A Review on Non-isolated Inductor Coupled DC-DC Converter for Photovoltaic Grid-Connected Applications

doi:10.20508/ijrer.v7i4.6158.g7197

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…From equation (23), the parameters c i , d i , and k i are subsequent constants, and there are fve layers in the ANFIS controller which are shown in Figure 6. Here, each layer node number is represented based on its related membership function, and the outputs of the 1-layer nodes are determined by using equations ( 25) and (26). From equation ( 25), the variables §; and n 1,i are the utilized membership values for the corresponding supply variables u and v. Similarly, the parameters g and h are represented as membership values.…”

Section: Proposed Adaptive Genetic Algorithm-based Anfis Mppt Controllermentioning

confidence: 99%

“…Here, the functioning point of the PEMFS is at the right side of the V-I curve, and then, the equivalent conductance value is increased. Otherwise, the conductance of the system is reduced for optimizing the oscillations across MPP [25][26][27][28]. All the renewable energy-fed power electronics circuits generate ripples which are supplied to the ripple correlation block to generate the suitable duty signal to the DC-DC converter [29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Design and Analysis Adaptive Hybrid ANFIS MPPT Controller for PEMFC-Fed EV Systems

Touti,

Aoudia,

Hussaian Basha

et al. 2024

International Transactions on Electrical Energy Systems

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Now, the present electric vehicle industry is focusing on the fuel cell technology because its features are high flexibility, continuous power supply, less atmospheric pollution, fast startup, and rapid response. However, the fuel cell gives nonlinear power versus current characteristics. Due to this nonlinear behavior, the maximum power extraction from the fuel stack is quite difficult. So, in this work, an adaptive genetic algorithm with an adaptive neuro-fuzzy inference system (ACS with ANFIS) MPPT controller is introduced for finding the MPP of the fuel stack system thereby extracting the peak power from the fuel stack. The proposed hybrid maximum power point tracking (MPPT) controller is compared with the other MPPT controllers which are enhanced incremental conductance-fuzzy logic controller (EIC with FLC), improved hill climb with fuzzy logic controller (IHC with FLC), adaptive beta with FLC, enhanced differential evolutionary with FLC (EDE with FLC), and marine predators optimization with FLC (MPO with FLC). Here, these hybrid controllers’ comprehensive investigations have been carried out in terms of tracking speed of the MPP, oscillations across the MPP, settling time of the converter voltage, maximum power extraction from the fuel stack, and working efficiency of the MPPT controller. The fuel stack generates a very low output voltage which is improved by using the boost DC-DC converter, and the overall fuel stack-fed boost converter system is designed by utilizing the MATLAB/Simulink tool. From the simulation results, the AGA with ANFIS MPPT controller gives high MPP tracking efficiency when compared to the other hybrid controller.

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Section: Proposed Adaptive Genetic Algorithm-based Anfis Mppt Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Design and Analysis Adaptive Hybrid ANFIS MPPT Controller for PEMFC-Fed EV Systems

Touti,

Aoudia,

Hussaian Basha

et al. 2024

International Transactions on Electrical Energy Systems

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“…At the same time, the MO is possess less-flammable characteristics therefore it is not fit dangerous fire risky location. And so, MO is releasing harmful gases to the atmosphere and so it has very few biodegradation properties [6].…”

Section: Introductionmentioning

confidence: 99%

An Experimental Analysis of Degradation of Cellulosic Insulating Material Immersed in Natural Ester Oil for Transformer

Basha¹,

Mariprasath²,

Kiran³

et al. 2022

ECS Trans.

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The physical, chemical and electrical prosperities of MO is matched as an insulating material for transformer. Therefore, it can be used in transformers. Whereas, the MO is extracted from the fossil fuels. Due to vast consumption of fossil fuels, the accessibility of vestige fuel is going to run out near future. In addition, the MO (MO) is doesn’t meet the new environmental regulation due to it has less biodegradable. Therefore, this research proposed a new ecological friendly insulating oil for transformer which is renewable that of petroleum based insulating oil such as MO. Initially, a critical review has been made on recent development on alternate liquid dielectrics for transformer. Subsequently, critical characteristics of insulating oil have been measured according to the standard. Added to that, the critical characteristics of Natural Ester Oil (NEO) are estimated at diverse temperatures from 50°C, 70°C, 90°C, 110°C, 130°C, and 150°C respectively.

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Multi-port Converter for Medium and High Voltage Applications

Alsokhiry

Al‐Turki

Abdelsalam

et al. 2018

2018 7th International Conference on Renewable Energy Research and Applications (ICRERA)

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A Review on Non-isolated Inductor Coupled DC-DC Converter for Photovoltaic Grid-Connected Applications

Cited by 5 publications

References 30 publications

A Novel Design and Analysis Adaptive Hybrid ANFIS MPPT Controller for PEMFC-Fed EV Systems

A Novel Design and Analysis Adaptive Hybrid ANFIS MPPT Controller for PEMFC-Fed EV Systems

An Experimental Analysis of Degradation of Cellulosic Insulating Material Immersed in Natural Ester Oil for Transformer

Multi-port Converter for Medium and High Voltage Applications

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