A variable maximum power tracking method based on fuzzy logic for solar systems

Document Type : Original Article

Author

abru

Abstract

Due to the change in the output characteristic of photovoltaic units under changes in radiation, temperature, load size and also the angle of placement of the panels, these systems rarely automatically turn on around the maximum power point. So far, various methods such as increasing conductivity, parasitic capacitor, neural network and fuzzy logic controller have been presented to track the maximum power point of photovoltaic systems, which have disadvantages such as high cost, high complexity. And they have low reliability. In this article, a fuzzy controller is designed to track the maximum power point so that the maximum power point tracking can be extracted under the conditions of changing temperature and radiation. In order to increase the accuracy of the proposed controller and considering the nature of temperature and radiation changes, the gray wolf optimization algorithm has been used to adjust the limits of the fuzzy functions to obtain a robust controller, and a proportional integral controller has also been used on the load side Its parameters are also calculated by GWO algorithm to set the optimal voltage. In order to validate the proposed mechanism, this structure has been implemented in the Simulink environment of MATLAB software, and the results show the optimal efficiency of the optimized fuzzy controller in tracking the maximum power point of photovoltaic sources.

Keywords

Main Subjects

References

[1] M. N. I. Jamaludin, M. F. N. bin Tajuddin, J. Ahmed and T. Sengodan, ”Hybrid Bio-Intelligence Salp Swarm Algorithm for Maximum Power Point Tracking (MPPT) of Photovoltaic Systems Under Gradual Change in Irradiance Conditions,” 2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT), Erode, India, 2021, pp. 1-7.
 
[2] H. Saber, A. E. Bendaouad, L. Rahmani and H. Radjeai, ”A comparative study of the FLC, INC and P&O methods of the MPPT algorithm for a PV system,” 2022 19th International Multi-Conference on Systems, Signals & Devices (SSD), Sétif, Algeria, pp. 2010-2015,2022.
 
[3] J. -Z. Yan, W. -H. Pan, H. -H. Wu, T. Hsu and C. -L. Wei, ”Photovoltaic Energy Harvesting Chip With P&O Maximum Power Point Tracking Circuit and Novel Pulse-Based Multiplier,” in IEEE Transactions on Power Electronics, vol. 36, no. 11, pp. 12867-12876, Nov. 2021, doi: 10.1109/TPEL.2021.
 
[4] B.N. Alajmi, K.H. Ahmed, S. J. Finney, and B.W. Williams, ”Fuzzy-Logic-Control Approach of a Modified Hill-Climbing Method for Maximum Power Point in Microgrid Standalone Photovoltaic System,” IEEE Transactions on Power Electronics, Vol. 26, No. 4, pp. 1022-1030, April 2011.
 
[5] L. H. Pratomo, ”Performance Analysis of Parallel PV Modules Using an MPPT Charge Controller,” 2021 International Seminar on Application for Technology of Information and Communication (iSemantic), Semarangin, Indonesia, pp. 167-172,2021.
 
[6] M. W. Rahman, C. Bathina, V. Karthikeyan, and R. Prasanth, “Comparative analysis of developed incremental conductance (IC) and perturb & observe (P&O) MPPT algorithm for photovoltaic applications,” in 2016 10th International Conference on Intelligent Systems and Control (ISCO), pp. 1–6, Coimbatore, India, 2020.
 
[7] M. K. Gawande, S. G. Ghulaxe, T. R. Mahatme, A. S. Salvi and M. D. Bagewadi, ”Modern approach for hybridization of PSO-INC MPPT methods for efficient solar power tracking,” 2021 2nd Global Conference for Advancement in Technology (GCAT), Bangalore, India, 2021.
 
[8] S. Paul, ”Comparison of MPPT using GA-Optimized ANN employing PI controller with GAOptimized ANN employing fuzzy controller for PV system,” IET Chennai Fourth International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2013), Chennai, 2013, pp. 266-271.
 
[9] H. Iles and Y. Mahmoud, ”Improved MPPT Algorithm for Differential Power Processing PV Converters,” IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, Brussels, Belgium, 2022, pp. 1-5.
 
[10] H. W. Salih, S. Wang and B. S. Farhan, ”A novel GA-PI optimized controller for MPPT based PV in a hybrid PV-diesel power system,” 2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), Changsha, China, 2015, pp. 1288-1293.
 
[11] L. B. Prasad, S. Sahu, M. Gupta, R. Srivastava, L. Mozhui and D. N. Asthana, ”An improved method for MPPT using ANN and GA with maximum power comparison through Perturb & Observe technique,” 2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering (UPCON), Varanasi, India, 2016, pp. 206-211.
 
[12] A. Khalilnejad, A. Sundararajan and A. I. Sarwat, ”Optimal design of hybrid wind/photovoltaic electrolyzer for maximum hydrogen production using imperialist competitive algorithm,” in Journal of Modern Power Systems and Clean Energy, vol. 6, no. 1, pp. 40-49, January 2018.
 
[13] S. R. Kiran, C. H. H. Basha, V. P. Singh, C. Dhanamjayulu, B. R. Prusty and B. Khan, ”Reduced Simulative Performance Analysis of Variable Step Size ANN Based MPPT Techniques for Partially Shaded Solar PV Systems,” in IEEE Access, vol. 10, pp. 48875-48889, 2022.
 
[14] M. Ali et al., ”Robust ANN-Based Control of Modified PUC-5 Inverter for Solar PV Applications,” in IEEE Transactions on Industry Applications, vol. 57, no. 4, pp. 3863-3876, July-Aug. 2021.
 
[15] M. N. Ali, K. Mahmoud, M. Lehtonen and M. M. F. Darwish, ”An Efficient Fuzzy-Logic Based Variable-Step Incremental Conductance MPPT Method for Grid-Connected PV Systems,” in IEEE Access, vol. 9, pp. 26420-26430, 2021.
 
[16] F. -J. Lin, K. -C. Lu, T. -H. Ke, B. -H. Yang and Y. -R. Chang, ”Reactive Power Control of ThreePhase Grid-Connected PV System During Grid Faults Using Takagi–Sugeno–Kang Probabilistic Fuzzy Neural Network Control,” in IEEE Transactions on Industrial Electronics, vol. 62, no. 9, pp. 5516-5528, Sept. 2015.
 
[17] N. Benbaha, F. Zidani, M. S. N. Said, S. e. Boukebbous and H. Ammar, ”Optimal energy control of induction motor standalone photovoltaic-battery pumping system,” 2017 6th International Conference on Systems and Control (ICSC), Batna, Algeria,pp. 622-628, 2017.
 
[18] R. Muniraj, M. Ulaganathan, J. T, B. Deepanraj and S. C, ”Design and Evaluation of MPPT Based Two Stage Battery Charging Scheme For A Solar PV Lighting System,” 2022 International Conference on Innovations in Science and Technology for Sustainable Development (ICISTSD), Kollam, India, pp. 375-380,2022.
 
[19] H. Xu, X. Wang, L. Huang, J. Qian and J. Lou, ”Research on Two-Stage Three-Phase Photovoltaic Grid-Connected System with MPPT,” 2019 4th International Conference on Power and Renewable Energy (ICPRE), Chengdu, China, 2019.
 
[20] J. Chang, W. Chang, and S. Chung, ”Single-phase grid-connected PV system using three-arm rectifier-inverter,” IEEE transactions on aerospace and electronic systems, vol. 42, pp. 211-219, 2006.
 
[21] B. Babes, F. Albalawi, N. Hamouda, S. Kahla and S. S. M. Ghoneim, ”Fractional-Fuzzy PID Control Approach of Photovoltaic-Wire Feeder System (PV-WFS): Simulation and HIL-Based Experimental Investigation,” in IEEE Access, vol. 9, pp. 159933-159954, 2021.
 
[22] W. Swiegers and J. H. Enslin, ”An integrated maximum power point tracker for photovoltaic panels,” in Industrial Electronics, 1998. Proceedings. ISIE’98. IEEE International Symposium on, 1998, pp. 40-44.
 
[23] N. Mahmud, A. Zahedi and A. Mahmud, ”A Cooperative Operation of Novel PV Inverter Control Scheme and Storage Energy Management System Based on ANFIS for Voltage Regulation of GridTied PV System,” in IEEE Transactions on Industrial Informatics, vol. 13, no. 5, pp. 2657-2668, Oct. 2017.
 
[24] Y.-T. Chen, Y.-C. Jhang, and R.-H. Liang, ”A fuzzy-logic based auto-scaling variable step-size MPPT method for PV systems,” Solar Energy, vol. 126, pp. 53-63, 2016.
 
[25] S. Azali and M. Sheikhan, ”Intelligent control of photovoltaic system using BPSO-GSA-optimized neural network and fuzzy-based PID for maximum power point tracking,” Applied Intelligence, vol. 44, pp. 88-110, 2016.
 
[26] O. Abdalla, H. Rezk, E.M. Ahmed, Wind driven optimization algorithm based global MPPT for PV system under non-uniform solar irradiance. Sol. Energy, 180, pp. 429-444,2019.
 
[27] M. Abdel-Salam, M.-T. El-Mohandes, M. Goda. An improved perturb-and-observe based MPPT method for PV systems under varying irradiation levels, Sol. Energy, 171, pp. 547-561,2018.
 
[28] T.Noguchi S.Togashi. ”Short-current pulsebased adaptive maximum-power-point tracking for a photovoltaic power generation system”, Electrical Engineering in Japan, Vol. 139, pp. 65-72, 2002.
 
[29] Ahmad, J,”A fractional open circuit voltage based maximum power point tracker for photovoltaic arrays”. IEEE International Conference on Software Technology and Engineering”, pp. 247–250, 2010.
 
[30] Saremi S, Mirjalili SZ, Mirjalili SM, Evolutionary population dynamics and grey wolf optimizer. Neural Comput Appl 26(5):1257–1263,2015.
Fuzzy Systems and its Applications
Volume 6, Issue 1 - Serial Number 12
September 2023
Pages 151-174

Files

History

  • Receive Date: 09 February 2023
  • Revise Date: 11 April 2023
  • Accept Date: 26 May 2023

Share

How to cite

Statistics