Maximum Power Point Tracking with Incremental Conductance and Fuzzy Logic Controller in Solar Energy Systems

Yıl 2024, Cilt: 11 Sayı: 1, 120 - 130, 13.03.2024

Murat Lüy , Nuri Alper Metin , Zafer Civelek

https://doi.org/10.31202/ecjse.1310705

Cited By: 2

Öz

Energy benefits both individuals and nations. Humanity's reliance on fossil fuels an inability to respond increases depletion. Energy supplies are rapidly decreasing. Electricity use causes the energy crisis. Sustainable energy largely meets the energy demand of the growing population. In addition, it benefits the environment by reducing carbon emissions. This situation sustainable energy sources have supplemented traditional energy sources and promoted sustainable energy use. Solar, wind, and fuel cell energy are given example of sustainable energy. Power generating facilities are employed nowadays because of their extended lifespan, inexpensive maintenance, no hazardous waste, and independence from dwindling energy sources. Solar power generation depends on environmental circumstances, hence MPP generation must be observed. MPPT follow solar panel highest MPP. This study involves a system is comprised by a DC-DC boost converter, PV panel, and a ohmic load. The duty ratio is generated by the IC and FLC MPPT algorithms, and the PWM signal is generated by comparing it with the triangle wave. This generated signal is applied to the DC-DC boost converter. The aim of this research is to investigate the effectiveness, variability, and duration required to attain the MPP of the implemented MPPT methods. The system has been developed within the MATLAB/Simulink framework. Based on the findings of the simulation, it has been determined that the FLC MPPT algorithm achieves the MPP at a faster rate compared to the IC MPPT algorithm. Consequently, the level of fluctuation is minimum and the efficiency is high.

Anahtar Kelimeler

Fuzzy Logic Controller (FLC), Incremental Conductance (IC), Maximum Power Point Tracking (MPPT)

Kaynakça

• [1] Ö. F. Tozlu and H. Çalık. A review and classification of most used mppt algorithms for photovoltaic systems. Hittite J. Sci. Eng., 8(3):207–220, 2021.
• [2] L. K. Narwat and J. Dhillon. Design and operation of fuzzy logic based mppt controller under uncertain condition. J. Phys. Conf. Ser., 1854(1), 2021.
• [3] B. Bendib, F. Krim, H. Belmili, M. F. Almi, and S. Boulouma. Advanced fuzzy mppt controller for a stand-alone pv system. Energy Procedia, 50:383–392, 2014.
• [4] M. Lüy, F. Türk, and N. A. Metin. Fotovoltaik sistemlerde maksimum güç noktası takibi İçin değiştir – gözle, artan İletkenlik ve parçacık sürü optimizasyon algoritmalarının karşılaştırılması. Uluslararası Muhendis. Arastirma ve Gelistirme Derg., 13(3):202–214, 2021.
• [5] J. K. Shiau, Y. C. Wei, and B. C. Chen. A study on the fuzzy-logic-based solar power mppt algorithms using different fuzzy input variables. Algorithms, 8(2):100–127, 2015.
• [6] M. Teke, A. S. M. Arjeelı, and F. Korkmaz. Pv sistemler için mppt kontrol cihazı tasarımı ve karşılaştırılması. International Journal of Engineering Research and Development, 15(1):1–15, 2023.
• [7] C. Vimalarani, N. Kamaraj, and C. B. B. Improved method of maximum power point tracking of photovoltaic (pv) array using hybrid intelligent controller. Optik (Stuttg)., 168:403–415, 2018.
• [8] A. Djalab, M. M. Rezaoui, A. Teta, and M. Boudiaf. Analysis of mppt methods: P o, inc and fuzzy logic (clf) for a pv system. In 2018 6th Int. Conf. Control Eng. Inf. Technol. CEIT 2018, 2018.
• [9] J. Reddy and S. Natarajan. Control and analysis of mppt techniques for stand-alone pv system with high voltage gain interleaved boost converter. Gazi Univ. J. Sci., 31(2):515–530, 2018.
• [10] P. C. Cheng, B. R. Peng, Y. H. Liu, Y. S. Cheng, and J. W. Huang. Optimisation of a fuzzy-logic-control-based mppt algorithm using the particle swarm optimization technique. Energies, 8(6):5338–5360, 2015.
• [11] K. Kayisli. Super twisting sliding mode-type 2 fuzzy mppt control of solar pv system with parameter optimization under variable irradiance conditions. Ain Shams Eng. J., 14(1):101950, 2023.
• [12] H. Abouobaida, Y. Mchaouar, Y. Abouelmahjoub, H. Mahmoudi, A. Abbou, and M. Jamil. Performance optimization of the inc-cond fuzzy mppt based on a variable step for photovoltaic systems. Optik (Stuttg)., 278(January):170657, 2023.
• [13] L. Farah, A. Haddouche, and A. Haddouche. Comparison between proposed fuzzy logic and anfis for mppt control for photovoltaic system. Int. J. Power Electron. Drive Syst., 11(2):1065–1073, 2020.
• [14] S. Singh, S. Manna, M. I. H. Mansoori, and A. K. Akella. Implementation of perturb observe mppt technique using boost converter in pv system. In Int. Conf. Comput. Intell. Smart Power Syst. Sustain. Energy, CISPSSE 2020, pages 29–32, 2020. .
• [15] L. M. Satapathy, A. Harshita, M. Saif, P. K. Dalai, and S. Jena. Comparative analysis of boost and buck-boost converter in photovoltaic power system under varying irradiance using mppt. Proc. Int. Conf. Inven. Commun. Comput. Technol. ICICCT 2018, 2018.
• [16] R. Ahmed and S. C. Mohonta. Comprehensive analysis of mppt techniques using boost converter for solar pv system. In 2020 2nd Int. Conf. Sustain. Technol. Ind. 4.0, STI 2020, pages 19–20, 2020.
• [17] S. Manna and A. K. Akella. Novel lyapunov-based rapid and ripple-free mppt using a robust model reference adaptive controller for solar pv system. Prot. Control Mod. Power Syst., 8(1), 2023. .
• [18] R. I. Putri, S. Wibowo, and M. Rifa’i. Maximum power point tracking for photovoltaic using incremental conductance method. Energy Procedia, 68:22–30, 2015.
• [19] U. Badak and A. B. Yıldız. Maksimum güç noktası İzleyici algoritmalarının verim, salınım miktarı ve yakınsama süresi açısından karşılaştırılması. Eur. J. Sci. Technol., (21):463–472, 2021. .
• [20] A. Safari and S. Mekhilef. Simulation and hardware implementation of incremental conductance mppt with direct control method using cuk converter. IEEE Trans. Ind. Electron., 58(4):1154–1161, 2011.
• [21] S. Saravanan and N. R. Babu. Maximum power point tracking algorithms for photovoltaic system - a review. Renew. Sustain. Energy Rev., 57(2):192–204, 2016.
• [22] M. Y. Baramadeh, M. A. A. Abouelela, and S. M. Alghuwainem. Maximum power point tracker controller using fuzzy logic control with battery load for photovoltaics systems. Smart Grid Renew. Energy, 12(10):163–181, 2021. .
• [23] A. M. Noman, K. E. Addoweesh, and H. M. Mashaly. A fuzzy logic control method for mppt of pv systems. In IECON Proc. Industrial Electron. Conf., pages 874–880, 2012.
• [24] A. S. Samosir, H. Gusmedi, S. Purwiyanti, and E. Komalasari. Modeling and simulation of fuzzy logic based maximum power point tracking (mppt) for pv application. Int. J. Electr. Comput. Eng., 8(3):1315–1323, 2018.