Operating conditions like temperature and irradiance fluctuations can significantly reduce the power output of PV systems, presenting a key challenge. Additionally, contemporary MPPT methods demand high computational resources and face difficulties in maintaining optimal PV array output when weather conditions change quickly. The P&O technique, though widely used, falls short in accurate maximum power point tracking amid sudden shifts in solar insolation due to incorrect adjustments in the duty cycle. This effort addresses the problems of drift effect and computing complexity by introducing an improved P&O MPPT approach. The proposed enhanced method along with the variations in the output voltage and power also includes the change in current (dI) of the PV panel. The impact of integrating the current factor dI with traditional MPPT methods with both fixed and variable step sizes was discussed. By implementing the direct duty-cycle technique on a standard boost converter, the efficacy of the suggested approach was confirmed. The suggested approach is validated using MATLAB simulations. Solar photovoltaic (PV) systems' efficiency is largely dependent on its capacity to draw the most power possible under a variety of environmental circumstances. Techniques for Maximum Power Point Tracking (MPPT) are essential for maximising PV system performance. Because of its simplicity and convenience of usage, Perturb and Observe (P&O) is one of the most popular MPPT approaches. Traditional P&O techniques, however, have shortcomings such delayed reaction to dynamic irradiance changes and steady-state oscillations. The hardware-centric examination of P&O approaches is presented in this paper, with particular attention to their real-time implementation, performance assessment, and optimisation tactics for increased productivity. The suggested optimisations are validated by experimental results that show notable gains in response time and power tracking efficiency using both real PV panels and embedded systems.

Keywords:Modified perturb and observe (MP&O), boost converter, adaptive perturb and observe (AP&O), PV panels, MPPT controllers

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1. A. Jafari, T. Khalili, H. Ganjeh Ganjehlou, and A. Bidram, “Optimal integration of renewable energy sources, diesel generators, and demand response program from pollution, financial, and reliability viewpoints: A multi objective approach,” Journal of Cleaner Production. Feb. 2020; 247. Art ID 119100.
2. P. Bhatnagar and R. K. Nema, “Maximum power point tracking control techniques: State-of-the-art in photovoltaic applications,” Renewable and Sustainable Energy Reviews, July 2013; 23: 224–241. https://doi.org/10.1016/j.rser.2013.02.011
3. M. Premkumar, K. Karthick, and R. Sowmya, “A comparative study and analysis on conventional solar PV based DC-DC converters and MPPT techniques,” Indonesian Journal of Electrical Engineering and Computer Science. Sep. 2018; 11(3): 831–838.
4. B. -R. Peng, K. -C. Ho and Y. -H. Liu, "A Novel and Fast MPPT Method Suitable for Both Fast Changing and Partially Shaded Conditions," in IEEE Transactions on Industrial Electronics, vol. 65, no. 4, pp. 3240-3251, April 2018, doi: 10.1109/TIE.2017.2736484.
5. M. A. Elgendy, B. Zahawi and D. J. Atkinson, "Assessment of Perturb and Observe MPPT Algorithm Implementation Techniques for PV Pumping Applications," in IEEE Transactions on Sustainable Energy, vol. 3, no. 1, pp. 21-33, Jan. 2012, doi: 10.1109/TSTE.2011.2168245.
6. YANG, Y., WEN, H. Adaptive perturb and observe maximum power point tracking with current predictive and decoupled power control for grid-connected photovoltaic inverters. J. Mod. Power Syst. Clean Energy 7, 422–432 (2019). https://doi.org/10.1007/s40565-018-0437-x
7. J. Ahmed and Z. Salam, “An enhanced adaptive P&O MPPT for fast and efficient tracking under varying environmental conditions,” IEEE Trans. Sustain. Energy, vol. 9, no. 3, pp. 1487 1496, Jan. 2018.
8. S. K. Kollimalla and M. K. Mishra, "Variable Perturbation Size Adaptive P&O MPPT Algorithm for Sudden Changes in Irradiance," in IEEE Transactions on Sustainable Energy, vol. 5, no. 3, pp. 718-728, July 2014, doi: 10.1109/TSTE.2014.2300162.
9. N. Femia, D. Granozio, G. Petrone, G. Spagnuolo and M. Vitelli, "Predictive & Adaptive MPPT Perturb and Observe Method," in IEEE Transactions on Aerospace and Electronic Systems, vol. 43, no. 3, pp. 934-950, July 2007, doi: 10.1109/TAES.2007.4383584.
10. A. Pandey, N. Dasgupta and A. K. Mukerjee, "High-Performance Algorithms for Drift Avoidance and Fast Tracking in Solar MPPT System," in IEEE Transactions on Energy Conversion, vol. 23, no. 2, pp. 681-689, June 2008, doi: 10.1109/TEC.2007.914201.
11. P. Manoharan et al., "Improved Perturb and Observation Maximum Power Point Tracking Technique for Solar Photovoltaic Power Generation Systems," in IEEE Systems Journal, vol. 15, no. 2, pp. 3024-3035, June 2021, doi: 10.1109/JSYST.2020.3003255.
12. H. M. El-Helw, A. Magdy, and M. I. Marei, “A hybrid maximum power point tracking technique for partially shaded photovoltaic arrays,” IEEE Access, vol. 5, pp. 11900–11908, Jun. 2017

Operating conditions like temperature and irradiance fluctuations can significantly reduce the power output of PV systems, presenting a key challenge. Additionally, contemporary MPPT methods demand high computational resources and face difficulties in maintaining optimal PV array output when weather conditions change quickly. The P&O technique, though widely used, falls short in accurate maximum power point tracking amid sudden shifts in solar insolation due to incorrect adjustments in the duty cycle. This effort addresses the problems of drift effect and computing complexity by introducing an improved P&O MPPT approach. The proposed enhanced method along with the variations in the output voltage and power also includes the change in current (dI) of the PV panel. The impact of integrating the current factor dI with traditional MPPT methods with both fixed and variable step sizes was discussed. By implementing the direct duty-cycle technique on a standard boost converter, the efficacy of the suggested approach was confirmed. The suggested approach is validated using MATLAB simulations. Solar photovoltaic (PV) systems' efficiency is largely dependent on its capacity to draw the most power possible under a variety of environmental circumstances. Techniques for Maximum Power Point Tracking (MPPT) are essential for maximising PV system performance. Because of its simplicity and convenience of usage, Perturb and Observe (P&O) is one of the most popular MPPT approaches. Traditional P&O techniques, however, have shortcomings such delayed reaction to dynamic irradiance changes and steady-state oscillations. The hardware-centric examination of P&O approaches is presented in this paper, with particular attention to their real-time implementation, performance assessment, and optimisation tactics for increased productivity. The suggested optimisations are validated by experimental results that show notable gains in response time and power tracking efficiency using both real PV panels and embedded systems.

Keywords:Modified perturb and observe (MP&O), boost converter, adaptive perturb and observe (AP&O), PV panels, MPPT controllers

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. A. Jafari, T. Khalili, H. Ganjeh Ganjehlou, and A. Bidram, “Optimal integration of renewable energy sources, diesel generators, and demand response program from pollution, financial, and reliability viewpoints: A multi objective approach,” Journal of Cleaner Production. Feb. 2020; 247. Art ID 119100.
2. P. Bhatnagar and R. K. Nema, “Maximum power point tracking control techniques: State-of-the-art in photovoltaic applications,” Renewable and Sustainable Energy Reviews, July 2013; 23: 224–241. https://doi.org/10.1016/j.rser.2013.02.011
3. M. Premkumar, K. Karthick, and R. Sowmya, “A comparative study and analysis on conventional solar PV based DC-DC converters and MPPT techniques,” Indonesian Journal of Electrical Engineering and Computer Science. Sep. 2018; 11(3): 831–838.
4. B. -R. Peng, K. -C. Ho and Y. -H. Liu, "A Novel and Fast MPPT Method Suitable for Both Fast Changing and Partially Shaded Conditions," in IEEE Transactions on Industrial Electronics, vol. 65, no. 4, pp. 3240-3251, April 2018, doi: 10.1109/TIE.2017.2736484.
5. M. A. Elgendy, B. Zahawi and D. J. Atkinson, "Assessment of Perturb and Observe MPPT Algorithm Implementation Techniques for PV Pumping Applications," in IEEE Transactions on Sustainable Energy, vol. 3, no. 1, pp. 21-33, Jan. 2012, doi: 10.1109/TSTE.2011.2168245.
6. YANG, Y., WEN, H. Adaptive perturb and observe maximum power point tracking with current predictive and decoupled power control for grid-connected photovoltaic inverters. J. Mod. Power Syst. Clean Energy 7, 422–432 (2019). https://doi.org/10.1007/s40565-018-0437-x
7. J. Ahmed and Z. Salam, “An enhanced adaptive P&O MPPT for fast and efficient tracking under varying environmental conditions,” IEEE Trans. Sustain. Energy, vol. 9, no. 3, pp. 1487 1496, Jan. 2018.
8. S. K. Kollimalla and M. K. Mishra, "Variable Perturbation Size Adaptive P&O MPPT Algorithm for Sudden Changes in Irradiance," in IEEE Transactions on Sustainable Energy, vol. 5, no. 3, pp. 718-728, July 2014, doi: 10.1109/TSTE.2014.2300162.
9. N. Femia, D. Granozio, G. Petrone, G. Spagnuolo and M. Vitelli, "Predictive & Adaptive MPPT Perturb and Observe Method," in IEEE Transactions on Aerospace and Electronic Systems, vol. 43, no. 3, pp. 934-950, July 2007, doi: 10.1109/TAES.2007.4383584.
10. A. Pandey, N. Dasgupta and A. K. Mukerjee, "High-Performance Algorithms for Drift Avoidance and Fast Tracking in Solar MPPT System," in IEEE Transactions on Energy Conversion, vol. 23, no. 2, pp. 681-689, June 2008, doi: 10.1109/TEC.2007.914201.
11. P. Manoharan et al., "Improved Perturb and Observation Maximum Power Point Tracking Technique for Solar Photovoltaic Power Generation Systems," in IEEE Systems Journal, vol. 15, no. 2, pp. 3024-3035, June 2021, doi: 10.1109/JSYST.2020.3003255.
12. H. M. El-Helw, A. Magdy, and M. I. Marei, “A hybrid maximum power point tracking technique for partially shaded photovoltaic arrays,” IEEE Access, vol. 5, pp. 11900–11908, Jun. 2017