Adaptive neuro-fuzzy inference system based maximum power point tracking for stand-alone photovoltaic system

Amara, Karima; Malek, A.; Bakir, Toufik; Fekik, Arezki; Azar, Ahmad Taher; Mellouli, Khaled; Bourennane, El-Bay; Hocine, D.

doi:10.1504/ijmic.2019.107480

Cited by 26 publications

(7 citation statements)

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“…It is highly suited for regulating systems with built-in uncertainties and nonlinearity since this combination of ANN and fuzzy logic creates a robust and flexible control system that can handle complicated and interrelated data. The ANFIS controller effectively captures the system's dynamic character, enabling accurate and effective decision-making depending on the inputs 47 . Utilizing the benefits of both ANN and FLC, the ANFIS approach emerges as a comprehensive and sophisticated solution, improving performance and flexibility for a variety of real-world applications.…”

Section: Working Principle Of Anfismentioning

confidence: 99%

Maximizing solar power generation through conventional and digital MPPT techniques: a comparative analysis

Sarang,

Raza,

Panhwar

et al. 2024

Sci Rep

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A substantial level of significance has been placed on renewable energy systems, especially photovoltaic (PV) systems, given the urgent global apprehensions regarding climate change and the need to cut carbon emissions. One of the main concerns in the field of PV is the ability to track power effectively over a range of factors. In the context of solar power extraction, this research paper performs a thorough comparative examination of ten controllers, including both conventional maximum power point tracking (MPPT) controllers and artificial intelligence (AI) controllers. Various factors, such as voltage, current, power, weather dependence, cost, complexity, response time, periodic tuning, stability, partial shading, and accuracy, are all intended to be evaluated by the study. It is aimed to provide insight into how well each controller performs in various circumstances by carefully examining these broad parameters. The main goal is to identify and recommend the best controller based on their performance. It is notified that, conventional techniques like INC, P&O, INC-PSO, P&O-PSO, achieved accuracies of 94.3, 97.6, 98.4, 99.6 respectively while AI based techniques Fuzzy-PSO, ANN, ANFIS, ANN-PSO, PSO, and FLC achieved accuracies of 98.6, 98, 98.6, 98.8, 98.2, 98 respectively. The results of this study add significantly to our knowledge of the applicability and effectiveness of both AI and traditional MPPT controllers, which will help the solar industry make well-informed choices when implementing solar energy systems.

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Section: Working Principle Of Anfismentioning

confidence: 99%

Maximizing solar power generation through conventional and digital MPPT techniques: a comparative analysis

Sarang,

Raza,

Panhwar

et al. 2024

Sci Rep

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“…The study conducted a comparative analysis of two techniques proposed by [41,42], with respect to the technique investigated in this work. The comparison criteria included P mpp (watts), current (A), V mpp (volts), time response (seconds), and the larger oscillations.…”

Section: Comparative Studymentioning

confidence: 99%

Enhancing Photovoltaic Efficiency with the Optimized Steepest Gradient Method and Serial Multi-Cellular Converters

et al. 2023

Self Cite

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Many methods have been developed to aid in achieving the maximum power point (MPP) generated by PV fields in order to improve photovoltaic (PV) production. The optimized steepest gradient technique (OSGM), which is used to extract the maximum power produced by a PV field coupled to a multicell series converter, is one such promising methodology. The OSGM uses the power function’s first and second derivatives to find the optimal voltage (Vpv) and converge to the voltage (Vref) that secures the MPP. The mathematical model was developed in Matlab/Simulink, and the MPPT algorithm’s performance was evaluated in terms of reaction time, oscillations, overshoots, and stability. The OSGM has a faster response time, fewer oscillations around the MPP, and minimal energy loss. Furthermore, the numerical calculation of the gradient and Hessian of the power function enables accurate modeling, improving the system’s precision. These findings imply that the OSGM strategy may be a more efficient way of obtaining MPP for PV fields. Future research can look into the suitability of this method for different types of PV systems, as well as ways to improve the algorithm’s performance for specific applications.

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“…Note: V 1 (100), V 2 (110), V 3 (010), V 4 (011), V 5 (001), V 6 (101) Ajel et al, 2021;Al-Qassar et al, 2021a,b;Bansal et al, 2021;Azar et al, ,b,c,d,e,f,g,h,i,j, 2020aNajm et al, 2022Najm et al, , 2021aNajm et al, ,b 2020Elkholy et al, 2020a,b;Mohamed et al, 2020;Ibrahim et al, 2020;Sayed et al, 2023Sayed et al, , 2020Samanta et al, 2018 ;Mukherjee et al, 2014;Fekik et al, 2022Fekik et al, . 2021aFekik et al, ,b,c, 2020aFekik et al, , 2019Fekik et al, , 2018aDaraz et al, 2022Daraz et al, , 2021Pilla et al, 2021aPilla et al, ,b, 2020Pilla et al, , 2019Abdul-Adheem et al, 2022Liu et al, 2020;Bouchemha et al, 2021;Gorripotu et al, 2021Gorripotu et al, , 2019Drhorhi et al, 2021 ;Kumar et al, 2018Kumar et al, , 2021Acharyulu et al, 2021;Hamiche et al, 2021;Mittal et al, 2021;Pham et al, 2021Pham et al, , 2018Pham et al, , 2017aSambas et al, 2021a,b;Khan et al, 2020a,b;Khennaoui et al, 2020a,b;Kammogne et al, 2020;Alain et al, 2020…”

Section: Proposed Controllermentioning

confidence: 99%

A Design and Implementation of a New Control Based on Petri Nets for Three Phase PWM-Rectifier

Fekik

Hamida

Kais

et al. 2023

International Journal of Service Science, Management, Engineering, and Technology

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This article introduces a novel and effective diagram based on direct instantaneous power control (DPC) of a PWM-controlled rectifier connected to the grid without a switching table. An optimum control vector of the PWM rectifier's input voltage, which depends on the switching states determined by a Petri nets controller, is adopted. This approach limits the instantaneous detection errors of reactive and active powers, maintains the DC bus voltage at a reference level, and ensures current close to a sinusoidal wave, guaranteeing operation at a unit power factor. The instantaneous tracking errors of active and reactive powers and the angular position of the voltage are used as input variables for the proposed controller, which then selects the best control vector for the converter based on the transition of a Petri net. The significant advantages of DPC based on Petri nets compared to traditional switching tables are that hysteresis comparators are not required, and the classical regulation of active and reactive powers is achieved in all sectors. Simulation and testing findings demonstrated excellent performance, supporting the viability of the suggested control approach using Petri nets.

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Adaptive neuro-fuzzy inference system based maximum power point tracking for stand-alone photovoltaic system

Cited by 26 publications

References 0 publications

Maximizing solar power generation through conventional and digital MPPT techniques: a comparative analysis

Maximizing solar power generation through conventional and digital MPPT techniques: a comparative analysis

Enhancing Photovoltaic Efficiency with the Optimized Steepest Gradient Method and Serial Multi-Cellular Converters

A Design and Implementation of a New Control Based on Petri Nets for Three Phase PWM-Rectifier

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