Maximum Power Point Tracker for Photovoltaic Module Arrays with Automatic Step Size Adjustment

P-V characteristic curve, dynamic response, steady-state performanceIn this paper, we propose an improved incremental conductance (IINC) method with automatic step size adjustment for maximum power point tracking (MPPT) in photovoltaic module arrays (PVMAs).The proposed method achieves MPPT by utilizing simple voltage and current sensors to feedback the output voltage and current of the PVMAs.Owing to changes in solar irradiance and temperature, the maximum power output of the PVMA varies.When the traditional incremental conductance (INC) is used for MPPT, if the tracking step size is very small and fixed, it results in excessively long tracking times.Conversely, if a large and fixed tracking step size is used, the tracking speed may increase; however, this can lead to unstable operation near the maximum power point (MPP), causing large oscillations around the point.As a result, the overall output power of the PVMA is reduced.To address this issue, we propose in this paper an IINC, aimed at enhancing the output power of the PVMA.First, the initial voltage for MPPT was set to 0.8 times the MPP voltage V mp of the PVMA under standard test conditions.At the same time, the tracking step size was automatically adjusted on the basis of the slope of the power-voltage (P-V) characteristic curve of the PVMA.Finally, experimental tests were conducted under various solar irradiance conditions using both the conventional INC and IINC for the MPPT of the PVMA.The results demonstrate that the proposed IINC offers superior dynamic response and steady-state performance compared with the traditional INC.

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Publication Details

Journal
Sensors and Materials
Published
2026-05-22
DOI
https://doi.org/10.18494/sam5840
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Maximum Power Point Tracker for Photovoltaic Module Arrays with Automatic Step Size Adjustment

Kuei‐Hsiang Chao, Kuan-Ting Lee, Cheng-Ze Li
Sensors and Materials
Photovoltaic System Optimization Techniques
article

Maximum Power Point Tracker for Photovoltaic Module Arrays with Automatic Step Size Adjustment

Kuei‐Hsiang Chao, Kuan-Ting Lee, Cheng-Ze Li
article en

Abstract

P-V characteristic curve, dynamic response, steady-state performanceIn this paper, we propose an improved incremental conductance (IINC) method with automatic step size adjustment for maximum power point tracking (MPPT) in photovoltaic module arrays (PVMAs).The proposed method achieves MPPT by utilizing simple voltage and current sensors to feedback the output voltage and current of the PVMAs.Owing to changes in solar irradiance and temperature, the maximum power output of the PVMA varies.When the traditional incremental conductance (INC) is used for MPPT, if the tracking step size is very small and fixed, it results in excessively long tracking times.Conversely, if a large and fixed tracking step size is used, the tracking speed may increase; however, this can lead to unstable operation near the maximum power point (MPP), causing large oscillations around the point.As a result, the overall output power of the PVMA is reduced.To address this issue, we propose in this paper an IINC, aimed at enhancing the output power of the PVMA.First, the initial voltage for MPPT was set to 0.8 times the MPP voltage V mp of the PVMA under standard test conditions.At the same time, the tracking step size was automatically adjusted on the basis of the slope of the power-voltage (P-V) characteristic curve of the PVMA.Finally, experimental tests were conducted under various solar irradiance conditions using both the conventional INC and IINC for the MPPT of the PVMA.The results demonstrate that the proposed IINC offers superior dynamic response and steady-state performance compared with the traditional INC.

Sensors and MaterialsVol. 38(5)
National Chin-Yi University of Technology (TW)
National Science and Technology Council
Affordable and clean energy
Openalex Percentile: Top 15%
Photovoltaic System Optimization Techniques
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