MPPT and Output Voltage Regulation of a Photovoltaic System Based on Dual-stage Conversion and Nonlinear PI Control

The performance of solar photovoltaic systems is heavily dependent on environmental factors such as solar irradiance, ambient temperature, and partial shading. To maximize energy extraction under these variable conditions, maximum power point tracking (MPPT) algorithms are typically integrated with a boost converter; however, while MPPT ensures operation at the maximum power point, the resulting output voltage still fluctuates due to environmental and load variations. This study proposes a dual-stage conversion approach that simultaneously implements MPPT control and voltage regulation: the first stage employs a boost converter governed by the incremental conductance algorithm for maximizing power output, and the second uses a buck converter controlled by a nonlinear proportional-integral (NPI) controller to maintain a stable, desired output voltage. By integrating experimental data with a hybrid genetic algorithm, the photovoltaic cell parameters are identified and then applied to construct a detailed SIMULINK model for optimizing NPI controller gains. Finally, simulations are conducted to demonstrate the effectiveness of the proposed method, particularly under partial shading conditions.

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Publication Details

Journal
Journal of Institute of Control Robotics and Systems
Published
2026-03-12
DOI
https://doi.org/10.5302/j.icros.2026.25.0329
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
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article

MPPT and Output Voltage Regulation of a Photovoltaic System Based on Dual-stage Conversion and Nonlinear PI Control

Adnan Kedir Jarso, Gang-Gyoo Jin, Jongkap Ahn, Ashebir Berhanu Beyesa
Journal of Institute of Control Robotics and Systems
Photovoltaic System Optimization Techniques
article

MPPT and Output Voltage Regulation of a Photovoltaic System Based on Dual-stage Conversion and Nonlinear PI Control

Adnan Kedir Jarso, Gang-Gyoo Jin, Jongkap Ahn, Ashebir Berhanu Beyesa
article en

Abstract

The performance of solar photovoltaic systems is heavily dependent on environmental factors such as solar irradiance, ambient temperature, and partial shading. To maximize energy extraction under these variable conditions, maximum power point tracking (MPPT) algorithms are typically integrated with a boost converter; however, while MPPT ensures operation at the maximum power point, the resulting output voltage still fluctuates due to environmental and load variations. This study proposes a dual-stage conversion approach that simultaneously implements MPPT control and voltage regulation: the first stage employs a boost converter governed by the incremental conductance algorithm for maximizing power output, and the second uses a buck converter controlled by a nonlinear proportional-integral (NPI) controller to maintain a stable, desired output voltage. By integrating experimental data with a hybrid genetic algorithm, the photovoltaic cell parameters are identified and then applied to construct a detailed SIMULINK model for optimizing NPI controller gains. Finally, simulations are conducted to demonstrate the effectiveness of the proposed method, particularly under partial shading conditions.

Journal of Institute of Control Robotics and SystemsVol. 32(3)
Affordable and clean energy
Openalex Percentile: Top 29%
Photovoltaic System Optimization Techniques
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