Performance Analysis of Soft Computing ANN Based MPPT Technique for Solar PV Generator

Chahar, Sunita; Yadav, Dinesh Kumar

doi:10.1109/aic55036.2022.9848876

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…We have now completed our examination of the meaning of GSA and can move on to its operation. As we have seen, the force between particles in a normal GSA is determined by gravitational attraction, so we know there must be force involved (32).…”

Section: Gravitational Search Algorithm (Gsa) Based Mpptmentioning

confidence: 98%

“…Existing review literature compares various MPPT algorithms; however, they can sometimes be difficult to understand [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. There are several parameters and approaches-based methods discussed in the literature, i.e., voltage-and current-based MPPT approaches [21], perturb and observation (P&O) methods [22,23], incremental conductance (INC) methods [24][25][26], temperature and irradiance-based method [27], intelligence techniques base MPPT method [28,29], fuzzy logic control methods [30,31], artificial neural network base method [32][33][34], optimization techniques base method, etc. [35][36][37].…”

Section: Figure 2 P-v and I-v Characteristics Of Pvmentioning

confidence: 99%

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Comprehensive Review of Conventional and Emerging Maximum Power Point Tracking Algorithms for Uniformly and Partially Shaded Solar Photovoltaic Systems

et al. 2023

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The authors would like to thank "Universidad Panamericana" for their support through the project "Estudio de topologías de convertidores de cd-cd" grand number: UP-CI-2022-GDL-06-ING."ABSTRACT Renewable energy utilization is the only suitable solution to diminish the increasing level of greenhouse gas emissions, fuel costs, and energy crisis in the next generation. Out of many renewable sources, solar energy sources that are clean, green, and emission-free have gained wide utilization despite their intermittency nature. Several solar photovoltaic (PV) panels are connected in series-parallel to achieve the energy demand. In such a system, it is possible that each panel operates differently due to uneven temperature and irradiation that results in uniform and partial shading conditions. Thus, a unique and efficient mechanism is required to extract maximum power from uniformly and partially shaded PV systems. Numerous maximum power point tracking (MPPT) methods have been developed to increase the efficiency and lifetime of photovoltaic systems. This study provides a unique, in-depth, and organized review of MPPT methods under four categories: classical, intelligent, optimization, and hybrid techniques. All possible selection benchmarks are considered to do a comprehensive review, which is not deliberated in the existing review literature. Based on the selection benchmarks, the advantages and disadvantages of each MPPT technique under different categories are summarized in tabulated form. To address the research gaps for further investigation in this field, a concise discussion is included at the end. This review article may find an accessible reference for engineers to understand the most useful MPPT method and to undertake extensive research in PV systems.

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Section: Gravitational Search Algorithm (Gsa) Based Mpptmentioning

confidence: 98%

Section: Figure 2 P-v and I-v Characteristics Of Pvmentioning

confidence: 99%

Comprehensive Review of Conventional and Emerging Maximum Power Point Tracking Algorithms for Uniformly and Partially Shaded Solar Photovoltaic Systems

et al. 2023

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“…In [52][53][54], fuzzy logic controllers were utilized for MPPT and they showed better tracking efficiency as compared to conventional techniques. Artificial neural networks were used for MPPT in Refs [55][56][57] and their performance was satisfactory.…”

Section: Maximum Power Point Trackingmentioning

confidence: 99%

The role of computational intelligence techniques in the advancements of solar photovoltaic systems for sustainable development: a review

Moyo

Dewa

2022

Ren. Ener. & Sust. Dev.

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The use of computational intelligence (CI) in solar photovoltaic (SPV) systems has been on the rise due to the increasing computational power, advancements in power electronics and the availability of data generation tools. CI techniques play an important role in modelling, sizing, forecasting, optimizing, analysing and predicting the performance and control of SPV systems. Thus, CI techniques have become an essential technology as the energy sector seeks to meet the rapidly increasing demand for clean, cheap, and reliable energy. In this context, this review paper aims to investigate the role of CI techniques in the advancements of SPV systems. The study includes the involvement of CI techniques for parameter identification of solar cells, PV system sizing, maximum power point tracking (MPPT), forecasting, fault detection and diagnosis, inverter control and solar tracking of SPV systems. A performance comparison between CI techniques and conventional methods is also carried out toprove the importance of CI in SPV systems. The findings confirmed the superiority of CI techniques over conventional methods for every application studied and it can be concluded that the continuous improvements and involvement of these techniques can revolutionize the SPV industry and significantly increase the adoption of solar energy.

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Adaptive Based Affine Combination of FXECAP-FXECLMS Control for Solar PV-ES Standalone System

Singh

Narayanan

Singh

et al. 2023

2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)

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Performance Analysis of Soft Computing ANN Based MPPT Technique for Solar PV Generator

Cited by 6 publications

References 16 publications

Comprehensive Review of Conventional and Emerging Maximum Power Point Tracking Algorithms for Uniformly and Partially Shaded Solar Photovoltaic Systems

Comprehensive Review of Conventional and Emerging Maximum Power Point Tracking Algorithms for Uniformly and Partially Shaded Solar Photovoltaic Systems

The role of computational intelligence techniques in the advancements of solar photovoltaic systems for sustainable development: a review

Adaptive Based Affine Combination of FXECAP-FXECLMS Control for Solar PV-ES Standalone System

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