A new design of transformerless, non‐isolated, high step‐up DC‐DC converter with hybrid fuzzy logic MPPT controller

Under Partial Shading Conditions (PSCs), the solar PV nonlinear characteristics consist of multiple Maximum Power Points (MPPs). As a result, it is very difficult to extract the peak power of the solar PV. In this article, an Improved Grey Wolf Optimization‐based Fuzzy Logic Controller (IGWO‐FLC) is...

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Published inInternational journal of circuit theory and applications Vol. 50; no. 1; pp. 272 - 297
Main Authors Basha, Chakarajamula Hussaian, Murali, Matcha
Format Journal Article
LanguageEnglish
Published Bognor Regis Wiley Subscription Services, Inc 01.01.2022
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ISSN0098-9886
1097-007X
DOI10.1002/cta.3153

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Abstract Under Partial Shading Conditions (PSCs), the solar PV nonlinear characteristics consist of multiple Maximum Power Points (MPPs). As a result, it is very difficult to extract the peak power of the solar PV. In this article, an Improved Grey Wolf Optimization‐based Fuzzy Logic Controller (IGWO‐FLC) is proposed to track the MPP of the solar PV. The advantages of the proposed hybrid soft computing Maximum Power Point Tracking (MPPT) controller are high accuracy, very less oscillations across MPP, and high tracking speed. Also, a new transformerless, high step‐up, Non‐isolated Boost Converter (NIBC) is introduced in this work to improve the voltage profile of the solar PV system at different atmospheric conditions. The introduced converter circuit makes use of the network LC3D3 to improve the voltage conversion ratio, reduced voltage stress on switches, and universal input voltage. In addition, the network LC3D3 acts as a filter to reduce the output power ripples of the converter. The steady‐state performance of the proposed converter is analyzed at Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM) of operations. The MATLAB/Simulink window is used to validate the proposed PV fed NIBC system at uniform and different PSCs of the solar PV. Also, the NIBC performance is investigated by applying an M62252P8020 type programmable DC‐source. An Improved Grey Wolf Optimization‐based Fuzzy Logic Controller (IGWO‐FLC) is used in this article to track the MPP of the solar PV. The advantages of the proposed hybrid soft computing Maximum Power Point Tracking (MPPT) controller are high accuracy, very less oscillations across MPP, and high tracking speed. Also, a new transformerless, high step‐up, Non‐isolated Boost Converter (NIBC) is proposed in this work to step‐up the PV system output voltage at different atmospheric conditions. The proposed converter circuit makes use of the network LC3D3 to improve the voltage conversion ratio, reduced voltage stress on switches, and universal input voltage.
AbstractList Under Partial Shading Conditions (PSCs), the solar PV nonlinear characteristics consist of multiple Maximum Power Points (MPPs). As a result, it is very difficult to extract the peak power of the solar PV. In this article, an Improved Grey Wolf Optimization‐based Fuzzy Logic Controller (IGWO‐FLC) is proposed to track the MPP of the solar PV. The advantages of the proposed hybrid soft computing Maximum Power Point Tracking (MPPT) controller are high accuracy, very less oscillations across MPP, and high tracking speed. Also, a new transformerless, high step‐up, Non‐isolated Boost Converter (NIBC) is introduced in this work to improve the voltage profile of the solar PV system at different atmospheric conditions. The introduced converter circuit makes use of the network LC 3 D 3 to improve the voltage conversion ratio, reduced voltage stress on switches, and universal input voltage. In addition, the network LC 3 D 3 acts as a filter to reduce the output power ripples of the converter. The steady‐state performance of the proposed converter is analyzed at Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM) of operations. The MATLAB/Simulink window is used to validate the proposed PV fed NIBC system at uniform and different PSCs of the solar PV. Also, the NIBC performance is investigated by applying an M62252P8020 type programmable DC‐source.
Under Partial Shading Conditions (PSCs), the solar PV nonlinear characteristics consist of multiple Maximum Power Points (MPPs). As a result, it is very difficult to extract the peak power of the solar PV. In this article, an Improved Grey Wolf Optimization‐based Fuzzy Logic Controller (IGWO‐FLC) is proposed to track the MPP of the solar PV. The advantages of the proposed hybrid soft computing Maximum Power Point Tracking (MPPT) controller are high accuracy, very less oscillations across MPP, and high tracking speed. Also, a new transformerless, high step‐up, Non‐isolated Boost Converter (NIBC) is introduced in this work to improve the voltage profile of the solar PV system at different atmospheric conditions. The introduced converter circuit makes use of the network LC3D3 to improve the voltage conversion ratio, reduced voltage stress on switches, and universal input voltage. In addition, the network LC3D3 acts as a filter to reduce the output power ripples of the converter. The steady‐state performance of the proposed converter is analyzed at Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM) of operations. The MATLAB/Simulink window is used to validate the proposed PV fed NIBC system at uniform and different PSCs of the solar PV. Also, the NIBC performance is investigated by applying an M62252P8020 type programmable DC‐source. An Improved Grey Wolf Optimization‐based Fuzzy Logic Controller (IGWO‐FLC) is used in this article to track the MPP of the solar PV. The advantages of the proposed hybrid soft computing Maximum Power Point Tracking (MPPT) controller are high accuracy, very less oscillations across MPP, and high tracking speed. Also, a new transformerless, high step‐up, Non‐isolated Boost Converter (NIBC) is proposed in this work to step‐up the PV system output voltage at different atmospheric conditions. The proposed converter circuit makes use of the network LC3D3 to improve the voltage conversion ratio, reduced voltage stress on switches, and universal input voltage.
Under Partial Shading Conditions (PSCs), the solar PV nonlinear characteristics consist of multiple Maximum Power Points (MPPs). As a result, it is very difficult to extract the peak power of the solar PV. In this article, an Improved Grey Wolf Optimization‐based Fuzzy Logic Controller (IGWO‐FLC) is proposed to track the MPP of the solar PV. The advantages of the proposed hybrid soft computing Maximum Power Point Tracking (MPPT) controller are high accuracy, very less oscillations across MPP, and high tracking speed. Also, a new transformerless, high step‐up, Non‐isolated Boost Converter (NIBC) is introduced in this work to improve the voltage profile of the solar PV system at different atmospheric conditions. The introduced converter circuit makes use of the network LC3D3 to improve the voltage conversion ratio, reduced voltage stress on switches, and universal input voltage. In addition, the network LC3D3 acts as a filter to reduce the output power ripples of the converter. The steady‐state performance of the proposed converter is analyzed at Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM) of operations. The MATLAB/Simulink window is used to validate the proposed PV fed NIBC system at uniform and different PSCs of the solar PV. Also, the NIBC performance is investigated by applying an M62252P8020 type programmable DC‐source.
Author Murali, Matcha
Basha, Chakarajamula Hussaian
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Snippet Under Partial Shading Conditions (PSCs), the solar PV nonlinear characteristics consist of multiple Maximum Power Points (MPPs). As a result, it is very...
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SubjectTerms boost converter
Circuits
Controllers
Conversion ratio
Converters
duty cycle
Electric potential
Fuzzy control
Fuzzy logic
GWO
high MPP tracking speed
high step‐up
Maximum power tracking
Optimization
Soft computing
Switches
Tracking control
transformerless
universal input voltage
Voltage
Title A new design of transformerless, non‐isolated, high step‐up DC‐DC converter with hybrid fuzzy logic MPPT controller
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fcta.3153
https://www.proquest.com/docview/2618155452
Volume 50
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