Design and experimental implementation of single phase power factor correction converter based on fuzzy logic controls techniques

Benyamina, Abderrahmen; Moulahoum, Samir; Çolak, İlhami; Kabache, Nadir; Houassine, Hamza

doi:10.1109/icrera.2015.7418529

Cited by 8 publications

(2 citation statements)

References 13 publications

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“…Artificial intelligent techniques such fuzzy logic, artificial neural network and generic algorithms are used widely in reactive power control and power factor correction for different application such as single phase power factor correction and converters power factor [11][12][13][14] In case the power factor that is needed to be corrected varies with loading, PFC capacitor bank needs to be switched between its different stages to achieve the correct amount of positive reactive power from the capacitor that compensates the negative reactive power consumed by the load. A special control is required always when design such switching system for capacitor to consider the overvoltage transient and to limit the inrush current [15,16].…”

Section: Introductionmentioning

confidence: 99%

Novel Design to Tune SVC for Power Factor Correction and Reactive Power Control Using Cascaded ANN Approach (CANNA

Mahmoud¹

2022

Preprint

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This article introduces new method using ANN to control SVC in order to correct the source power factor of low voltage network. Two ANN approaches are investigated to design accurate and fast power factor correction (PFC) controller. First approach uses simple ANN (SANNA). Second approach uses cascaded ANN (CANNA). ANN regression, performance and the calculated error for both approaches are investigated to select between the two approaches. CANNA is selected as a better solution and it used to build the ANN PFFC controller using database, generated by MATLAB-Simulink, for standard three low voltage levels (240V, 220V and 110V). Nine test cases are carried out to validate the performance of proposed ANN PFC controller with a network has variable loads and low power factor (0.6 approximately). In order to extend the use of the controller to other voltage levels not included in the training process of the cascaded ANN, only the SVC is resized. Another nine cases are carried out with the same loads using the same ANN controller, as it is, to test its performance with the extended voltage level range (415V, 230V and 120V). The results show accurate and fast response in all test cases.

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Section: Introductionmentioning

confidence: 99%

Novel Design to Tune SVC for Power Factor Correction and Reactive Power Control Using Cascaded ANN Approach (CANNA

Mahmoud¹

2022

Preprint

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“…These methods must has a full acknowledge of system parameters, but due to the system's non-linearity and variation, the relevant calculations are often complex. Compared to those techniques, the utilization of fuzzy logic controllers (FLCs) has been proposed as a way to deal with the non-linearity of the system, and at the same time, to absorb the fluctuations within the microgrid [12][13][14][15][16][17][18]. FLCs can efficiently handle non-linear systems, without the knowledge of the system parameters.…”

Section: Introductionmentioning

confidence: 99%

A Constant Grid Interface Current Controller for DC Microgrid

Alshareef

Lin

2018

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

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With the increased percentage of distributed renewable energy sources (RES) connected to the power network, it is challenging to maintain the balance between the power generation and consumptions against the unpredictable renewable energy generation and load variations. Considering this, this study proposed a new DC microgrid control strategy to reduce the disturbance to the main power grid from the distributed generation and load variations within the DC microgrid. The DC microgrid model used in this study includes an energy storage unit (battery), a distributed generation unit (PV) and loads. A fuzzy logic controller (FLC) is used to actively regulate the battery charging/discharging current to absorb the power variation caused by PV generation and load changes. The proposed control strategy is validated by simulation in MATLAB/Simulink.

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Design and real time implementation of adaptive neural-fuzzy inference system controller based unity single phase power factor converter

Benyamina

Moulahoum

Çolak

et al. 2017

Electric Power Systems Research

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Design and experimental implementation of single phase power factor correction converter based on fuzzy logic controls techniques

Cited by 8 publications

References 13 publications

Novel Design to Tune SVC for Power Factor Correction and Reactive Power Control Using Cascaded ANN Approach (CANNA

Novel Design to Tune SVC for Power Factor Correction and Reactive Power Control Using Cascaded ANN Approach (CANNA

A Constant Grid Interface Current Controller for DC Microgrid

Design and real time implementation of adaptive neural-fuzzy inference system controller based unity single phase power factor converter

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