Maximum Power Point Tracking Achievements and Challenges in Photovoltaic Systems

Year 2023, Volume: 7 Issue: 2, 40 - 47, 30.06.2023

Ahmed Mousa

Abstract

The ever-increasing demand for electrical energy in recent decades has necessitated the exploration of alternative energy sources, one of which is solar energy. The most practical means of utilizing solar energy is through the use of a Photovoltaic (PV) system. Nevertheless, the energy harvested by PV modules is constrained by low conversion efficiency, nonlinearity, and susceptibility to weather conditions, such as temperature and irradiance levels. To address these limitations, Maximum Power Point Tracking (MPPT) techniques have been developed to optimize the output of PV systems under specific circumstances. This academic article provides an in-depth analysis of the most widely used MPPT techniques, utilizing both traditional and soft computing methods. The article discusses the fundamental principles and practical applications of these techniques, as well as the challenges associated with MPPT, such as coping with rapidly changing irradiance and partial shading scenarios.

Keywords

Photovoltaic (PV), maximum power point tracking (MPPT), partial shading, fast irradiance

References

• [1] M. E. Başoğlu, “Comprehensive review on distributed maximum power point tracking: Submodule level and module level MPPT strategies,” Sol. Energy, vol. 241, pp. 85–108, 2022, doi: https://doi.org/10.1016/j.solener.2022.05.039.
• [2] P. Bharadwaj and V. John, “Optimized Global Maximum Power Point Tracking of Photovoltaic Systems Based on Rectangular Power Comparison,” IEEE Access, vol. 9, pp. 53602–53616, 2021, doi: 10.1109/ACCESS.2021.3071136.
• [3] W. Zhang, G. Zhou, H. Ni, and Y. Sun, “A Modified Hybrid Maximum Power Point Tracking Method for Photovoltaic Arrays Under Partially Shading Condition,” IEEE Access, vol. 7, pp. 160091–160100, 2019, doi: 10.1109/ACCESS.2019.2950375.
• [4] S. K. Cherukuri et al., “Power Enhancement in Partial Shaded Photovoltaic System Using Spiral Pattern Array Configuration Scheme,” IEEE Access, vol. 9, pp. 123103–123116, 2021, doi: 10.1109/ACCESS.2021.3109248.
• [5] H. Delavari and M. Zolfi, “Maximum power point tracking in photovoltaic systems using indirect adaptive fuzzy robust controller,” Soft Comput., vol. 25, no. 16, pp. 10969–10985, 2021, doi: 10.1007/s00500-021-05823-0.
• [6] A. Gani and M. Sekkeli, “Experimental evaluation of type-2 fuzzy logic controller adapted to real environmental conditions for maximum power point tracking of solar energy systems,” Int. J. Circuit Theory Appl., vol. 50, no. 11, pp. 4131–4145, 2022, doi: https://doi.org/10.1002/cta.3374.
• [7] K. Nora, A. Idir, S. Grouni, and M. S. Boucherit, “A New Combined Method for Tracking The Global Maximum Power Point Of Photovoltaic Systems,” Rev. Roum. des Sci. Tech. Série Électrotechnique Énergétique, vol. 64, p. 2022, 2022.
• [8] Z. Kesilmiş, “A manhattan metric based perturb and observe maximum power point tracking algorithm for photovoltaic systems,” Energy Sources, Part A Recover. Util. Environ. Eff., vol. 44, pp. 469–492, 2022, doi: 10.1080/15567036.2022.2046662.
• [9] T. Sutikno, A. C. Subrata, and A. Elkhateb, “Evaluation of Fuzzy Membership Function Effects for Maximum Power Point Tracking Technique of Photovoltaic System,” IEEE Access, vol. 9, pp. 109157–109165, 2021, doi: 10.1109/ACCESS.2021.3102050.
• [10] L. Tightiz, S. Mansouri, F. Zishan, J. Yoo, and N. Shafaghatian, “Maximum Power Point Tracking for Photovoltaic Systems Operating under Partially Shaded Conditions Using SALP Swarm Algorithm,” Energies, vol. 15, p. 8210, 2022, doi: 10.3390/en15218210.
• [11] F. Sedaghati, A. Nahavandi, M. A. Badamchizadeh, S. Ghaemi, and M. Abedinpour Fallah, “PV Maximum Power-Point Tracking by Using Artificial Neural Network,” Math. Probl. Eng., vol. 2012, p. 506709, 2012, doi: 10.1155/2012/506709.
• [12] I. Mandourarakis, V. Gogolou, E. Koutroulis, and S. Siskos, “Integrated Maximum Power Point Tracking System for Photovoltaic Energy Harvesting Applications,” IEEE Trans. Power Electron., vol. 37, no. 8, pp. 9865–9875, 2022, doi: 10.1109/TPEL.2022.3156400.
• [13] S. Mumtaz, S. Ahmad, L. Khan, S. Ali, T. Kamal Khan, and S. Hassan, “Adaptive Feedback Linearization Based NeuroFuzzy Maximum Power Point Tracking for a Photovoltaic System,” Energies, vol. 11, p. 606, 2018, doi: 10.3390/en11030606.
• [14] R. K. Phanden, L. Sharma, J. Chhabra, and H. İ. Demir, “A novel modified ant colony optimization based maximum power point tracking controller for photovoltaic systems,” Mater. Today Proc., vol. 38, pp. 89–93, 2021, doi: https://doi.org/10.1016/j.matpr.2020.06.020.
• [15] M. Shamseldein, “Unconstrained model and merge sorted serpentine arrangement method for dynamic reconfiguration of large PV arrays,” Energy Convers. Manag. X, vol. 16, p. 100320, 2022, doi: https://doi.org/10.1016/j.ecmx.2022.100320.
• [16] R. Rouphael, N. Maamri, and J.-P. Gaubert, “Dynamic Maximum Power Point Tracking Method including Detection of Varying Partial Shading Conditions for Photovoltaic Systems,” in 2022 24th European Conference on Power Electronics and Applications (EPE’22 ECCE Europe), 2022, pp. 1–8.
• [17] U. C. Turhal and Y. Onal, “Maximum Power Point Estimation Based on Operating Conditions Classification for Photovoltaic Systems: A Case Study for Partial Shading,” Acta Phys. Pol. A, vol. 142, no. 2, pp. 256–265, 2022, doi: 10.12693/APhysPolA.142.256.
• [18] M. H. Osman, M. K. Ahmed, A. Refaat and N. V. Korovkin, "A Comparative Study of MPPT for PV System Based on Modified Perturbation & Observation Method," 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus), St. Petersburg, Moscow, Russia, 2021, pp. 1023-1026, doi: 10.1109/ElConRus51938.2021.9396444.
• [19] A. B. M. I. F.-B. A. Y. A. Roberto I. Rico-Camacho Luis J. Ricalde, “Transient Differentiation Maximum Power Point Tracker (Td-MPPT) for Optimized Tracking under Very Fast-Changing Irradiance: A Theoretical Approach for Mobile PV Applications,” Appl. Sci., vol. 12, no. 5, p. 2671, 2022, doi: 10.3390/app12052671.
• [20] U. ur Rehman, P. Faria, L. Gomes, and Z. Vale, “Artificial Neural Network Based Efficient Maximum Power Point Tracking for Photovoltaic Systems,” in 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2022, pp. 1–6, doi: 10.1109/EEEIC/ICPSEurope54979.2022.9854613.
• [21] A. F. Mirza, M. Mansoor, K. Zhan, and Q. Ling, “High-efficiency swarm intelligent maximum power point tracking control techniques for varying temperature and irradiance,” Energy, vol. 228, p. 120602, 2021, doi: https://doi.org/10.1016/j.energy.2021.120602.
• [22] K. Unal, G. Bal, S. Oncu, and N. Ozturk, “MPPT Design for PV-Powered WPT System with Irregular Pulse Density Modulation,” Electr. Power Components Syst., vol. 51, no. 1, pp. 83–91, 2023, doi: 10.1080/15325008.2022.2161674.