Step Incremental Conductance MPPT for Solar PV System Based on Fuzzy Logic Controller
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Keywords

MPPT
Fuzzy logic
Solar PV system
Boost converter
Conductance algorithm

How to Cite

Siva, Harshini, and Sujatha Balaraman. 2022. “Step Incremental Conductance MPPT for Solar PV System Based on Fuzzy Logic Controller”. Journal of Trends in Computer Science and Smart Technology 4 (1): 23-29. https://doi.org/10.36548/jtcsst.2022.1.004.

Abstract

Due to strong industrial expansion, the need for electrical power has increased in recent years. As more than just a by-product of this increased dependence on fossil fuels, resource depletion occurs, and renewable sources such as solar, wind, and wave energy sources have begun to operate as an electricity source and are now playing a key role. Solar energy has been widely used in power systems, particularly in the form of photovoltaic (PV) generating units. Control scheme is a technique for obtaining electricity from a solar photovoltaic system under changing environmental circumstances. The proposed research compares two control methods: incremental conductance algorithm and fuzzy logic, in order to maximise the efficiency of a solar PV system. The algorithms described above change the switching frequency of the power converter to monitor a solar PV array's global MPP. In MATLAB/Simulink, the simulation is run, and the performance is evaluated. The simulated findings imply that the fuzzy logic controller performs better than the incremental conductance technique.

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References

H. Rezk, M. Aly, M. Al-Dhaifallah, and M. Shoyama, ‘‘Design and hardware implementation of new adaptive fuzzy logic-based MPPT control method for photovoltaic applications,’’ IEEE Access, vol. 7, pp. 106427–106438, 2019

B. Subudhi and R. Pradhan, ‘‘A comparative study on maximum power point tracking techniques for photovoltaic power systems,’’ IEEE Trans. Sustain. Energy, vol. 4, no. 1, pp. 89–98, Jan. 2013.

Y.-H. Liu, S.-C. Huang, J.-W. Huang, and W.-C. Liang, ‘‘A particle swarm optimization-based maximum power po;int tracking algorithm for PV sys- tems operating under partially shaded conditions,’’ IEEE Trans. Energy Convers., vol. 27, no. 4, pp. 1027–1035, Dec. 2012.

M. A. G. de Brito, L. Galotto, L. P. Sampaio, G. D. A. e Melo, and C. A. Canesin, ‘‘Evaluation of the main MPPT techniques for photovoltaic applications,’’ IEEE Trans. Ind. Electron., vol. 60, no. 3, pp. 1156–1167, Mar. 2013

R.Mahalakshmi, Aswin Kumar.A., Aravind Kumar, “Design of Fuzzy Logic Based Maximum Power Point Tracking Controller for Solar Array for Cloudy Weather Conditions,” IEEE Power and Energy System: Towards Sustainable Energy, p.p.1-4, 2014.

Fangrui Liu, Shanxu Duan, Fei Liu, Bangyin Liu, and Yong Kang, “A Variable Step Size INC MPPT Method for PV Systems” IEEE Transactions On Industrial Electronics,Vol.55, No.7, p.p.2622-2628, July 2008.

Recep Cakmak, Ismail H. Altas, Adel M. Sharaf, “Modeling of FLC-Incremental Based MPPT using DC-DC Boost Converter for Standalone PV System” IEEE Innovations in intelligent system and applications, p.p.1-5, 2012.

Mohammed A. Elgendy, Bashar Zahawi, David J. Atkinson, “Assessment of the Incremental Conductance Maximum Power Point Tracking Algorithm” IEEE Transactions on Sustainable Energy, Vol.4, No.1, Jan.2013.

Nirmal Mukundan C. M. Syed Bilal Qaiser Naqvi;Bhim Singh;P. Jayaprakash “Single-Layer Decoupled Multiple-Order Generalized Integral Control for Single-Stage Solar Energy Grid Integrator With Maximum Power Extraction IEEE Transactions on Industrial Informatics”, Volume: 17, Issue: 1,2021.

Sudip Bhattacharyya;Shailendra Kumar;Bhim Singh,” Adaptive Damped Circular Current Limit Control for PV Grid-Tied System”.IEEE Transactions on Industry Applications, Volume: 56, Issue: 2 ,2020.

Shubhra Shubhra;Bhim Singh,” Three-Phase Grid-Interactive Solar PV-Battery Microgrid Control Based on Normalized Gradient Adaptive Regularization Factor Neural Filter”, IEEE Transactions on Industrial Informatics, Volume: 16, Issue: 4,2020.

Aurobinda Bag;Bidyadhar Subudhi;Pravat Kumar Ray,” A combined reinforcement learning and sliding mode control scheme for grid integration of a PV system”, Volume: 5, Issue: 4,2019.