Modified Perturb and Observe Approach in MPPT for a Standalone Photovoltaic System
DOI:
https://doi.org/10.18196/jet.v6i2.18354Keywords:
MPPT, Perturb and Observe, Solar Photovoltaic, OptimizationAbstract
This paper proposes a modified perturb and observe algorithm approach to increase the output power of an independent photovoltaic system. Today, photovoltaic application as renewable energy power plant has been prevalent. This popularity is because photovoltaic power plants are easy to apply on-grid and off-grid schemes. In standalone power generation applications, the increased photovoltaic output power is of great help to users as it contributes to increasing overall system efficiency. The perturb and observe algorithm has been known as a reliable and inexpensive method. However, the performance still needs to be improved. Therefore, this study proposes a modified perturb and observe algorithm approach. The research results show the superiority of the proposed method.References
K. Pal, S. Kumar, B. Singh, and T.C. Kandpal, “Implementation of frequency integrated multi-order generalized integrator for solar energy sourced grid,” International Journal of Electrical Power & Energy Systems, vol. 131, October 2021, p. 106918.
A. Raj, S. R. Arya, and J. Gupta, “Solar PV array-based DC–DC converter with MPPT for low power applications,” Renew. Energy Focus, vol. 34, September 2020, pp. 109–119.
R.B. Ballipo, S. Mikkili, and P.K. Bonthagorla, “Hybrid, Optimal, Intelligent and Classical PV MPPT Techniques: A Review,” CSEE Journal of Power and Energy Systems, vol. 7, no. 1, January 2021.
A. Jouda, F. Elyes, A. Rabhi, and M. Abdelkader, “Optimization of Scaling Factors of Fuzzy-MPPT Controller for Stand-alone Photovoltaic System by Particle Swarm Optimization,” Energy Procedia, vol. 111, September 2016, pp. 954–963.
R.A. Alhasibi, S.P. Hadi, and Sarjiya, “The Integration of Renewable-Distributed Energy Resources into Electrical Power System Expansion with Intermittency Consideration,” IREMOS, vol. 14, no. 2, 2021, pp. 89-100.
R. Syahputra and I. Soesanti, "Performance Improvement for Small-Scale Wind Turbine System Based on Maximum Power Point Tracking Control," Energies, 12 (20), 2019, p. 3938.
R. Singh, S.M. Amrr, and M.S.J. Asghar, “Supervisory control strategy for the effective solar energy utilization in a residential microgrid system using a cost-effective controller,” International Journal of Electrical Power & Energy Systems, vol. 132, November 2021, p. 107170.
A. Arther Jain, B. J. Rabi, and S. S. Darly, “Application of QOCGWO-RFA for maximum power point tracking (MPPT) and power flow management of solar PV generation system,” Int. J. Hydrogen Energy, vol. 45, no. 7, pp. 4122–4136, 2020,
H. Tao, M. Ghahremani, F. W. Ahmed, W. Jing, M. S. Nazir, and K. Ohshima, “A novel MPPT controller in PV systems with hybrid whale optimization-PS algorithm based ANFIS under different conditions,” Control Eng. Pract., vol. 112, February 2021, doi: 10.1016/j.conengprac.2021.104809.
A.F.C. Borray, A. Garces, J. Merino, E. Torres, and J. Mazon, “New energy bound-based model for optimal charging of electric vehicles with solar photovoltaic considering low-voltage network's constraints,” International Journal of Electrical Power & Energy Systems, vol. 129, July 2021, p. 106862.
S.D. Al-Majidiab, M.F. Abboda, and H.S. Al-Raweshidya, "A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems," International Journal of Hydrogen Energy, vol. 43, no. 31, 2018, pp. 14158-14171.
B. Laxman, A. Annamraju, and N. V. Srikanth, “A grey wolf optimized fuzzy logic based MPPT for shaded solar photovoltaic systems in microgrids,” Int. J. Hydrogen Energy, vol. 46, no. 18, pp. 10653–10665, 2021.
Q. Zhao and C. Li, "Two-Stage Multi-Swarm Particle Swarm Optimizer for Unconstrained and Constrained Global Optimization", IEEE Access, vol. 8, 2020, pp. 124905 - 124927.
X. Ge, F. W. Ahmed, A. Rezvani, N. Aljojo, S. Samad, and L. K. Foong, “Implementation of a novel hybrid BAT-Fuzzy controller based MPPT for grid-connected PV-battery system,” Control Eng. Pract., vol. 98, March 2020.
M. O. Okwu and L. K. Tartibu, “Particle Swarm Optimisation,” Stud. Comput. Intell., vol. 927, pp. 5–13, 2021.
M. Jiang, M. Ghahremani, S. Dadfar, H. Chi, and Y.N. Abdallah, “A novel combinatorial hybrid SFL–PS algorithm based neural network with perturb and observe for the MPPT controller of a hybrid PV-storage system,” Control Engineering Practice, vol. 114, 2021, p. 104880.
Y. Singh and N. Pal, “Reinforcement learning with fuzzified reward approach for MPPT control of PV systems,” Sustainable Energy Technologies and Assessments, vol. 48, October 2021, p. 101665.
A. Ali, K. Almutairi, S. Padmanaban, V. Tirth, S. Algarni, K. Irshad, S. Islam, M.H. Zahir, M. Shafiullah, and M.Z. Malik, “Investigation of MPPT Techniques Under Uniform and Non-Uniform Solar Irradiation Condition–A Retrospection,” IEEE Access, vol. 8, 2020.
N. Shankar and N. SaravanaKumar, “Reduced Partial shading effect in Multiple PV Array configuration model using MPPT based Enhanced Particle Swarm Optimization Technique,” Microprocess and Microsystem, vol. 2020, p. 103287.
Y. Soufi, M. Bechouat, and S. Kahla, “Fuzzy-PSO controller design for maximum power point tracking in photovoltaic system,” Int. J. Hydrogen Energy, vol. 42, no. 13, pp. 8680–8688, 2017.
Y. Shi, Y. Sun, J. Liu, and X. Du, “Model and stability analysis of grid-connected PV system considering the variation of solar irradiance and cell temperature,” International Journal of Electrical Power & Energy Systems, vol. 132, November 2021, p. 107155.
V. Q. B. Ngo, M. Latifi, R. Abbassi, H. Jerbi, K. Ohshima, and M. khaksar, “Improved krill herd algorithm based sliding mode MPPT controller for variable step size P&O method in PV system under simultaneous change of irradiance and temperature,” J. Franklin Inst., vol. 358, pp. 3491–3511, 2021.
M. Rastogi, A. Ahmad, and A. H. Bhat, “Performance investigation of two-level reduced-switch D-STATCOM in grid-tied solar-PV array with stepped P&O MPPT algorithm and modified SRF strategy,” Journal of King Saud University - Engineering Sciences., vol. 2021.
M. Jiang, M. Ghahremani, S. Dadfar, H. Chi, Y. N. Abdallah, and N. Furukawa, “A novel combinatorial hybrid SFL–PS algorithm based neural network with perturb and observe for the MPPT controller of a hybrid PV-storage system,” Control Eng. Pract., vol. 114, June 2021.
M. Mohammadinodoushan, R. Abbassi, H. Jerbi, F.W. Ahmed, H.A.K. Ahmed, and A. Rezvani, “A new MPPT design using variable step size perturb and observe method for PV system under partially shaded conditions by modified shuffled frog leaping algorithm- SMC controller,” Sustainable Energy Technologies and Assessments, vol. 45, 2021, p. 101056.
https://www.pveducation.org/pvcdrom/solar-cell-operation/iv-curve.
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