New adaptive modified perturb and observe algorithm for maximum power point tracking in photovoltaic systems with interleaved boost converter
DOI:
https://doi.org/10.20998/2074-272X.2025.6.08Keywords:
photovoltaic system, maximum power point tracking, adaptive step size, modified perturb and observe algorithm, interleaved DC- DC converter, tracking efficiencyAbstract
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.
References
Katche M.L., Makokha A.B., Zachary S.O., Adaramola M.S. A Comprehensive Review of Maximum Power Point Tracking (MPPT) Techniques Used in Solar PV Systems. Energies, 2023, vol. 16, no. 5, art. no. 2206. doi: https://doi.org/10.3390/en16052206.
Endiz M.S., Gökkuş G., Coşgun A.E., Demir H. A Review of Traditional and Advanced MPPT Approaches for PV Systems Under Uniformly Insolation and Partially Shaded Conditions. Applied Sciences, 2025, vol. 15, no. 3, art. no. 1031. doi: https://doi.org/10.3390/app15031031.
Ali M.H., Zakaria M., El-Tawab S. A comprehensive study of recent maximum power point tracking techniques for photovoltaic systems. Scientific Reports, 2025, vol. 15, no. 1, art. no. 14269. doi: https://doi.org/10.1038/s41598-025-96247-5.
Alombah N.H., Harrison A., Mbasso W.F., Belghiti H., Fotsin H.B., Jangir P., Al-Gahtani S.F., Elbarbary Z.M.S. Multiple-to-single maximum power point tracking for empowering conventional MPPT algorithms under partial shading conditions. Scientific Reports, 2025, vol. 15, no. 1, art. no. 14540. doi: https://doi.org/10.1038/s41598-025-98619-3.
Sun C., Ling J., Wang J. Research on a novel and improved incremental conductance method. Scientific Reports, 2022, vol. 12, no. 1, art. no. 15700. doi: https://doi.org/10.1038/s41598-022-20133-7.
Ye S.-P., Liu Y.-H., Liu C.-Y., Ho K.-C., Luo Y.-F. Artificial Neural Network Assisted Variable Step Size Incremental Conductance MPPT Method with Adaptive Scaling Factor. Electronics, 2021, vol. 11, no. 1, art. no. 43. doi: https://doi.org/10.3390/electronics11010043.
Singh Chawda G., Prakash Mahela O., Gupta N., Khosravy M., Senjyu T. Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions. Applied Sciences, 2020, vol. 10, no. 13, art. no. 4575. doi: https://doi.org/10.3390/app10134575.
Mahmod Mohammad A.N., Mohd Radzi M.A., Azis N., Shafie S., Atiqi Mohd Zainuri M.A. An Enhanced Adaptive Perturb and Observe Technique for Efficient Maximum Power Point Tracking Under Partial Shading Conditions. Applied Sciences, 2020, vol. 10, no. 11, art. no. 3912. doi: https://doi.org/10.3390/app10113912.
Amal Z. Advanced Perturb and Observe Algorithm for Maximum Power Point Tracking in Photovoltaic Systems with Adaptive Step Size. Journal of Automation, Mobile Robotics and Intelligent Systems, 2024, pp. 55-60. doi: https://doi.org/10.14313/JAMRIS/3-2024/22.
Djilali A.B., Bounadja E., Yahdou A., Benbouhenni H., Elbarbary Z.M.S., Colak I., Al-Gahtani S.F. Enhanced variable step sizes perturb and observe MPPT control to reduce energy loss in photovoltaic systems. Scientific Reports, 2025, vol. 15, no. 1, art. no. 11700. doi: https://doi.org/10.1038/s41598-025-95309-y.
Subudhi B., Pradhan R. A Comparative Study on Maximum Power Point Tracking Techniques for Photovoltaic Power Systems. IEEE Transactions on Sustainable Energy, 2013, vol. 4, no. 1, pp. 89-98. doi: https://doi.org/10.1109/TSTE.2012.2202294.
Boubaker O. MPPT techniques for photovoltaic systems: a systematic review in current trends and recent advances in artificial intelligence. Discover Energy, 2023, vol. 3, no. 1, art. no. 9. doi: https://doi.org/10.1007/s43937-023-00024-2.
Naima B., Belkacem B., Ahmed T., Benbouhenni H., Riyadh B., Samira H., Sarra Z., Elbarbary Z.M.S., Mohammed S.A. Enhancing MPPT optimization with hybrid predictive control and adaptive P&O for better efficiency and power quality in PV systems. Scientific Reports, 2025, vol. 15, no. 1, art. no. 24559. doi: https://doi.org/10.1038/s41598-025-10335-0.
Nagadurga T., Raju V.D., Barnawi A.B., Bhutto J.K., Razak A., Wodajo A.W. Global MPPT optimization for partially shaded photovoltaic systems. Scientific Reports, 2025, vol. 15, no. 1, art. no. 10831. doi: https://doi.org/10.1038/s41598-025-89694-7.
Chtita S., Motahhir S., El Hammoumi A., Chouder A., Benyoucef A.S., El Ghzizal A., Derouich A., Abouhawwash M., Askar S.S. A novel hybrid GWO–PSO-based maximum power point tracking for photovoltaic systems operating under partial shading conditions. Scientific Reports, 2022, vol. 12, no. 1, art. no. 10637. doi: https://doi.org/10.1038/s41598-022-14733-6.
Melhaoui M., Rhiat M., Oukili M., Atmane I., Hirech K., Bossoufi B., Almalki M.M., Alghamdi T.A.H., Alenezi M. Hybrid fuzzy logic approach for enhanced MPPT control in PV systems. Scientific Reports, 2025, vol. 15, no. 1, art. no. 19235. doi: https://doi.org/10.1038/s41598-025-03154-w.
Hussain M.T., Sarwar A., Tariq M., Urooj S., BaQais A., Hossain M.A. An Evaluation of ANN Algorithm Performance for MPPT Energy Harvesting in Solar PV Systems. Sustainability, 2023, vol. 15, no. 14, art. no. 11144. doi: https://doi.org/10.3390/su151411144.
Zemmit A., Loukriz A., Belhouchet K., Alharthi Y.Z., Alshareef M., Paramasivam P., Ghoneim S.S.M. GWO and WOA variable step MPPT algorithms-based PV system output power optimization. Scientific Reports, 2025, vol. 15, no. 1, art. no. 7810. doi: https://doi.org/10.1038/s41598-025-89898-x.
Timur O., Uzundağ B.K. Design and Analysis of a Hybrid MPPT Method for PV Systems Under Partial Shading Conditions. Applied Sciences, 2025, vol. 15, no. 13, art. no. 7386. doi: https://doi.org/10.3390/app15137386.
Elsafi A., Almohammedi A.A., Balfaqih M., Balfagih Z., Sabri S. Comparative analysis of maximum power point tracking methods for power optimization in grid tied photovoltaic solar systems. Discover Applied Sciences, 2025, vol. 7, no. 9, art. no. 976. doi: https://doi.org/10.1007/s42452-025-07606-w.
Latreche K., Taleb R., Bentaallah A., Toubal Maamar A.E., Helaimi M., Chabni F. Design and experimental implementation of voltage control scheme using the coefficient diagram method based PID controller for two-level boost converter with photovoltaic system. Electrical Engineering & Electromechanics, 2024, no. 1, pp. 3-9. doi: https://doi.org/10.20998/2074-272X.2024.1.01.
Hosseinpour M., Seifi E., Seifi A., Shahparasti M. Design and analysis of an interleaved step-up DC–DC converter with enhanced characteristics. Scientific Reports, 2024, vol. 14, no. 1, art. no. 14413. doi: https://doi.org/10.1038/s41598-024-65171-5.
Saberi A., Niroomand M., Dehkordi B.M. An Improved P&O Based MPPT for PV Systems with Reduced Steady-State Oscillation. International Journal of Energy Research, 2023, vol. 2023, art. no. 4694583. doi: https://doi.org/10.1155/2023/4694583.
Louarem S., Kebbab F.Z., Salhi H., Nouri H. A comparative study of maximum power point tracking techniques for a photovoltaic grid-connected system. Electrical Engineering & Electromechanics, 2022, no. 4, pp. 27-33. doi: https://doi.org/10.20998/2074-272X.2022.4.04.
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