Comparative Analysis of Voltage Segmentation (0.8Voc) and Sensorless MPPT Algorithms in PV Pump Systems Operating Under Partial Shading Conditions

Year 2025, Volume: 15 Issue: 1, 1 - 7

Yunus Atagün , Reşat Çelikel

Abstract

When photovoltaic (PV) irrigation systems operate under partial shading conditions (PSC), traditional methods are insufficient. In addition to modified traditional methods, artificial intelligence and optimization-based smart methods are used to obtain maximum power from PV systems operating under PSC. These methods use one or more of the PV system's current, voltage, and atmospheric environment variables. In this study, a sensorless Maximum Power Point Tracking (MPPT) algorithm was developed. The proposed algorithm uses the values of the current and speed of the Brushless Direct Current Motor(BLDC) which used in the PV irrigation system. The current, voltage and other parameters of the PV system was not used. The proposed algorithm was compared the 0.8Voc method that used panel data. The proposed MPPT algorithm was tested with a simulation study created in the MATLAB/Simulink environment. In the simulation study, four different PSCs were created and the 0.8Voc method was compared with the proposed method. The obtained results are shown graphically. Accordingly, the superiority of the proposed method was observed in all cases except for the PSC2 case. On the other hand, there is a clear superiority in the speed of the 0.8Voc method. The proposed sensorless MPPT technique operated the PV pump system with high efficiency as 99.9% in the case of PSC1, 95% in the case of PSC2, 99.9% in the case of PSC3 and 99.7% in the case of PSC4.

Keywords

PV pump, Partial shading, Sensorless MPPT, BLDC, 0.8Voc

Kısmi Gölgelenme Koşullarında Çalışan FV Pompa Sistemlerinde 0.8Voc ve Algılayıcısız MGNİ Algoritmalarının Karşılaştırılmalı Analizi

Abstract

Fotovoltaik (FV) sulama sistemleri kısmi gölgeleme koşullarında (KGK) çalıştığında geleneksel yöntemler yetersiz kalmaktadır. KGK altında FV sistemlerden maksimum güç elde etmek için modifiye edilmiş geleneksel yöntemlerin yanı sıra yapay zekâ ve optimizasyona dayalı akıllı yöntemler de kullanılmaktadır. Bu yöntemler FV sistemin akım, gerilim ve atmosferik ortam değişkenlerinden bir veya daha fazlasını kullanır. Bu çalışmada algılayıcısız bir Maksimum Güç Noktası İzleme (MGNİ) algoritması geliştirilmiştir. Önerilen algoritma, FV sulama sisteminde kullanılan Fırçasız Doğru Akım Motorunun (FDAM) akım ve hız değerlerini kullanmaktadır. FV sistemin akım, gerilim ve diğer parametreleri kullanmamaktadır. Önerilen algoritma, panel verileri kullanan 0.8Voc yöntemiyle karşılaştırılmıştır. Önerilen MGNİ algoritması MATLAB/Simulink ortamında oluşturulan bir simülasyon çalışmasıyla test edilmiştir. Simülasyon çalışmasında dört farklı KGK oluşturulmuş ve 0.8Voc yöntemi önerilen yöntemle karşılaştırılmıştır. Elde edilen sonuçlar grafiksel olarak gösterilmektedir. Buna göre önerilen yöntemin üstünlüğü KGK2 durumu dışındaki tüm durumlarda gözlenmiştir. Öte yandan 0.8Voc yönteminin hızında da bariz bir üstünlük görülmektedir.

Keywords

FV pompa, Kısmi gölgelenme, Algılayıcısız MGNİ, FDAM, 0.8Voc

References

• [1] Gündoğdu, A. (2022). System identification based ARV-MPPT technique for PV systems under variable atmospheric conditions. IEEE Access, 10, 51325-51342.W.-K. Chen, Linear Networks and Systems. Belmont, CA, USA: Wadsworth, 1993, pp. 123–135.
• [2] Liu, L., Meng, X., & Liu, C. (2016). A review of maximum power point tracking methods of PV power system at uniform and partial shading. Renewable and Sustainable Energy Reviews, 53, 1500-1507.
• [3] Ahmed, J., & Salam, Z. (2015). An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency. Applied Energy, 150, 97-108.
• [4] J. Ahmed and Z. Salam, ‘‘A modified P&O maximum power point tracking method with reduced steady-state oscillation and improved tracking efficiency,’’ IEEE Trans. Sustain. Energy, vol. 7, no. 4, pp. 1506–1515, Oct. 2016.
• [5] A. Loukriz, M. Haddadi, and S. Messalti, ‘‘Simulation and experimental design of a new advanced variable step size incremental conductance MPPT algorithm for PV systems,’’ ISA Trans., vol. 62, pp. 30–38, May 2016.
• [6] Başoğlu, M. E. (2018). An improved 0.8 Voc model based GMPPT technique for module level photovoltaic power optimizers. IEEE Transactions on Industry Applications, 55(2), 1913-1921.
• [7] Bi, Z., Ma, J., Man, K. L., Smith, J. S., Yue, Y., & Wen, H. (2020). An Enhanced 0.8Voc-Model-Based Global Maximum Power Point Tracking Method for Photovoltaic Systems. IEEE Transactions on Industry Applications, 56(6), 6825-6834.
• [8] Kesilmiş, Z., Karabacak, M. A., & Aksoy, M. (2020). A novel MPPT method based on inflection voltages. Journal of Cleaner Production, 266, 121473.
• [9] Li, X., Zhu, Y., Wen, H., Du, Y., & Xiao, W. (2022). Reference-voltage-line-aided power incremental algorithm for photovoltaic GMPPT and partial shading detection. IEEE Transactions on Sustainable Energy, 13(3), 1756-1770.
• [10] Celikel, R., Yilmaz, M., & Gundogdu, A. (2022). A voltage scanning-based MPPT method for PV power systems under complex partial shading conditions. Renewable Energy, 184, 361-373.
• [11] Aquib, M., Jain, S., & Ghosh, S. (2022). A technique for tracking the global peak of PV arrays during partially shaded conditions using the detection of current source and voltage source regions of I–V curves. IEEE Journal of Emerging and Selected Topics in Industrial Electronics, 3(4), 1096-1105.
• [12] Ye, S. P., Liu, Y. H., Pai, H. Y., Sangwongwanich, A., & Blaabjerg, F. (2023). A novel ANN-based GMPPT method for PV systems under complex partial shading conditions. IEEE Transactions on Sustainable Energy, 15(1), 328-338.
• [13] Anh, T. V., Trieu, T. N., Nghi, P. V. H., & Van Hien, B. (2024). Fast and accurate GMPPT based on modified P&O algorithm. IEEE Access.
• [14] Renaudineau, H., Donatantonio, F., Fontchastagner, J., Petrone, G., Spagnuolo, G., Martin, J. P., & Pierfederici, S. (2014). A PSO-based global MPPT technique for distributed PV power generation. IEEE Transactions on Industrial Electronics, 62(2), 1047-1058.
• [15] Hussaian Basha, C. H., Bansal, V., Rani, C., Brisilla, R. M., & Odofin, S. (2020). Development of cuckoo search MPPT algorithm for partially shaded solar PV SEPIC converter. In Soft Computing for Problem Solving: SocProS 2018, Volume 1 (pp. 727-736). Springer Singapore.
• [16] Mohanty, S., Subudhi, B., & Ray, P. K. (2015). A new MPPT design using grey wolf optimization technique for photovoltaic system under partial shading conditions. IEEE Transactions on Sustainable Energy, 7(1), 181-188.
• [17] Kumar, C. S., & Rao, R. S. (2016). A novel global MPP tracking of photovoltaic system based on whale optimization algorithm. International Journal of Renewable Energy Development, 5(3), 225-232.
• [18] Kumar, R., & Singh, B. (2019). Solar PV powered‐sensorless BLDC motor driven water pump. IET Renewable Power Generation, 13(3), 389-398.
• [19] Kumar, R., & Singh, B. (2016). BLDC motor-driven solar PV array-fed water pumping system employing zeta converter. IEEE Transactions on Industry Applications, 52(3), 2315-2322.
• [20] Mudlapur, A., Ramana, V. V., Damodaran, R. V., Balasubramanian, V., & Mishra, S. (2018). Effect of partial shading on PV fed induction motor water pumping systems. IEEE Transactions on Energy Conversion, 34(1), 530-539.
• [21] Ammar, A., Hamraoui, K., Belguellaoui, M., & Kheldoun, A. (2022). Performance enhancement of photovoltaic water pumping system based on BLDC Motor under partial shading condition. Engineering Proceedings, 14(1), 22.
• [22] Celikel, R., Boztas, G., & Aydogmus, O. (2022). A system identification-based MPPT algorithm for solar photovoltaic pumping system under partial shading conditions. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 44(2), 5199-5214.
• [23] Jha, K. K., & Anwar, M. N. (2019, September). Solar photovoltaic based brushless DC motor driven water pumping system using PSO-MPPT algorithm. In 2019 54th International Universities Power Engineering Conference (UPEC) (pp. 1-6). IEEE.
• [24] Akkaya, R., Kulaksız, A. A., & Aydoğdu, Ö. (2007). DSP implementation of a PV system with GA-MLP-NN based MPPT controller supplying BLDC motor drive. Energy Conversion and Management, 48(1), 210-218.
• [25] Oliver, J. S., David, P. W., Balachandran, P. K., & Mihet-Popa, L. (2022). Analysis of grid-interactive PV-fed BLDC pump using optimized MPPT in DC–DC converters. Sustainability, 14(12), 7205.