New adaptive modified perturb and observe algorithm for maximum power point tracking in photovoltaic systems with interleaved boost converter
Introduction. In recent years, maximum power point tracking (MPPT) has become a critical component in photovoltaic (PV) systems to ensure maximum energy harvesting under varying irradiance and temperature conditions. Among the most common algorithms, perturb and observe (P&O) and incremental...
Збережено в:
| Дата: | 2025 |
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| Автори: | , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
National Technical University "Kharkiv Polytechnic Institute" and Аnatolii Pidhornyi Institute of Power Machines and Systems of NAS of Ukraine
2025
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| Теми: | |
| Онлайн доступ: | http://eie.khpi.edu.ua/article/view/339002 |
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| Назва журналу: | Electrical Engineering & Electromechanics |
Репозитарії
Electrical Engineering & Electromechanics| Резюме: | Introduction. In recent years, maximum power point tracking (MPPT) has become a critical component in photovoltaic (PV) systems to ensure maximum energy harvesting under varying irradiance and temperature conditions. Among the most common algorithms, perturb and observe (P&O) and incremental conductance (IC) are widely adopted due to their simplicity and effectiveness. Problem. Conventional P&O suffers from steady-state oscillations and slow dynamic response, while IC requires higher computational complexity and loses accuracy under rapidly changing conditions. These drawbacks limit overall tracking efficiency and system reliability. The goal of this work is the development and evaluation of a novel adaptive modified perturb and observe (AM-P&O) algorithm for a PV system with an interleaved boost converter. The proposed method dynamically adjusts the perturbation step size to achieve faster convergence and lessen steady-state oscillations to enhance tracking efficiency. Its performance is assessed through simulation with varying irradiance. It is then compared to traditional methods (P&O and IC) using quantitative metrics such as convergence time, oscillation magnitude, tracking efficiency, and computational cost. Methodology. The AM-P&O algorithm introduces an adaptive step size adjustment strategy, in which the perturbation magnitude is dynamically tuned according to the slope of the PV power-voltage curve. A detailed PV system and converter model was developed in MATLAB/Simulink, and simulations were performed under varying irradiance conditions. Performance metrics include tracking efficiency, convergence time, steady-state oscillation amplitude, and computational complexity. Results. The proposed AM-P&O achieves a better tracking, reduces convergence time by approximately 35 %, and decreases steady-state oscillations by nearly 90 % compared to conventional P&O. Under fast irradiance variations, the AM-P&O also demonstrates superior dynamic performance with lower computational burden compared to IC. Scientific novelty of this work lies in the adaptive perturbation mechanism, which balances fast convergence and reduced oscillations without increasing algorithmic complexity. Practical value. The AM-P&O provides a practical MPPT solution for PV systems, ensuring higher energy yield and improved stability in real-world applications, thereby supporting more efficient renewable energy integration into power networks. References 32, tables 8, figures 8. |
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