Enhanced Incremental Conductance MPPT with Adjustable Reference Current and Scheduled-Gain Using a Power Zoning Strategy for Flyback-Based Photovoltaic Inverter Systems

Efficient and reliable Maximum Power Point Tracking (MPPT) is crucial for photovoltaic (PV) systems, particularly under rapidly changing irradiance and temperature. This paper proposes an enhanced MPPT algorithm that extends the traditional Incremental Conductance (IncCond) method by introducing an adjustable reference current and scheduled-gain, coordinated through a power zoning strategy that suits current-source inverter or converter. Unlike conventional approaches based on voltage-source converters that adjust duty cycle or input voltage, the proposed method employs current-driven control tailored to distinct power regions, enabling faster and more accurate tracking. The algorithm was developed and validated in MATLAB/Simulink, providing a rigorous simulation environment to evaluate its dynamic performance. Results show that the proposed method achieves negligible overshoot, with deviations corrected in less than 16 milliseconds and maximum overshoot limited to under 2 W, even under extreme operating conditions such as 0˚C. Within normal operating ranges and near rated power, oscillations are minimal, overcoming the common drawbacks of conventional IncCond methods that suffer from slower convergence and steady-state oscillations. The findings confirm that the scheduled-gain power-zoning framework ensures a superior balance of transient speed, steady-state accuracy, and system stability, offering a practical and efficient solution for real-time PV applications in variable environments.

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Publication Details

Journal
Journal of Power and Energy Engineering
Published
2025-01-01
DOI
https://doi.org/10.4236/jpee.2025.139018
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Enhanced Incremental Conductance MPPT with Adjustable Reference Current and Scheduled-Gain Using a Power Zoning Strategy for Flyback-Based Photovoltaic Inverter Systems

Maaspaliza Azri, Faridah Hanim Mohd Noh, Suhaidi Shafie, Mohd Amran Mohd Radzi et al.
Journal of Power and Energy Engineering
Photovoltaic System Optimization Techniques
article

Enhanced Incremental Conductance MPPT with Adjustable Reference Current and Scheduled-Gain Using a Power Zoning Strategy for Flyback-Based Photovoltaic Inverter Systems

Maaspaliza Azri, Faridah Hanim Mohd Noh, Suhaidi Shafie, Mohd Amran Mohd Radzi, Muhamad Faizal Yaakub, Norhafiz Azis, AAhmad Naji Zaidan
article en

Abstract

Efficient and reliable Maximum Power Point Tracking (MPPT) is crucial for photovoltaic (PV) systems, particularly under rapidly changing irradiance and temperature. This paper proposes an enhanced MPPT algorithm that extends the traditional Incremental Conductance (IncCond) method by introducing an adjustable reference current and scheduled-gain, coordinated through a power zoning strategy that suits current-source inverter or converter. Unlike conventional approaches based on voltage-source converters that adjust duty cycle or input voltage, the proposed method employs current-driven control tailored to distinct power regions, enabling faster and more accurate tracking. The algorithm was developed and validated in MATLAB/Simulink, providing a rigorous simulation environment to evaluate its dynamic performance. Results show that the proposed method achieves negligible overshoot, with deviations corrected in less than 16 milliseconds and maximum overshoot limited to under 2 W, even under extreme operating conditions such as 0˚C. Within normal operating ranges and near rated power, oscillations are minimal, overcoming the common drawbacks of conventional IncCond methods that suffer from slower convergence and steady-state oscillations. The findings confirm that the scheduled-gain power-zoning framework ensures a superior balance of transient speed, steady-state accuracy, and system stability, offering a practical and efficient solution for real-time PV applications in variable environments.

Journal of Power and Energy EngineeringVol. 13(09)
Universiti Putra Malaysia, Universiti Teknikal Malaysia Melaka
Openalex Percentile: Top 83%
Photovoltaic System Optimization Techniques
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