Improved divide-and-conquer algorithm with ternary ratio for stable MPPT in PV systems under dynamic irradiance conditions

This study proposes an Improved Divide-and-Conquer Algorithm with Ternary Ratio (IDCA-TR) as a Maximum Power Point Tracking (MPPT) method to improve the efficiency and dynamic responsiveness of photovoltaic (PV) systems under varying irradiance conditions. The introduced IDCA-TR employs the power-voltage derivative (dP/dV) to intelligently guide the reduction of the voltage search interval (VSI), enabling faster convergence to the maximum power point (MPP) and improved tracking stability. Simulation results demonstrate that the IDCA-TR achieves up to 50% faster tracking and significantly reduces power oscillations compared to the divide-and-conquer algorithm with ternary ratio (DCA-TR). Under step and Gaussian (G) profiles, the method maintains high tracking speed and robust performance, attaining tracking efficiencies of up to 98.73%. Experimental validation further confirms these outcomes, exhibiting strong agreement with simulation data and underscoring the method’s practical feasibility. The proposed algorithm consistently outperforms the benchmarked MPPT techniques in both convergence speed and power stability, offering a cost-effective, software-based solution suitable for real-world PV applications. This advancement positions IDCA-TR as a compelling candidate for next-generation solar energy systems that demand fast, precise, and reliable MPP tracking under varying environmental conditions.

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Publication Details

Journal
Electrical Engineering
Published
2025-11-20
DOI
https://doi.org/10.1007/s00202-025-03346-7
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Improved divide-and-conquer algorithm with ternary ratio for stable MPPT in PV systems under dynamic irradiance conditions

Maaspaliza Azri, Mohd Zulkifli Ramli, Abdelhak Lekbir, Dhia Elhak Rouabah
Electrical Engineering
Photovoltaic System Optimization Techniques
article

Improved divide-and-conquer algorithm with ternary ratio for stable MPPT in PV systems under dynamic irradiance conditions

Maaspaliza Azri, Mohd Zulkifli Ramli, Abdelhak Lekbir, Dhia Elhak Rouabah
article en

Abstract

This study proposes an Improved Divide-and-Conquer Algorithm with Ternary Ratio (IDCA-TR) as a Maximum Power Point Tracking (MPPT) method to improve the efficiency and dynamic responsiveness of photovoltaic (PV) systems under varying irradiance conditions. The introduced IDCA-TR employs the power-voltage derivative (dP/dV) to intelligently guide the reduction of the voltage search interval (VSI), enabling faster convergence to the maximum power point (MPP) and improved tracking stability. Simulation results demonstrate that the IDCA-TR achieves up to 50% faster tracking and significantly reduces power oscillations compared to the divide-and-conquer algorithm with ternary ratio (DCA-TR). Under step and Gaussian (G) profiles, the method maintains high tracking speed and robust performance, attaining tracking efficiencies of up to 98.73%. Experimental validation further confirms these outcomes, exhibiting strong agreement with simulation data and underscoring the method’s practical feasibility. The proposed algorithm consistently outperforms the benchmarked MPPT techniques in both convergence speed and power stability, offering a cost-effective, software-based solution suitable for real-world PV applications. This advancement positions IDCA-TR as a compelling candidate for next-generation solar energy systems that demand fast, precise, and reliable MPP tracking under varying environmental conditions.

Electrical EngineeringVol. 108(1)
Technical University of Malaysia Malacca (MY), University of Malaya (MY)
Universiti Teknikal Malaysia Melaka
Openalex Percentile: Top 75%
Photovoltaic System Optimization Techniques
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Improved divide-and-conquer algorithm with ternary ratio for stable MPPT in PV systems under dynamic irradiance conditions — Maaspaliza Azri, Mohd Zulkifli Ramli, et al. · Electrical Engineering (2025) | TGRS Research Map | TGRS