A critical evaluation of maximum power point tracking techniques for PV systems working under partial shading conditions

Year 2023, , 73 - 81, 15.01.2023

Fuad Alhaj Omar , Nihat Pamuk , Ahmet Afşin Kulaksız

https://doi.org/10.31127/tuje.1032674

Cited By: 7

Abstract

Photovoltaic (PV) energy is a promising source of renewable energy which is sturdy and environmentally friendly. PV generation systems, once installed, produce electricity from solar irradiance without emitting greenhouse gases. To maximize the output power of PV systems, the maximum power point tracking system has been employed (MPPT). The MPPT constitutes a fundamental part of PV systems. In recent years, a large number of MPPT techniques have been proposed. This paper is set up to critically review some of the proposed maximum power point tracking (MPPT) techniques to handle the emergence of multiple MPPs in PV panel characteristics due to the partial shading conditions (PSCs). To define the working principle and the pros and cons of the different proposed techniques clearly and sequentially, they are divided into three groups as follows: conventional MPPT techniques, improved MPPT techniques and artificial intelligence- based MPPT techniques to deal with PSCs. The paper also critically summarizes the findings in terms of their performance in capturing the global maximum power point (GMPP) for PV systems operating under PSCs.

Keywords

Photovoltaic system, Maximum power point tracking, Partial shading conditions, Global tracking, Artificial intelligence

References

• Burrett, R., Clini, C., Dixon, R., Eckhart, M., El-Ashry, M., Gupta, D., ... & Ballesteros, A. R. (2009). Renewable Energy Policy Network for the 21st Century.
• Jäger-Waldau, A. (2019). PV status report 2019. Publications Office of the European Union: Luxembourg.
• Cheng, P. C., Peng, B. R., Liu, Y. H., Cheng, Y. S., & Huang, J. W. (2015). Optimization of a fuzzy-logic-control-based MPPT algorithm using the particle swarm optimization technique. Energies, 8(6), 5338-5360.
• Alhajomar, F., Gokkus, G., & Kulaksiz, A. A. (2019). Rapid control prototyping based on 32-Bit ARM Cortex-M3 microcontroller for photovoltaic MPPT algorithms. International Journal of Renewable Energy Research-IJRER.
• Mule, S., Hardas, R., & Kulkarni, N. R. (2016, March). P&O, IncCon and Fuzzy Logic implemented MPPT scheme for PV systems using PIC18F452. In 2016 international conference on wireless communications, signal processing and networking (WiSPNET) (pp. 1320-1325). IEEE.
• Anwer, A. M. O., Omar, F. A., & Kulaksiz, A. A. (2020). Design of a fuzzy logic-based MPPT controller for a PV system employing sensorless control of MRAS-based PMSM. International Journal of Control, Automation and Systems, 18(11), 2788-2797.
• Mohanty, P., Bhuvaneswari, G., Balasubramanian, R., & Dhaliwal, N. K. (2014). MATLAB based modeling to study the performance of different MPPT techniques used for solar PV system under various operating conditions. Renewable and Sustainable Energy Reviews, 38, 581-593.
• Rezk, H., & Eltamaly, A. M. (2015). A comprehensive comparison of different MPPT techniques for photovoltaic systems. Solar energy, 112, 1-11.
• Ram, J. P., Babu, T. S., & Rajasekar, N. (2017). A comprehensive review on solar PV maximum power point tracking techniques. Renewable and Sustainable Energy Reviews, 67, 826-847.
• Kwan, T. H., & Wu, X. (2017). High performance P&O based lock-on mechanism MPPT algorithm with smooth tracking. Solar Energy, 155, 816-828.
• Omar, F. A., Gökkuş, G., & Kulaksız, A. A. (2019). Şebekeden bağımsız FV sistemde maksimum güç noktası takip algoritmalarının değişken hava şartları altında karşılaştırmalı analizi. Konya Mühendislik Bilimleri Dergisi, 7(3), 585-594.
• Elgendy, M. A. (2016, March). Comparative investigation on hill climbing MPPT algorithms at high perturbation rates. In 2016 7th International Renewable Energy Congress (IREC) (pp. 1-6). IEEE.
• Shebani, M. M., Iqbal, T., & Quaicoe, J. E. (2016, October). Comparing bisection numerical algorithm with fractional short circuit current and open circuit voltage methods for MPPT photovoltaic systems. In 2016 IEEE Electrical Power and Energy Conference (EPEC) (pp. 1-5). IEEE.
• Paz, F., & Ordonez, M. (2016). High-performance solar MPPT using switching ripple identification based on a lock-in amplifier. IEEE Transactions on Industrial Electronics, 63(6), 3595-3604.
• Mojallizadeh, M. R., Badamchizadeh, M., Khanmohammadi, S., & Sabahi, M. (2016). Designing a new robust sliding mode controller for maximum power point tracking of photovoltaic cells. Solar Energy, 132, 538-546.
• Kamarzaman, N. A., & Tan, C. W. (2014). A comprehensive review of maximum power point tracking algorithms for photovoltaic systems. Renewable and Sustainable Energy Reviews, 37, 585-598.
• Anwer, A. M. O., Omar, F. A., Bakir, H., & Kulaksiz, A. A. (2020). Sensorless Control of a PMSM Drive Using EKF for Wide Speed Range Supplied by MPPT Based Solar PV System. Elektronika ir Elektrotechnika, 26(1), 32-39.
• Obukhov, S. G., Plotnikov, I. A., & Sheryazov, S. K. (2016, May). Methods of effective use of solar power system. In 2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM) (pp. 1-6). IEEE.
• Husain, M. A., Tariq, A., Hameed, S., Arif, M. S. B., & Jain, A. (2017). Comparative assessment of maximum power point tracking procedures for photovoltaic systems. Green Energy & Environment, 2(1), 5-17.
• Liu, F., Kang, Y., Zhang, Y., & Duan, S. (2008, June). Comparison of P&O and hill climbing MPPT methods for grid-connected PV converter. In 2008 3rd IEEE Conference on Industrial Electronics and Applications (pp. 804-807). IEEE.
• Shah, K. B., & Joshi, L. P. (2013, November). Comparative analysis of incremental conductance base MPPT for multi-string photovoltaic system. In 2013 Nirma University International Conference on Engineering (NUiCONE) (pp. 1-6). IEEE.
• Seyedmahmoudian, M., Horan, B., Soon, T. K., Rahmani, R., Oo, A. M. T., Mekhilef, S., & Stojcevski, A. (2016). State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems–A review. Renewable and Sustainable Energy Reviews, 64, 435-455.
• Ji, Y. H., Jung, D. Y., Kim, J. G., Kim, J. H., Lee, T. W., & Won, C. Y. (2010). A real maximum power point tracking method for mismatching compensation in PV array under partially shaded conditions. IEEE Transactions on power electronics, 26(4), 1001-1009.
• Lei, P., Li, Y., & Seem, J. E. (2011). Sequential ESC-based global MPPT control for photovoltaic array with variable shading. IEEE Transactions on Sustainable Energy, 2(3), 348-358.
• Ghasemi, M. A., Foroushani, H. M., & Parniani, M. (2015). Partial shading detection and smooth maximum power point tracking of PV arrays under PSC. IEEE Transactions on Power Electronics, 31(9), 6281-6292.
• Patel, H., & Agarwal, V. (2008). Maximum power point tracking scheme for PV systems operating under partially shaded conditions. IEEE transactions on industrial electronics, 55(4), 1689-1698.
• Nguyen, T. L., & Low, K. S. (2010). A global maximum power point tracking scheme employing DIRECT search algorithm for photovoltaic systems. IEEE transactions on Industrial Electronics, 57(10), 3456-3467.
• Boztepe, M., Guinjoan, F., Velasco-Quesada, G., Silvestre, S., Chouder, A., & Karatepe, E. (2013). Global MPPT scheme for photovoltaic string inverters based on restricted voltage window search algorithm. IEEE transactions on Industrial Electronics, 61(7), 3302-3312.
• Femia, N., Lisi, G., Petrone, G., Spagnuolo, G., & Vitelli, M. (2008). Distributed maximum power point tracking of photovoltaic arrays: Novel approach and system analysis. IEEE Transactions on Industrial Electronics, 55(7), 2610-2621.
• Kobayashi, K., Takano, I., & Sawada, Y. (2006). A study of a two-stage maximum power point tracking control of a photovoltaic system under partially shaded insolation conditions. Solar energy materials and solar cells, 90(18-19), 2975-2988.
• Miyatake, M., Inada, T., Hiratsuka, I., Zhao, H., Otsuka, H., & Nakano, M. (2004, August). Control characteristics of a fibonacci-search-based maximum power point tracker when a photovoltaic array is partially shaded. In The 4th International Power Electronics and Motion Control Conference, 2004. IPEMC 2004. (Vol. 2, pp. 816-821). IEEE.
• Kazmi, S. M. R., Goto, H., Ichinokura, O., & Guo, H. J. (2009, September). An improved and very efficient MPPT controller for PV systems subjected to rapidly varying atmospheric conditions and partial shading. In 2009 Australasian Universities Power Engineering Conference (pp. 1-6). IEEE.
• Ahmed, J., & Salam, Z. (2017). An accurate method for MPPT to detect the partial shading occurrence in a PV system. IEEE transactions on industrial informatics, 13(5), 2151-2161.
• Koutroulis, E., & Blaabjerg, F. (2012). A new technique for tracking the global maximum power point of PV arrays operating under partial-shading conditions. IEEE journal of photovoltaics, 2(2), 184-190.
• Kermadi, M., Salam, Z., Ahmed, J., & Berkouk, E. M. (2018). An effective hybrid maximum power point tracker of photovoltaic arrays for complex partial shading conditions. IEEE Transactions on Industrial Electronics, 66(9), 6990-7000.
• Furtado, A. M., Bradaschia, F., Cavalcanti, M. C., & Limongi, L. R. (2017). A reduced voltage range global maximum power point tracking algorithm for photovoltaic systems under partial shading conditions. IEEE Transactions on Industrial Electronics, 65(4), 3252-3262.
• Wang, Y., Li, Y., & Ruan, X. (2015). High-accuracy and fast-speed MPPT methods for PV string under partially shaded conditions. IEEE Transactions on Industrial Electronics, 63(1), 235-245.
• Bayod-Rújula, Á. A., & Cebollero-Abián, J. A. (2014). A novel MPPT method for PV systems with irradiance measurement. solar energy, 109, 95-104.
• Chen, K., Tian, S., Cheng, Y., & Bai, L. (2014). An improved MPPT controller for photovoltaic system under partial shading condition. IEEE transactions on sustainable energy, 5(3), 978-985.
• Manickam, C., Raman, G. P., Raman, G. R., Ganesan, S. I., & Chilakapati, N. (2016). Efficient global maximum power point tracking technique for a partially shaded photovoltaic string. IET Power Electronics, 9(14), 2637-2644.
• Manickam, C., Raman, G. R., Raman, G. P., Ganesan, S. I., & Nagamani, C. (2016). A hybrid algorithm for tracking of GMPP based on P&O and PSO with reduced power oscillation in string inverters. IEEE Transactions on Industrial Electronics, 63(10), 6097-6106.
• Balasankar, R., Arasu, G. T., & Raj, J. C. M. (2017). A global MPPT technique invoking partitioned estimation and strategic deployment of P&O to tackle partial shading conditions. Solar energy, 143, 73-85.
• Tatabhatla, V. M. R., Agarwal, A., & Kanumuri, T. (2019). Performance enhancement by shade dispersion of Solar Photo-Voltaic array under continuous dynamic partial shading conditions. Journal of cleaner production, 213, 462-479.
• Kouchaki, A., Iman-Eini, H., & Asaei, B. (2013). A new maximum power point tracking strategy for PV arrays under uniform and non-uniform insolation conditions. Solar Energy, 91, 221-232.
• Liu, Y. H., Chen, J. H., & Huang, J. W. (2014). Global maximum power point tracking algorithm for PV systems operating under partially shaded conditions using the segmentation search method. Solar Energy, 103, 350-363.
• Seyedmahmoudian, M., Rahmani, R., Mekhilef, S., Oo, A. M. T., Stojcevski, A., Soon, T. K., & Ghandhari, A. S. (2015). Simulation and hardware implementation of new maximum power point tracking technique for partially shaded PV system using hybrid DEPSO method. IEEE transactions on sustainable energy, 6(3), 850-862.
• Liu, Y. H., Huang, S. C., Huang, J. W., & Liang, W. C. (2012). A particle swarm optimization-based maximum power point tracking algorithm for PV systems operating under partially shaded conditions. IEEE transactions on energy conversion, 27(4), 1027-1035.
• Daraban, S., Petreus, D., & Morel, C. (2014). A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading. Energy, 74, 374-388.
• Efendi, M. Z., Murdianto, F. D., & Setiawan, R. E. (2017, September). Modeling and simulation of MPPT sepie converter using modified PSO to overcome partial shading impact on DC microgrid system. In 2017 International Electronics Symposium on Engineering Technology and Applications (IES-ETA) (pp. 27-32). IEEE.
• Lyden, S., & Haque, M. E. (2015). A simulated annealing global maximum power point tracking approach for PV modules under partial shading conditions. IEEE Transactions on Power Electronics, 31(6), 4171-4181.
• Kumar, N., Hussain, I., Singh, B., & Panigrahi, B. K. (2017). Rapid MPPT for uniformly and partial shaded PV system by using JayaDE algorithm in highly fluctuating atmospheric conditions. IEEE Transactions on Industrial Informatics, 13(5), 2406-2416.
• Huang, C., Wang, L., Yeung, R. S. C., Zhang, Z., Chung, H. S. H., & Bensoussan, A. (2017). A prediction model-guided Jaya algorithm for the PV system maximum power point tracking. IEEE Transactions on sustainable energy, 9(1), 45-55.
• Sundareswaran, K., Vigneshkumar, V., Sankar, P., Simon, S. P., Nayak, P. S. R., & Palani, S. (2015). Development of an improved P&O algorithm assisted through a colony of foraging ants for MPPT in PV system. IEEE transactions on industrial informatics, 12(1), 187-200.
• Lian, K. L., Jhang, J. H., & Tian, I. S. (2014). A maximum power point tracking method based on perturb-and-observe combined with particle swarm optimization. IEEE journal of photovoltaics, 4(2), 626-633.
• Ishaque, K., & Salam, Z. (2012). A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition. IEEE transactions on industrial electronics, 60(8), 3195-3206.
• Kollimalla, S. K., & Mishra, M. K. (2014). A novel adaptive P&O MPPT algorithm considering sudden changes in the irradiance. IEEE Transactions on Energy conversion, 29(3), 602-610.
• Shah, N., & Chudamani, R. (2012, December). A novel algorithm for global peak power point tracking in partially shaded grid-connected PV system. In 2012 IEEE International Conference on Power and Energy (PECon) (pp. 558-563). IEEE.
• Mahamudul, H., Saad, M., & Ibrahim Henk, M. (2013). Photovoltaic system modeling with fuzzy logic based maximum power point tracking algorithm. International Journal of Photoenergy, 2013.
• Ahmed, J., & Salam, Z. (2014). A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability. Applied energy, 119, 118-130.
• Eltamaly, A. M., & Farh, H. M. (2019). Dynamic global maximum power point tracking of the PV systems under variant partial shading using hybrid GWO-FLC. Solar Energy, 177, 306-316.
• Kaced, K., Larbes, C., Ramzan, N., Bounabi, M., & elabadine Dahmane, Z. (2017). Bat algorithm based maximum power point tracking for photovoltaic system under partial shading conditions. Solar Energy, 158, 490-503.
• Priyadarshi, N., Padmanaban, S., Maroti, P. K., & Sharma, A. (2018). An extensive practical investigation of FPSO-based MPPT for grid integrated PV system under variable operating conditions with anti-islanding protection. IEEE Systems Journal, 13(2), 1861-1871.
• Eltamaly, A. M., Farh, H. M., & Al-Saud, M. S. (2019). Grade point average assessment for metaheuristic GMPP techniques of partial shaded PV systems. IET Renewable Power Generation, 13(8), 1215-1231.
• Oshaba, A. S., Ali, E. S., & Abd Elazim, S. M. (2015). MPPT control design of PV system supplied SRM using BAT search algorithm. Sustainable Energy, Grids and Networks, 2, 51-60.
• Li, G., Jin, Y., Akram, M. W., Chen, X., & Ji, J. (2018). Application of bio-inspired algorithms in maximum power point tracking for PV systems under partial shading conditions–A review. Renewable and Sustainable Energy Reviews, 81, 840-873.
• Sundareswaran, K., Peddapati, S., & Palani, S. (2014). MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies. IEEE transactions on energy conversion, 29(2), 463-472.
• Huang, Y. P., Ye, C. E., & Chen, X. (2018). A modified firefly algorithm with rapid response maximum power point tracking for photovoltaic systems under partial shading conditions. Energies, 11(9), 2284.
• Teshome, D. F., Lee, C. H., Lin, Y. W., & Lian, K. L. (2016). A modified firefly algorithm for photovoltaic maximum power point tracking control under partial shading. IEEE Journal of Emerging and Selected Topics in Power Electronics, 5(2), 661-671.
• Wang, H., Wang, W., Zhou, X., Sun, H., Zhao, J., Yu, X., & Cui, Z. (2017). Firefly algorithm with neighborhood attraction. Information Sciences, 382, 374-387.
• Alhaj Omar, F., & Kulaksiz, A. A. (2021). Experimental evaluation of a hybrid global maximum power tracking algorithm based on modified firefly and perturbation and observation algorithms. Neural Computing and Applications, 33(24), 17185-17208.
• Gupta, A., Chauhan, Y. K., & Pachauri, R. K. (2016). A comparative investigation of maximum power point tracking methods for solar PV system. Solar energy, 136, 236-253.
• Chuang, S. J., Hong, C. M., & Chen, C. H. (2016). Design of intelligent control for stabilization of microgrid system. International Journal of Electrical Power & Energy Systems, 82, 569-578.
• Boukenoui, R., Salhi, H., Bradai, R., & Mellit, A. (2016). A new intelligent MPPT method for stand-alone photovoltaic systems operating under fast transient variations of shading patterns. Solar Energy, 124, 124-142.
• Kotti, R., & Shireen, W. (2015). Efficient MPPT control for PV systems adaptive to fast changing irradiation and partial shading conditions. Solar Energy, 114, 397-407.
• Sundareswaran, K., Sankar, P., Nayak, P. S. R., Simon, S. P., & Palani, S. (2014). Enhanced energy output from a PV system under partial shaded conditions through artificial bee colony. IEEE transactions on sustainable energy, 6(1), 198-209.
• Kow, K. W., Wong, Y. W., Rajkumar, R., & Isa, D. (2018). An intelligent real-time power management system with active learning prediction engine for PV grid-tied systems. Journal of cleaner production, 205, 252-265.
• Kaid, I. E., Hafaifa, A., Guemana, M., Hadroug, N., Kouzou, A., & Mazouz, L. (2018). Photovoltaic system failure diagnosis based on adaptive neuro fuzzy inference approach: South Algeria solar power plant. Journal of Cleaner Production, 204, 169-182.
• Jiang, L. L., Maskell, D. L., & Patra, J. C. (2013). A novel ant colony optimization-based maximum power point tracking for photovoltaic systems under partially shaded conditions. Energy and Buildings, 58, 227-236.
• Soufyane, B. A., Chouder, A., Kara, K., & Silvestre, S. (2015). Artificial bee colony-based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions. Applied Soft Computing, 32, 38-48.
• 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.
• Lyden, S., & Haque, M. E. (2015). A simulated annealing global maximum power point tracking approach for PV modules under partial shading conditions. IEEE Transactions on Power Electronics, 31(6), 4171-4181.