A Comparative Analysis of MPPT Techniques for Grid Connected PVs


  • F. Z. Kebbab Department of Electrical Engineering, Laboratoire DAC HR, Ferhat Abbas University Setif I, Algeria
  • L. Sabah Department of Electrical Engineering, LAS Laboratory, Ferhat Abbas University Setif I, Algeria
  • H. Nouri Department of Electrical Engineering, LAS Laboratory, Ferhat Abbas University Setif I, Algeria


Maximum Power Point Tracking (MPPT) is essential for the application of a photovoltaic (PV) energy system in order to extract the maximum possible power under variable conditions of irradiation and temperature. This paper deals with the implementation of different MPPT algorithms for a PV array installed for a system connected to the Grid: Perturb and Observe (P&O), Fuzzy Logic Control (FLC), Cuckoo Search (CS), and Beta algorithms were simulated in Matlab/Simulink and the results were analyzed and compared. Beta algorithm proved to have greater tracking power, minor power loss, great tracking speed, less time, and less oscillation than the other techniques.


beta algorithm, cuckoo search, fuzzy logic controller, grid, photovoltaic (PV) generation system, MPPT, P&O, THD


Download data is not yet available.


M. Sarvi and A. Azadian, "A comprehensive review and classified comparison of MPPT algorithms in PV systems," Energy Systems, Nov. 2021. DOI: https://doi.org/10.1007/s12667-021-00427-x

F. K. Abo-Elyousr, A. M. Abdelshafy, and A. Y. Abdelaziz, "MPPT-Based Particle Swarm and Cuckoo Search Algorithms for PV Systems," in Modern Maximum Power Point Tracking Techniques for Photovoltaic Energy Systems, A. M. Eltamaly and A. Y. Abdelaziz, Eds. New York, NY, USA: Springer, 2020, pp. 379–400. DOI: https://doi.org/10.1007/978-3-030-05578-3_14

H. Zong, Y. Cao, and Z. Liu, "Energy security in Group of Seven (G7): a quantitative approach for renewable energy policy," Energy Sources, Part B: Economics, Planning, and Policy, vol. 13, no. 3, pp. 173–175, Nov. 2018. DOI: https://doi.org/10.1080/15567249.2017.1422053

S. D. Al-Majidi, M. F. Abbod, and H. S. Al-Raweshidy, "A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems," International Journal of Hydrogen Energy, vol. 43, no. 31, pp. 14158–14171, May 2018. DOI: https://doi.org/10.1016/j.ijhydene.2018.06.002

B. Sasidhar, T. H. Kumar, and P. U. Kumar, "A Comparative Analysis of Intelligent Techniques to obtain MPPT by Metaheuristic Approach in PV Systems," International Journal for Modern Trends in Science and Technology, vol. 2, no. 10, pp. 16–23, 2016.

N. Aouchiche, M. S. Aitcheikh, M. Becherif, and M. A. Ebrahim, "AI-based global MPPT for partial shaded grid connected PV plant via MFO approach," Solar Energy, vol. 171, pp. 593–603, Jun. 2018. DOI: https://doi.org/10.1016/j.solener.2018.06.109

F.-E. Lamzouri, E.-M. Boufounas, A. Brahmi, and A. E. Amrani, "Optimized TSMC Control Based MPPT for PV System under Variable Atmospheric Conditions Using PSO Algorithm," Procedia Computer Science, vol. 170, pp. 887–892, Jan. 2020. DOI: https://doi.org/10.1016/j.procs.2020.03.116

R. Alik and A. Jusoh, "An enhanced P&O checking algorithm MPPT for high tracking efficiency of partially shaded PV module," Solar Energy, vol. 163, pp. 570–580, Nov. 2018. DOI: https://doi.org/10.1016/j.solener.2017.12.050

M. A. Eltawil and Z. Zhao, "MPPT techniques for photovoltaic applications," Renewable and Sustainable Energy Reviews, vol. 25, pp. 793–813, Jun. 2013. DOI: https://doi.org/10.1016/j.rser.2013.05.022

M. Lasheen, A. K. Abdel Rahman, M. Abdel-Salam, and S. Ookawara, "Adaptive reference voltage-based MPPT technique for PV applications," IET Renewable Power Generation, vol. 11, no. 5, pp. 715–722, 2017. DOI: https://doi.org/10.1049/iet-rpg.2016.0749

S. Veerapen, H. Wen, and Y. Du, "Design of a novel MPPT algorithm based on the two stage searching method for PV systems under partial shading," in IEEE 3rd International Future Energy Electronics Conference and ECCE Asia, Kaohsiung, Taiwan, Jun. 2017, pp. 1494–1498. DOI: https://doi.org/10.1109/IFEEC.2017.7992266

Y.-H. Liu, J.-H. Chen, and J.-W. Huang, "A review of maximum power point tracking techniques for use in partially shaded conditions," Renewable and Sustainable Energy Reviews, vol. 41, pp. 436–453, Jan. 2015. DOI: https://doi.org/10.1016/j.rser.2014.08.038

H. A. Sher, K. E. Addoweesh, and K. Al-Haddad, "An Efficient and Cost-Effective Hybrid MPPT Method for a Photovoltaic Flyback Microinverter," IEEE Transactions on Sustainable Energy, vol. 9, no. 3, pp. 1137–1144, Jul. 2018. DOI: https://doi.org/10.1109/TSTE.2017.2771439

C. Manickam, G. P. Raman, G. R. Raman, S. I. Ganesan, and N. Chilakapati, "Fireworks Enriched P&O Algorithm for GMPPT and Detection of Partial Shading in PV Systems," IEEE Transactions on Power Electronics, vol. 32, no. 6, pp. 4432–4443, Jun. 2017. DOI: https://doi.org/10.1109/TPEL.2016.2604279

M. Abdel-Salam, M.-T. El-Mohandes, and M. Goda, "An improved perturb-and-observe based MPPT method for PV systems under varying irradiation levels," Solar Energy, vol. 171, pp. 547–561, Jun. 2018. DOI: https://doi.org/10.1016/j.solener.2018.06.080

Y. Jung, J. So, G. Yu, and J. Choi, "Improved perturbation and observation method (IP amp;O) of MPPT control for photovoltaic power systems," in Conference Record of the Thirty-first IEEE Photovoltaic Specialists Conference, Lake Buena Vista, FL, USA, Jan. 2005, pp. 1788–1791.

H. Yatimi and E. Aroudam, "Standalone Photovoltaic System with Maximum Power Point Tracking: Modeling and Simulation," International Journal of System Dynamics Applications, vol. 7, no. 3, pp. 94–111, Jul. 2018. DOI: https://doi.org/10.4018/IJSDA.2018070105

S. Farajdadian and S. M. H. Hosseini, "Optimization of fuzzy-based MPPT controller via metaheuristic techniques for stand-alone PV systems," International Journal of Hydrogen Energy, vol. 44, no. 47, pp. 25457–25472, Jul. 2019. DOI: https://doi.org/10.1016/j.ijhydene.2019.08.037

M. Fathi and J. A. Parian, "Intelligent MPPT for photovoltaic panels using a novel fuzzy logic and artificial neural networks based on evolutionary algorithms," Energy Reports, vol. 7, pp. 1338–1348, Aug. 2021. DOI: https://doi.org/10.1016/j.egyr.2021.02.051

M. Mao, L. Cui, Q. Zhang, K. Guo, L. Zhou, and H. Huang, "Classification and summarization of solar photovoltaic MPPT techniques: A review based on traditional and intelligent control strategies," Energy Reports, vol. 6, pp. 1312–1327, Aug. 2020. DOI: https://doi.org/10.1016/j.egyr.2020.05.013

J. Shi, W. Zhang, Y. Zhang, F. Xue, and T. Yang, "MPPT for PV systems based on a dormant PSO algorithm," Electric Power Systems Research, vol. 123, pp. 100–107, Mar. 2015. DOI: https://doi.org/10.1016/j.epsr.2015.02.001

P. S. Gavhane, S. Krishnamurthy, R. Dixit, J. P. Ram, and N. Rajasekar, "EL-PSO based MPPT for Solar PV under Partial Shaded Condition," Energy Procedia, vol. 117, pp. 1047–1053, Mar. 2017. DOI: https://doi.org/10.1016/j.egypro.2017.05.227

K. Ishaque, Z. Salam, M. Amjad, and S. Mekhilef, "An Improved Particle Swarm Optimization (PSO)–Based MPPT for PV With Reduced Steady-State Oscillation," IEEE Transactions on Power Electronics, vol. 27, no. 8, pp. 3627–3638, Dec. 2012. DOI: https://doi.org/10.1109/TPEL.2012.2185713

D. A. Nugraha, K. L. Lian, and Suwarno, "A Novel MPPT Method Based on Cuckoo Search Algorithm and Golden Section Search Algorithm for Partially Shaded PV System," Canadian Journal of Electrical and Computer Engineering, vol. 42, no. 3, pp. 173–182, 2019. DOI: https://doi.org/10.1109/CJECE.2019.2914723

B. S. Goud and G. C. Sekhar, "Cuckoo Search Optimization MPPT Technique for Grid Connected PV System," International Transactions on Electrical Engineering and Computer Science, vol. 1, no. 1, pp. 42–47, Dec. 2020.

X.-S. Yang and S. Deb, "Engineering optimisation by cuckoo search," International Journal of Mathematical Modelling and Numerical Optimisation, vol. 1, no. 4, pp. 330–343, Jan. 2010. DOI: https://doi.org/10.1504/IJMMNO.2010.035430

C. Hussaian Basha, V. Bansal, C. Rani, R. M. Brisilla, and S. Odofin, "Development of Cuckoo Search MPPT Algorithm for Partially Shaded Solar PV SEPIC Converter," in Soft Computing for Problem Solving, K. N. Das, J. C. Bansal, K. Deep, A. K. Nagar, P. Pathipooranam, and R. C. Naidu, Eds. Singapore: Springer, 2020, pp. 727–736. DOI: https://doi.org/10.1007/978-981-15-0035-0_59

X. Li, H. Wen, L. Jiang, E. G. Lim, Y. Du, and C. Zhao, "Photovoltaic Modified β-Parameter-based MPPT Method with Fast Tracking," Journal of Power Electronics, vol. 16, no. 1, pp. 9–17, 2016. DOI: https://doi.org/10.6113/JPE.2016.16.1.9

M. Rosa-Clot, Floating PV Plants. Cambridge, MA, USA: Academic Press, 2020.

M. H. Zafar et al., "Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading," Electronics, vol. 9, no. 11, Nov. 2020, Art. no. 1962. DOI: https://doi.org/10.3390/electronics9111962

M. A. G. de Brito, L. P. Sampaio, L. G. Junior, and C. A. Canesin, "Evaluation of MPPT techniques for photovoltaic applications," in IEEE International Symposium on Industrial Electronics, Gdansk, Poland, Jun. 2011, pp. 1039–1044. DOI: https://doi.org/10.1109/ISIE.2011.5984303

W. Hayder, A. Abid, M. B. Hamed, and L. Sbita, "Improved PSO Algorithms in PV System Optimisation," European Journal of Electrical Engineering and Computer Science, vol. 4, no. 1, pp. 1–6, Jan. 2020. DOI: https://doi.org/10.24018/ejece.2020.4.1.104

S. Saad, "Enhancement of Solar Cell Modeling with MPPT Command Practice with an Electronic Edge Filter," Engineering, Technology & Applied Science Research, vol. 11, no. 4, pp. 7501–7507, Aug. 2021. DOI: https://doi.org/10.48084/etasr.4304

T. S. Tran, D. T. Nguyen, and G. Fujita, "Islanding Detection Method Based on Injecting Perturbation Signal and Rate of Change of Output Power in DC Grid-Connected Photovoltaic System," Energies, vol. 11, no. 5, May 2018, Art. no. 1313. DOI: https://doi.org/10.3390/en11051313

A. G. Abdullah, M. Sh. Aziz, and B. A. Hamad, "Comparison between neural network and P&O method in optimizing MPPT control for photovoltaic cell," International Journal of Electrical and Computer Engineering, vol. 10, no. 5, pp. 5083–5092, 2020. DOI: https://doi.org/10.11591/ijece.v10i5.pp5083-5092

S. Salman, X. AI, and Z. WU, "Design of a P-&-O algorithm based MPPT charge controller for a stand-alone 200W PV system," Protection and Control of Modern Power Systems, vol. 3, no. 1, May 2018, Art. no. 25. DOI: https://doi.org/10.1186/s41601-018-0099-8

T. O. Sweidan, M. S. Widyan, and M. B. Rifai, "Perturbation and observation as MPPT for highly penetrated grid-integrated PV generator considering symmetrical three-phase fault," International Journal of Power and Energy Conversion, vol. 10, no. 2, pp. 225–240, Jan. 2019. DOI: https://doi.org/10.1504/IJPEC.2019.10018718

X.-S. Yang and S. Deb, "Cuckoo Search via Levy flights," in World Congress on Nature & Biologically Inspired Computing, Coimbatore, India, Dec. 2009, pp. 210–214. DOI: https://doi.org/10.1109/NABIC.2009.5393690

R. Anand, D. Swaroop, and B. Kumar, "Global Maximum Power Point Tracking for PV Array under Partial Shading using Cuckoo Search," in IEEE 9th Power India International Conference, Sonepat, India, Mar. 2020, pp. 1–6. DOI: https://doi.org/10.1109/PIICON49524.2020.9113004

C. Hussaian Basha, C. Rani, R. M. Brisilla, and S. Odofin, "Simulation of Metaheuristic Intelligence MPPT Techniques for Solar PV Under Partial Shading Condition," in Soft Computing for Problem Solving, K. N. Das, J. C. Bansal, K. Deep, A. K. Nagar, P. Pathipooranam, and R. C. Naidu, Eds. New York, NY, USA: Springer, 2020, pp. 773–785. DOI: https://doi.org/10.1007/978-981-15-0035-0_63

M. Y. Allani, D. Mezghani, F. Tadeo, and A. Mami, "FPGA Implementation of a Robust MPPT of a Photovoltaic System Using a Fuzzy Logic Controller Based on Incremental and Conductance Algorithm," Engineering, Technology & Applied Science Research, vol. 9, no. 4, pp. 4322–4328, Aug. 2019. DOI: https://doi.org/10.48084/etasr.2771

U. Yilmaz, A. Kircay, and S. Borekci, "PV system fuzzy logic MPPT method and PI control as a charge controller," Renewable and Sustainable Energy Reviews, vol. 81, pp. 994–1001, Jan. 2018. DOI: https://doi.org/10.1016/j.rser.2017.08.048

Z. B. Duranay, H. Guldemir, and S. Tuncer, "Fuzzy Sliding Mode Control of DC-DC Boost Converter," Engineering, Technology & Applied Science Research, vol. 8, no. 3, pp. 3054–3059, Jun. 2018. DOI: https://doi.org/10.48084/etasr.2116

S. Jain and V. Agarwal, "A new algorithm for rapid tracking of approximate maximum power point in photovoltaic systems," IEEE Power Electronics Letters, vol. 2, no. 1, pp. 16–19, Mar. 2004. DOI: https://doi.org/10.1109/LPEL.2004.828444

X. Li, H. Wen, Y. Hu, Y. Du, and Y. Yang, "A Comparative Study on Photovoltaic MPPT Algorithms Under EN50530 Dynamic Test Procedure," IEEE Transactions on Power Electronics, vol. 36, no. 4, pp. 4153–4168, Apr. 2021. DOI: https://doi.org/10.1109/TPEL.2020.3024211

X. Li, H. Wen, and C. Zhao, "Improved beta parameter based MPPT method in photovoltaic system," in 9th International Conference on Power Electronics and ECCE Asia, Seoul, Korea (South), Jun. 2015, pp. 1405–1412. DOI: https://doi.org/10.1109/ICPE.2015.7167963

M. V. da Rocha, L. P. Sampaio, and S. A. O. da Silva, "Comparative analysis of MPPT algorithms based on Bat algorithm for PV systems under partial shading condition," Sustainable Energy Technologies and Assessments, vol. 40, May 2020, Art. no. 100761. DOI: https://doi.org/10.1016/j.seta.2020.100761

S. Kumar, C. Sethuraman, and G. Chandru, "Design of Control Unit for Off-grid and Grid Connected Solar- Wind Hybrid System Suitable for Supplying Power to both AC and DC Loads," in International Conference on Recent Trends on Electronics, Information, Communication & Technology, Bangalore, India, Aug. 2021, pp. 331–338. DOI: https://doi.org/10.1109/RTEICT52294.2021.9573541


How to Cite

F. Z. Kebbab, L. Sabah, and H. Nouri, “A Comparative Analysis of MPPT Techniques for Grid Connected PVs”, Eng. Technol. Appl. Sci. Res., vol. 12, no. 2, pp. 8228–8235, Apr. 2022.


Abstract Views: 1513
PDF Downloads: 837

Metrics Information

Most read articles by the same author(s)