, while the MPPT technique based on the P&O-Backstepping make a delay of 1.5s, also, also, under the partial shading effect, a considerable loss of power is noticed when using the MPPT technique.

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Comparative Study Between the Different MPPT Techniques

Cited by 11 publications

References 13 publications

Optimizing The Maximum Power of Photovoltaic System Using Modified Incremental Conductance Algorithm Operating Under Varying Dynamic Climatic Conditions

Optimizing The Maximum Power of Photovoltaic System Using Modified Incremental Conductance Algorithm Operating Under Varying Dynamic Climatic Conditions

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

Experimental Test Bench of Photovoltaic Panel Under Partial Shading Effect Using the SLG-Backstepping technique

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