Abstract
The objective of this paper is to study the performance of a photovoltaic (PV) system controlled by two types of Maximum Power Point Tracking (MPPT) commands under a rapid change in load. These commands are, respectively, perturb and observe (P &O) and improved fuzzy logic (FL) based on two types of algorithms: Mamdani and Takagi-Sugeno (TS). These improved FL commands are based on two inputs which represent the slope of the power-current curve and changes of this slope instead of the power-voltage curve slope. The designed PV system consists of a typical PV panel (1Soltech 1STH215-P) feeding a resistive load via a (DC/DC) converter where the MOSFET is controlled by PWM signal generated by the MPPT control. The simulation results obtained using MATLAB/Simulink environment show that the performance of the boost converter is very satisfactory (97%) in efficiency and that FL-Mamdani, and FL-TS MPPTs controls are more efficient than the classical P &O. Indeed, the comparison of different performance parameters, such as PV system efficiency and response time to achieve MPP, shows that the PV system efficiency obtained by fuzzy logic method is about 99.60% for FL-Mamdani, 99.64% for FL-TS and 99.20% for P &O method under the rapid change in load. In addition, the response time is shorter for FL methods (25.7 ms for FL-Mamdani and 21.9 ms for FL-TS) than in P &O method which records 31.5 ms. Furthermore, the proposed FL controls (FL-Mamdani and FL-TS) reduce the oscillations obtained by the P &O method and converge quickly to the maximum power point (MPP) regardless the load change.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
El Motahhir S, El Hammoumi A, Ghzizal A (2018) Photovoltaic system with quantitative comparative between an improved MPPT and existing INC and P &O methods under fast varying of solar irradiation. Energy Rep 4:341–350. https://doi.org/10.1016/j.egyr.2018.04.003
Gupta AK, Chauhan YK, Maity T (2018) Experimental investigations and comparison of various MPPT techniques for photovoltaic system. Indian Acad Sci 43:132. https://doi.org/10.1007/s12046-018-0815-0
Singh K, Anand A, Mishra AK, Singh B, Sahay K (2021) SEPIC converter for solar PV array fed battery charging in DC homes. J Inst Eng (India) 102:455–463. https://doi.org/10.1007/s40031-020-00522-0
Guenounou O, Boutaib D, Chabour F (2014) Adaptive fuzzy controller based MPPT for photovoltaic systems. J Energy Convers Manage 78:843–850. https://doi.org/10.1016/j.enconman.2013.07.093
Suganthi L, Iniyan S, Samuel AA (2015) Applications of fuzzy logic in renewable energy systems. J Renew Sustain Energy Rev 48:585–607. https://doi.org/10.1016/j.rser.2015.04.037
Radjai T, Gaubert J-P, Rahmani L (2014) The new FLC-variable incremental conductance MPPT with direct control method using Cuk converter. In: 2014 IEEE 23rd international symposium on industrial electronics (ISIE), pp 2508–2513. https://doi.org/10.1109/ISIE.2014.6865014
Ait Cheikh M-S, Larbes C, Tchoketch Kebir G-F, Zerguerras A (2007) Maximum power point tracking using a fuzzy logic control scheme. Rev Energ Renouvelables 10:387–395
Rahmani R, Seyedmahmoudian M, Mekhilef S, Yusof R (2013) Implementation of fuzzy logic maximum power point tracking controller for photovoltaic system. Am J Appl Sci 3:209–218. https://doi.org/10.3844/ajassp.2013.209.218
Aicha D, Rezaoui M, Teta A, Boudiaf M (2019) The MPPT command for a PV system comparative study: control based on fuzzy logic with “P &O’’. Renew Energy Smart Sustain Cities 62:346–354. https://doi.org/10.1016/j.rser.2015.04.037
Khlifi Y, Aziz A (2018) Efficient energy utilization of stand alone photovoltaic system under rapid change in load. AIP Conf Proc 2056:SP-020026. https://doi.org/10.1063/1.5084999
Yilmaz U, Kircay A, Borekci S (2018) PV system fuzzy logic MPPT method and PI control as a charge controller. Renew Sustain Energy Rev 81:994–1001. https://doi.org/10.1016/j.rser.2017.08.048
Othmani H, Chaouali H, Mezghani D, Mami A (2015) Optimisation de la technique de perturbation et observation par la logique floue. In: 3ème confèrence internationale des ènergies renouvelables. CIER-2015. Int J Sci Res Eng Technol (IJSET) 4:140–144
Bounechba H, Bouzid A, Nabti K, Benalla H (2014) Comparison of perturb and observe and fuzzy logic in maximum power point tracker for PV systems. J Energy Proc 50:667–684. https://doi.org/10.1016/j.egypro.2014.06.083
Kiswantono A, Prasetyo E, Amirullah A (2019) Comparative performance of mitigation voltage sag/swell and harmonics using DVR-BES-PV system with MPPT-fuzzy Mamdani/MPPT-fuzzy Sugeno. J Int J Intell Eng Syst 12:222–235. https://doi.org/10.22266/ijies2019.0430.22
Bendib B, Belmili H, Krim F (2015) A survey of the most used MPPT methods: conventional and advanced algorithms applied for photovoltaic systems. J Renew Sustain Energy Rev 45:637–648. https://doi.org/10.1016/j.rser.2015.02.009
Khlifi Y, Hajji B, Messaoudi A (2019) A new maximum power point tracking PV control for rapid changes in irradiation level. In: Proceedings of the 1st international conference on electronic engineering and renewable energy, vol 512, pp 384–391. https://doi.org/10.1007/978-981-13-1405-6-46
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Boutaybi, M., Khlifi, Y., Bekkay, H. (2023). Efficient Fuzzy Logic MPPT Controls for Sudden Change in Load. In: Bekkay, H., Mellit, A., Gagliano, A., Rabhi, A., Amine Koulali, M. (eds) Proceedings of the 3rd International Conference on Electronic Engineering and Renewable Energy Systems. ICEERE 2022. Lecture Notes in Electrical Engineering, vol 954. Springer, Singapore. https://doi.org/10.1007/978-981-19-6223-3_50
Download citation
DOI: https://doi.org/10.1007/978-981-19-6223-3_50
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-6222-6
Online ISBN: 978-981-19-6223-3
eBook Packages: EnergyEnergy (R0)