Implementing GA-ANFIS for Maximum Power Point Tracking in PV System

Rezvani, Alireza; Izadbakhsh, Maziar; Gandomkar, Majid; Vafaei, Saeed

doi:10.17485/ijst/2015/v8i10/51832

Cited by 20 publications

(8 citation statements)

References 19 publications

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“…One another algorithm [24] represents maximization of power efficiency of photovoltaic systems exposed to different climate circumstances using also GA optimized ANFIS model. In power and energy field an ANFIS model was used to control generator terminal voltage in order to design power stabilizer system [25].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy System Based on Two-Step Cascade Genetic Optimization Strategy for Tobacco Tar Prediction

Kafadar¹,

Avdagić²,

Fazlic³

2019

IJCIS

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There are many challenges in accurately measuring cigarette tar constituents. These include the need for standardized smoke generation methods related to unstable mixtures. In this research were developed algorithms using fusion of artificial intelligence methods to predict tar concentration. Outputs of development are three fuzzy structures optimized with genetic algorithms resulting in genetic algorithm (GA)-FUZZY, GA-adaptive neuro fuzzy inference system (ANFIS), GA-GA-FUZZY algorithms. Proposed algorithms are used for the tar prediction in the cigarette production process. The results of prediction are compared with gas chromatograph (high-performance liquid chromatography (HPLC)) readings.

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Section: Introductionmentioning

confidence: 99%

Fuzzy System Based on Two-Step Cascade Genetic Optimization Strategy for Tobacco Tar Prediction

Kafadar¹,

Avdagić²,

Fazlic³

2019

IJCIS

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“…Nowadays, the intelligent controllers are getting popular for enhancing the performance of PV power system . In Duru, a closed loop current control method is proposed for MPPT in which the reference signal for controller is determined by the curve fitting between maximum power point current versus maximum power.…”

Section: Introductionmentioning

confidence: 99%

“…Nowadays, the intelligent controllers are getting popular for enhancing the performance of PV power system. [28][29][30] In Duru, 31 a closed loop current control method is proposed for MPPT in which the reference signal for controller is determined by the curve fitting between maximum power point current versus maximum power. In Karanjkar et al, 32 perturb and observation (P&O), incremental conductance (IC), fuzzy, neural network (NN), and adaptive neuro fuzzy inference system (ANFIS)-based MPPT algorithms have been implemented on synchronous buck converter.…”

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confidence: 99%

Experimental assessment of maximum power extraction from solar panel with different converter topologies

Dixit¹,

Yadav

Gupta

2018

Int Trans Electr Energ Syst

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Summary The solar power plants are playing a significant role in energy market due to its eco‐friendly nature, low operational, and maintenance cost. The efficiency of these plants depends mainly on load impedance, topology of converters, and maximum power point tracking algorithms. In this work, effect of operating point (load line selection) on the performance of maximum power point tracking for different DC‐DC converter topologies has been studied and experimentally validated. Further, the operating constraints of buck, boost, and buck‐boost modes of converter operation in terms of load impedance are presented. The performance of different maximum power point tracking algorithms under load and solar irradiance change has been investigated for all converter topologies discussed. The modified model of photovoltaic module has been presented for simulation study under different solar irradiance and load variations that can be easily implemented on Real Time Digital Simulator platform unlike conventional models.

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“…Amongst various PWM methods for a multilevel inverter, SVM is suitable due to various advantages like it directly control system, identifies the voltage and switching vectors and co-ordinates transformation. The space vector diagram for any level inverter contains six sectors [8], [9]. Each sector contains number of triangles and sub regions.…”

Section: Introductionmentioning

confidence: 99%

A Sub-Region Based Space Vector Modulation Scheme for Dual 2-Level Inverter System

Palanisamy

Velu²,

Selvakumar

et al. 2018

IJECE

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This paper deals the implementation of 3-level output voltage using dual 2-level inverter with control of sub-region based Space Vector Modulation (SR-SVM). Switching loss and voltage stress are the most important issues in multilevel inverters, for keep away from these problems dual inverter system executed. Using this proposed system, the conventional 3-level inverter voltage vectors and switching vectors can be located. In neutral point clamped multilevel inverter, it carries more load current fluctuations due to the DC link capacitors and it requires large capacitors. Based on the sub-region SVM used to control IGBT switches placed in the dual inverter system. The proposed system improves the output voltage with reduced harmonic content with improved dc voltage utilisation. The simulation and hardware results are verified using matlab/simulink and dsPIC microcontroller.

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Implementing GA-ANFIS for Maximum Power Point Tracking in PV System

Cited by 20 publications

References 19 publications

Fuzzy System Based on Two-Step Cascade Genetic Optimization Strategy for Tobacco Tar Prediction

Fuzzy System Based on Two-Step Cascade Genetic Optimization Strategy for Tobacco Tar Prediction

Experimental assessment of maximum power extraction from solar panel with different converter topologies

A Sub-Region Based Space Vector Modulation Scheme for Dual 2-Level Inverter System

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