A Study on An MPPT Control Approach Using Artificial Intelligence and the Perturb and Observe Method

Saif Talal Bahar; Yasir G. Rashid

doi:10.24237/djes.2024.17210

Authors

Saif Talal Bahar
saif.talal@mtu.edu.iq
Department of Electrical Techniques, Baquba Technical Institute, Middle Technical University, Baghdad, Iraq
Yasir G. Rashid Department of Electrical Power and Machines, Collage of Engineering, University of Diyala, Diyala, Iraq

Keywords:

Photovoltaic Cells, Fuzzy Control, Maximum Power Point Tracking, Artificial intelligence, Renewable energy

Abstract

A maximum power point tracking (MPPT) control procedure constructed based on the Artificial intelligence optimization algorithm is proposed. A mathematical model of photovoltaic cells was established under varying light intensity and ambient temperature. Maximal power tracking control for iterative search using an artificial intelligence (AI) optimization technique Excellent, the artificial intelligence-based MPPT algorithm's principle is presented. Simulation results it shows that the artificial intelligence algorithm can faster and exactly track the maximum power point and remains stable, and compared to Perturb and Observe algorithm under dynamic shadow conditions and artificial intelligence MPPT control method, which has higher tracking accuracy and faster convergence speed. Faster and smaller oscillation amplitude, which is the best response to sunlight conditions for photovoltaic maximum power point tracking technology Flexibility. Using Matlab/Simulink software to build a simulation model of an independent photovoltaic system. It controls variables by keeping the temperature continuous and changes the light intensity to simulate different lighting environments. The identical comparison was conducted between all based MPPT methods such as the fuzzy control approach, demonstrating that the fuzzy control based technique exhibits higher results in terms of efficiency.

Downloads

Download data is not yet available.

References

Yu, Ting-Chung, and Tang-Shiuan Chien. “Analysis and simulation of characteristics and maximum power point tracking for photovoltaic systems,” In 2009 International Conference on Power Electronics and Drive Systems (PEDS), pp. 1339-1344. IEEE, 2009.

Gohar Ali, Hina, Ramon Vilanova Arbos, Jorge Herrera, Andrés Tobón, and Julián Peláez-Restrepo, “Non-linear sliding mode controller for photovoltaic panels with maximum power point tracking,” Processes, vol. 8, no. 1: pp.108.‏ 2020.

Seddik, M., S. Zouggar, T. Ouchbel, M. Oukili, A. Rabhi, A. Aziz, and M. L. Elhafyani, “A stand-alone system energy hybrid combining wind and photovoltaic with voltage control feedback loop voltage,” International Journal of Electrical Engineering IJEET, vol.6, no.2. pp. 9-13, 2010.

H. Wang and J. Shen, “Analysis of the Characteristics of Solar Cell Array Based on MATLAB/Simulink in Solar Unmanned Aerial Vehicle,” IEEE Access, vol. 6, pp. 21195-21201, 2018.

Ishaque, Kashif, and Zainal Salam. “A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition,” Renewable and Sustainable Energy Reviews 19, pp.475-488, 2013

M. Ahmed, I. Harbi, R. Kennel, M. L. Heldwein, J. Rodríguez, and M. Abdelrahem, “Performance Evaluation of PV ModelBased Maximum Power Point Tracking Techniques,” Electronics, vol. 11, no. 16, p. 2563, Aug. 2022.

YUN, Eun Jeong; PARK, Jong Tae; YU, Chong Gun. “An maximum power point tracking interface circuit for low-voltage DC-type energy harvesting sources,” Bulletin of Electrical Engineering and Informatics, , vol.11, no. 6, pp. 3108-3118, 2022

J. H. Kumar, S. B. Ch, and J. Yugandhar, “Design and Investigation of Short Circuit Current Based Maximum Power Point Tracking for Photovoltaic System,” Science Academy Publisher International Journal of Research and Reviews in Electrical and Computer Engineering, vol. 1, no. 2, pp. 2046–5149, Jul. 2011.

K. Ullah, Y. Wang, A. Zaman, H. Imtiaz, S. Ahmad, and B. Kumar, “Maximum Power Point Technique (MPPT) for PV System Based on Improved Pert and Observe (P&O) Method with PI Controller,” International Research Journal of Engineering and Technology (IRJET), vol. 6, no. 12, pp. 813–819, Dec. 2019.

C. R. Algarín, J. T. Giraldo and O. R. Álvarez, “Fuzzy Logic Based MPPT Controller for a PV System,” Energies, vol. 10, no. 12, p. 2036, Dec. 2017.

O. Boutebba, S. Semcheddine, F. Krim and B. Talbi, “Design of a Backstepping-Controlled Boost Converter for MPPT in PV Chains,” International Conference on Advanced Electrical Engineering (ICAEE), Algiers, Algeria, pp. 1-7, 2019.

T. Zhu, J. Dong, X. Li, and S. Ding, “A Comprehensive Study on Maximum Power Point Tracking Techniques Based on Fuzzy Logic Control for Solar Photovoltaic Systems,” Frontiers in Energy Research, vol. 9, Jul. 2021.

D. -E. Jeong, J. -S. Ko, J. -G. Lee and D. -H. Chung, "MPPT control of photovoltaic system using optimization voltage with temperature,” 12th International Conference on Control, Automation and Systems, Jeju, Korea (South), pp. 1139-1143, 2012.

K. P. Panda, P. R. Bana and G. Panda, “A Self-Balanced Switched-Capacitor Boost Seven-Level Inverter for Photovoltaic Systems,” IEEE International Conference on Computing, Power and Communication Technologies (GUCON), Greater Noida, India, pp. 338-343, 2020

Selvakumar, Sankar, Mohanty Madhusmita, Chandrasekaran Koodalsamy, Sishaj Pulikottil Simon, and Yog Raj Sood, “High-speed maximum power point tracking module for PV systems,” IEEE Transactions on Industrial Electronics, vol.66, no.2, pp. 1119-1129, 2018.

BENKERCHA, Rabah; MOULAHOUM, Samir; COLAK, Ilhami, “Modelling of fuzzy logic controller of a maximum power point tracker based on artificial neural network,” In: 16th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, pp. 485-492, 2017

Brahim, Ayeb, Youcef Soufi, Djamel Ounnas, and Dhaouadi Guiza,“Stand-alone photovoltaic system control based on Artificial neural network and fuzzy logic,” 5th International Conference on Power Electronics and their Applications (ICPEA). IEEE, pp. 1-6,‏ 2022.

UNO, Masatoshi; SUGIYAMA, Kazuki, “PWM-and PFM-controlled switched capacitor converter-based multiport converter integrating voltage equalizer for photovoltaic systems,” IEEE 3rd International Future Energy Electronics Conference and ECCE Asia (IFEEC 2017-ECCE Asia). IEEE, 2017. pp. 1499-1504, 2017.

Muhammad Yaqoob Javed, Muhammad Majid Gulzar, Syed Tahir Hussain Rizvi, Arslan Arif. “A Hybrid Technique to Harvest Maximum Power from PV Systems under Partial Shading Conditions", IEEE International Conference on Emerging Technologies (ICET), Islamabad, Pakistan, pp 1-5, October 2016.

I. K. Abdul-Razzaq, M. M. F. Sakr, and Y. G. Rashid, “Comparison of PV Panels MPPT Techniques Applied to Solar Water Pumping System,” International Journal of Power Electronics and Drive System, vol. 12, no. 3, pp. 1813-1822, September 2021.

S. Talal Bahar and D. Rahman Neama, “Improved Direct Torque Control Utilizing Model Predictive Control Approach for Permanent Magnet Synchronous Motor”, IJSER, vol. 3, no. 2, pp. 57–64, Jun. 2024.

R. Abid, S. Mahjoub, F. Masmoudi and N. Derbel, “MPPT Control Strategies for Photovoltaic Applications: Algorithms and Comparative Analysis,” 2019 16th International Multi-Conference on Systems, Signals & Devices (SSD), Istanbul, Turkey, 2019, pp. 566-572,

N. Hashmi and S. A. Khan, “Power Energy Management for a Grid-Connected PV System Using Rule-Base Fuzzy Logic,” 2015 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS), Kota Kinabalu, Malaysia, 2015, pp. 31-36,‏

V. Rajagopal, D. Sharath, G. Vishwas, J. Bangarraju, S. R. Arya and C. Venkatesh, “Optimized Controller Gains Using Grey Wolf Algorithm for Grid Tied Solar Power Generation with Improved Dynamics and Power Quality,” in Chinese Journal of Electrical Engineering, vol. 8, no. 2, pp. 75-85, June 2022,

S. Prajapati and E. Fernandez, “Performance Evaluation of Membership Function on Fuzzy Logic Model for Solar PV array,” IEEE International Conference on Computing, Power and Communication Technologies (GUCON), Greater Noida, India, 2020, pp. 609-613,

Mohamed Lasheen, Ali Kamel Abdel Rahman, Mazen Abdel-Salam, et al. “Adaptive reference voltage-based MPPT technique for PV applications,” IET Renewable Power Generation, 2017, 11(5):715-722.

R. Chilipi, N. Al Sayari and J. Y. Alsawalhi, "Control of Single-Phase Solar Power Generation System With Universal Active Power Filter Capabilities Using Least Mean Mixed-Norm (LMMN)-Based Adaptive Filtering Method," in IEEE Transactions on Sustainable Energy, vol. 11, no. 2, pp. 879-893, April 2020,

Y. Eto, Y. Noge and M. Shoyama, “A Control System of PV Sources for DC Microgrid with Seamless Switching Operation between I-V Droop Control and MPPT Control,” 2022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia), Himeji, Japan, 2022, pp. 1547-1552,

X. Guo, W. -P. Li, Y. Pan and J. Liu, "A Novel Power Switching Control Method of the Wind Power MPPT System Based on the Switching System Theory,” 2022 International Electronics Symposium (IES), Surabaya, Indonesia, 2022, pp. 79-84,

H. H. Khalaf, A. T. Mohammad, A. N. Hussain and Z. S. Al-Sagar, “Comparison and Assessment of PV Module Power Prediction Based on ANN for Iraq Weather,” 4th International Conference on Advanced Science and Engineering (ICOASE), Zakho, Iraq, pp. 154-159, 2022.

S. Kambale and V. Bhole, “Enhanced Voltage Regulation in Solar PV Systems using ANN-based MPPT control for DC-DC Converter,” 3rd Asian Conference on Innovation in Technology (ASIANCON), Ravet IN, India, pp. 1-5, 2023.

R. Bhattacharjee, A. Deb and N. Adhikary, "A Comparative Performance Analysis of P&O and ANN Algorithm Based MPPT Energy Harvesting in PV Systems,” 2023 7th International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS), Bangalore, India, pp. 1-6, 2023.

S. Kumar Roy, S. Hussain and M. A. Bazaz, "Implementation of MPPT technique for solar PV system using ANN,” 2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE), Noida, India, pp. 338-342,2017.