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Improved Fuzzy MPPT to Solve Partial Shading Conditions Problem in a Photovoltaic System

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This paper presents a hybrid maximum power point tracker for a photovoltaic (PV) system. The proposed technique combines between the advantage of fuzzy logic flexibility and the linearity of the β parameter method to override the problem of Partial Shading Conditions (PSC). The proposed approach can resolve the problem of PSC by tracking the Global Maximum Power Point (MPP) regardless of the shading conditions to which the PV system is submitted. For evaluating the presented technique, the Perturb and Observe command and a conventional FLC have been implemented too. Extended simulations with different meteorological conditions and scenarios of PSC are performed. The obtained results clearly show the superiority of the β-FLC tracker presented in terms of response time in the transient state and the steady-state error around MPP. The tracker presents also better effectiveness in the presence of PSC because it can reach up to 20.51% of the surplus of transmitted power compared to the other trackers presented.
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Beta Parameter Method; Fuzzy Logic Controller; Maximum Power Point Trackers; Partial Shading Conditions; Photovoltaic System

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A. Sharma M. Sharma, Power energy optimization in solar photovoltaic and concentrated solar power systems, in 2017 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), nov. 2017, p. 1-6.

A. Fathy, T. M. Alanazi, H. Rezk, D. Yousri, Optimal energy management of micro-grid using sparrow search algorithm, Energy Rep., vol. 8, p. 758-773, Nov. 2022.

A. I. M. Ali, H. R. A. Mohamed, Improved P&O MPPT algorithm with efficient open-circuit voltage estimation for two-stage grid-integrated PV system under realistic solar radiation, Int. J. Electr. Power Energy Syst., vol. 137, p. 107805, May 2022.

H. Abouadane, A. Fakkar, D. Sera, A. Lashab, S. Spataru, T. Kerekes, Multiple-Power-Sample Based P&O MPPT for Fast-Changing Irradiance Conditions for a Simple Implementation, IEEE J. Photovolt., vol. 10, no 5, p. 1481-1488, Sept. 2020.

P. Singh, N. Shukla, P. Gaur, Modified variable step incremental-conductance MPPT technique for photovoltaic system, Int. J. Inf. Technol., vol. 13, no 6, p. 2483-2490, Dec. 2021.

Y. Triki, A. Bechouche, H. Seddiki, D. O. Abdeslam, An Improved Incremental Conductance Based MPPT Algorithm for Photovoltaic Systems, in IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society, Toronto, ON, Canada, oct. 2021, p. 1-6.

L. F. C. Monteiro, C. M. Freitas, M. D. Bellar, Improvements on the Incremental Conductance MPPT Method Applied to a PV String with Single-Phase to Three-Phase Converter for Rural Grid Applications, Adv. Electr. Comput. Eng., vol. 19, n° 1, p. 63-70, 2019.

Y. C. Im, S. S. Kwak, J. Park, . S. Kim, Intermittent FOCV Using an I-V Curve Tracer for Minimizing Energy Loss, Appl. Sci., vol. 11, no 19, p. 9006, Sept. 2021.

R. Marroquín-Arreola et al., Design of an MPPT Technique for the Indirect Measurement of the Open-Circuit Voltage Applied to Thermoelectric Generators, Energies, vol. 15, no 10, 2022.

LESIA Laboratory, ENSAI, University of LESIA Laboratory, ENSAI, University of Ngaoundere. Cameroon. Cameroon, C. B. Nzoundja Fapi, P. Wira, M. Kamta, IRIMAS Laboratory, University of Haute Alsace. France, Real-Time Experimental Assessment of a New MPPT Algorithm Based on the Direct Detection of the Short-Circuit Current for a PV System, Renew. Energy Power Qual. J., vol. 19, p. 598-603, Sept. 2021.

C. B. Nzoundja Fapi, P. Wira, M. Kamta, Real-time experimental assessment of a new MPPT algorithm based on the direct detection of the short-circuit current for a PV system, Renew. Energy Power Qual. J., vol. 19, p. 598-603, 2021.

A. S. Samosir, H. Gusmedi, S. Purwiyanti, et E. Komalasari, Modeling and Simulation of Fuzzy Logic based Maximum Power Point Tracking (MPPT) for PV Application, Int. J. Electr. Comput. Eng. IJECE, vol. 8, no 3, p. 1315, June 2018.

Z. Massaq, A. Abounada, M. Ramzi, Fuzzy and predictive control of a photovoltaic pumping system based on three-level boost converter, Bull. Electr. Eng. Inform., vol. 10, no 3, p. 1183-1192, June 2021.

G. A. Madrigal et al., Fuzzy logic-based maximum power point tracking solar battery charge controller with backup stand-by AC generator, Indones. J. Electr. Eng. Comput. Sci., vol. 16, no 1, p. 136, oct. 2019.

A. M. Kassem, MPPT control design and performance improvements of a PV generator powered DC motor-pump system based on artificial neural networks, Int. J. Electr. Power Energy Syst., vol. 43, no 1, p. 90-98, Dec. 2012.

H. Chojaa, A. Derouich, S. E. Chehaidia, O. Zamzoum, M. Taoussi, et H. Elouatouat, Integral sliding mode control for DFIG based WECS with MPPT based on artificial neural network under a real wind profile, Energy Rep., vol. 7, p. 4809-4824, Nov. 2021.

D. P. Hohm, M. E. Ropp, Comparative study of maximum power point tracking algorithms, Prog. Photovolt. Res. Appl., vol. 11, no 1, p. 47-62, Jan. 2003.

J. Ahmed et Z. Salam, An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency, Appl. Energy, vol. 150, p. 97-108, July. 2015.

M. Rezoug, R. Chenni, D. Taibi, Fuzzy Logic-Based Perturb and Observe Algorithm with Variable Step of a Reference Voltage for Solar Permanent Magnet Synchronous Motor Drive System Fed by Direct-Connected Photovoltaic Array, Energies, vol. 11, no 2, p. 462, Feb. 2018.

R. Bennia, C. Larbes, F. Belhachat, Maximum Power Point Tracking Under Fast Changing Irradiance Using Hybrid Fuzzy-PO Algorithm, in Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities, vol. 361, M. Hatti, Éd. Cham: Springer International Publishing, 2022, p. 155-166.

O. Guenounou, B. Dahhou, F. Chabour, Adaptive fuzzy controller based MPPT for photovoltaic systems, Energy Convers. Manag., vol. 78, p. 843-850, Feb. 2014.

X. Li, H. Wen, Y. Hu, L. Jiang, A novel beta parameter based fuzzy-logic controller for photovoltaic MPPT application, Renew. Energy, vol. 130, p. 416-427, Jan. 2019.

S. Jain, V. Agarwal, A New Algorithm for Rapid Tracking of Approximate Maximum Power Point in Photovoltaic Systems, Power Electron. Lett. IEEE, vol. 2, p. 16-19, Apr. 2004.

K. Amara et al., Improved Performance of a PV Solar Panel with Adaptive Neuro Fuzzy Inference System ANFIS based MPPT, in 2018 7th International Conference on Renewable Energy Research and Applications (ICRERA), Paris, oct. 2018, p. 1098-1101.

D. Mlakić, L. Majdandžić, S. Nikolovski, ANFIS Used as a Maximum Power Point Tracking Algorithm for a Photovoltaic System, Int. J. Electr. Comput. Eng. IJECE, vol. 8, no 2, p. 867, Apr. 2018.

A. Muthu, Comparative analysis of fuzzy and ANFIS based MPPT controller for wind power generation system, Int. J. Appl. Power Eng. IJAPE, vol. 10, no 4, p. 355, Dec. 2021.

S. Narthana, P. M. Thiruvengadam, et J. Gnanavadivel, Adaptive neuro-fuzzy approach for maximum power point tracking with high gain converter for photo voltaic applications, Int. J. Adv. Technol. Eng. Explor., vol. 9, no 93, p. 1168-1182, 2022.

R. Thankakan, E. R. Samuel Nadar, ANFIS-Based MPPT Controller of the Thermoelectric Energy Harvesting System for DC Micro-grid Applications, Arab. J. Sci. Eng., vol. 46, n° 2, p. 1137-1154, 2021.

K.-Y. Chou, Y.-W. Yeh, Y.-T. Chen, Y.-M. Cheng, Y.-P. Chen, Adaptive Neuro Fuzzy Inference System Based MPPT Algorithm applied to Photovoltaic Systems under Partial Shading Conditions, 2020 International Automatic Control Conference, CACS 2020, 2020.

P.-C. Cheng, B.-R. Peng, Y.-H. Liu, Y.-S. Cheng, J.-W. Huang, Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique, Energies, vol. 8, no 6, p. 5338-5360, June 2015.

A. Jouda, F. Elyes, A. Rabhi, et M. Abdelkader, Optimization of Scaling Factors of Fuzzy-MPPT Controller for Stand-alone Photovoltaic System by Particle Swarm Optimization, Energy Procedia, vol. 111, p. 954-963, March 2017.

S. Figueiredo, R. Nayana Alencar Leao e Silva Aquino, Hybrid MPPT Technique PSO-P&O Applied to Photovoltaic Systems Under Uniform and Partial Shading Conditions, IEEE Lat. Am. Trans., vol. 19, no 10, p. 1610-1617, Oct. 2021.

J. Farzaneh, A hybrid modified FA-ANFIS-P&O approach for MPPT in photovoltaic systems under PSCs, Int. J. Electron., vol. 107, no 5, p. 703-718, May 2020.

P. Verma, R. Garg, et P. Mahajan, Asymmetrical Fuzzy Logic Control Based MPPT Algorithm For Stand-Alone PV SYSTEM Under Partially Shaded Conditions, Scientia Iranica D (2020) 27(6), 3162-3174.

Z. Bi, J. Ma, K. L. Man, J. S. Smith, Y. Yue, H. Wen, Global MPPT Method for Photovoltaic Systems Operating under Partial Shading Conditions using the 0.8VOC Model, in 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Genova, Italy, June 2019, p. 1-6.

Z. Bi, H. Wen, An Enhanced 0.8VOC-model-based Global Maximum Power Point Tracking Method for Photovoltaic Systems, IEEE Trans. Ind. Appl., p. 9.

M. E. Başoğlu, B. Çakır, Hybrid global maximum power point tracking approach for photovoltaic power optimisers, IET Renew. Power Gener., vol. 12, no 8, p. 875-882, June 2018.

Y.-H. Ji, D.-Y. Jung, J.-G. Kim, J.-H. Kim, T.-W. Lee, et C.-Y. Won, A Real Maximum Power Point Tracking Method for Mismatching Compensation in PV Array Under Partially Shaded Conditions, IEEE Trans. Power Electron., vol. 26, no 4, p. 1001-1009 Apr. 2011.

B. N. Alajmi, K. H. Ahmed, S. J. Finney, B. W. Williams, A Maximum Power Point Tracking Technique for Partially Shaded Photovoltaic Systems in Microgrids, IEEE Trans. Ind. Electron., vol. 60, no 4, p. 1596-1606, avr. 2013.

X. Li, H. Wen, Y. Hu, L. Jiang, et W. Xiao, Modified Beta Algorithm for GMPPT and Partial Shading Detection in Photovoltaic Systems, IEEE Trans. Power Electron., vol. 33, no 3, p. 2172-2186, March 2018.

V. Bhan et al., Performance Evaluation of Perturb and Observe Algorithm for MPPT with Buck-Boost Charge Controller in Photovoltaic Systems, J. Control Autom. Electr. Syst., vol. 32, no 6, p. 1652-1662, Dec. 2021.


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