COMPARATIVE STUDY OF SOME FLC-BASED MPPT METHODS FOR PHOTOVOLTAIC SYSTEMS
DOI:
https://doi.org/10.20319/mijst.2017.33.3650Keywords:
Photovoltaic Systems, Maximum Power Point Tracking, Fuzzy Logic Controller, Perturb and ObserveAbstract
In this paper, an asymmetrical and symmetrical fuzzy logic controller (FLC) based maximum power point tracking (MPPT) methods are compared. The input membership function (MF) setting values are calculated based on the power-voltage (P-V) characteristics of the utilized photovoltaic (PV) module at standard technical conditions (STC). Moreover, five and seven triangular (5-tri and 7-tri) MFs are analyzed. The performance comparisons of the different categories of the FLC-based PV MPPT methods are performed using Matlab/Simulink package. A BP SX150S PV module is used in the simulation at STC. According to the simulation results, the asymmetrical FLC-based MPPT method has the superior results in terms of transient and steady state tracking performances for the different numbers of MFs. In the case of 5-tri MFs, the asymmetrical FLC-based MPPT method can enhance the rising time (tr), tracking accuracy, and energy yield by 84%, 0.05%, and 13.25% respectively, compared to the symmetrical FLC. Whereas, in the case of 7-tri MFs, the rising time, tracking accuracy, and extracted energy are enhanced by 86.7%, 0.04%, and 14.72% respectively. The rising time and extracted energy are improved approximately by 10% and 0.08%, respectively, by using 7-tri MFs in the asymmetrical FLC. Consequently and regardless of the number of MFs, the asymmetrical FLC can be used as the most promising MPPT method for improving the overall performance of the PV system.
References
Afandi, M. M., & Chandrarini, D. D. (2015). Optimization of solar energy utilization using concentrated solar hybrid energy harvester (CSHEH) based on smart solar panel and concentrated thermoelectric generator. MATTER: International Journal of Science and Technology, 1(1), 64-75. https://doi.org/10.20319/mijst.2016.s11.6475
Al-Gizi, A. G. (2016). Comparative study of MPPT algorithms under variable resistive load. 2016 International Conference on Applied and Theoretical Electricity (ICATE), 1-6. https://doi.org/10.1109/ICATE.2016.7754611
Al-Gizi, A. G., Craciunescu, A., & Al-Chlaihawi, S. J. (2017). The use of ANN to supervise the PV MPPT based on FLC. 2017 10th International Symposium on Advanced Topics in Electrical Engineering (ATEE), 703-708. https://doi.org/10.1109/ATEE.2017.7905128
Attou, A., Massoum, A., & Chadli, M. (2015). Comparison study of two tracking methods for photovoltaic systems. Rev. Roum. Sci. Techn.–Électrotechn. et Énerg, 60(2), 205-214.
Bellia, A. H., Ramdani, Y., Moulay, F., & Medles, K. (2013). Irradiance and temperature impact on photovoltaic power by design of experiments. Rev. Roum. Sci. Techn.–Électrotechn. et Énerg, 58(3), 284-294.
Bendib, B., Krim, F., Belmili, H., Almi, M., & Boulouma, S. (2014). Advanced fuzzy MPPT controller for a stand-alone PV system. Energy Procedia, 50, 383-392. https://doi.org/10.1016/j.egypro.2014.06.046
Charan, C. R., Laxmi, A. J., & Sangeetha, P. (2017). Optimized energy efficient solution with stand alone PV system. MATTER: International Journal of Science and Technology, 3(1), 16-27. https://doi.org/10.20319/Mijst.2017.31.1627
Eltawil, M. A., & Zhao, Z. (2013). MPPT techniques for photovoltaic applications. Renewable and Sustainable Energy Reviews, 25, 793-813. https://doi.org/10.1016/j.rser.2013.05.022
Harrag, A., & Messalti, S. (2015). Variable step size modified P&O MPPT algorithm using GA-based hybrid offline/online PID controller. Renewable and Sustainable Energy Reviews, 49, 1247-1260. https://doi.org/10.1016/j.rser.2015.05.003
Islam, M. A., Talukdar, A. B., Mohammad, N., & Khan, P. K. (2010). Maximum power point tracking of photovoltaic arrays in Matlab using fuzzy logic controller. 2010 Annual IEEE India Conference (INDICON), 1-4. https://doi.org/10.1109/INDCON.2010.5712680
Papadopoulou, E. (2013). Photovoltaic Industrial Systems An Environmental Approach. Berlin: Springer Berlin. https://doi.org/10.1007/978-3-642-16301-2
Rahma, A., & Khemliche, M. (2014). Combined approach between FLC and PSO to find the best MFs to improve the performance of PV system. 2014 International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM), 1-8. https://doi.org/10.1109/CISTEM.2014.7077038
Subudhi, B., & Pradhan, R. (2013). A comparative study on maximum power point tracking techniques for photovoltaic power systems. IEEE Transactions on Sustainable Energy, 4(1), 89-98. https://doi.org/10.1109/TSTE.2012.2202294
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