DOI: https://doi.org/10.14710/transmisi.27.4.%25p

MPPT Control Algorithm Based on Optimization of Solar System under Partial Shading Condition (PSC)

*Anak Agung Istri Pandawani  -  Magister Teknik Elektro, Universitas Udayana, Jalan P.B. Sudirman, Denpasar, Bali, Indonesia, Indonesia
Dikirim: 27 Peb 2025; Diterbitkan: 6 Okt 2025.
Akses Terbuka Copyright (c) 2025 Transmisi: Jurnal Ilmiah Teknik Elektro under http://creativecommons.org/licenses/by-sa/4.0.

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The photovoltaic system has an intermittent nature because it depends on dynamic environmental conditions, therefore a method is developed to track the maximum power so that in varying environmental conditions photovoltaic system can maximize its production. The method is the process of identifying the maximum power point through tracking which can be done with various algorithms known as the MPPT method. MPPT faces challenges during dynamic environmental conditions such as when Partial Shading Condition (PSC) occurs where solar panels receive uneven irradiation which can cause power losses and affect the performance of solar panels. During PSC conditions, not all MPPT algorithms have the ability to find the accurate maximum point so that optimization-based algorithms are used to track the maximum power point accurately and in a short time. This paper provides a comprehensive review of several optimization-based MPPT algorithms by highlighting the capabilities of each method in terms of speed, stability and efficiency under PSC conditions.

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Kata Kunci: MPPT, PSC, Photovoltaic, Optimization

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Bagian: Artikel - Teknik Tenaga Listrik
Bahasa : EN
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  1. International Energy Agency Photovoltaic Power Systems Technology Collaboration Programme, “PHOTOVOLTAIC POWER SYSTEMS PROGRAMME ANNUAL REPORT 2019,” 2019
  2. H.-D. Liu, C.-H. Lin, and S.-D. Lu, “A novel MPPT algorithm considering solar photovoltaic modules and load characteristics for a single stage standalone solar photovoltaic system,” IEICE Electronics Express, vol. xx, No.xx, pp. 1–6, 2020, doi: 10.1587/elex.XX.XXXXXXXX
  3. M. H. Albadi, “Solar PV power intermittency and its impacts on power systems - An overview,” Journal of Engineering Research, vol. 16, no. 2, pp. 142–150, 2019, doi: 10.24200/tjer.vol16iss2pp142-150
  4. I. D. G. Jayawardana, C. N. M. Ho, M. Pokharel, and G. E. Valderrama, “A Fast-Dynamic Control Scheme for a Power-Electronics-Based PV Emulator,” IEEE J Photovolt, vol. 11, no. 2, pp. 485–495, Mar. 2021, doi: 10.1109/JPHOTOV.2020.3041188
  5. B. Azmi, J. H. Abner, P. E. B, and H. Seputra, “REVIEW PERBANDINGAN TEKNIK MAXIMUM POWER POINT TRACKER (MPPT) UNTUK SISTEM PENGISIAN DAYA MENGGUNAKAN SEL SURYA (REVIEW COMPARISON MAXIMUM POWER POINT TRACKER (MPPT) TECHNIQUE FOR CHARGING SYSTEMS USING SOLAR CELLS),” Jurnal Teknologi Dirgantara, vol. 16, pp. 111–122, 2019
  6. B. Ji et al., “A Novel Particle Jump Particle Swarm Optimization Method for PV MPPT Control under Partial Shading Conditions,” IEEJ Journal of Industry Applications, vol. 9, no. 4, pp. 435–443, Jul. 2020, doi: 10.1541/ieejjia.9.435
  7. J. Dadkhah and M. Niroomand, “Optimization Methods of MPPT Parameters for PV Systems: Review,
  8. Classification, and Comparison,” Mar. 01, 2021, State Grid Electric Power Research Institute. doi: 10.35833/MPCE.2019.000379
  9. M. L. Katche, A. B. Makokha, S. O. Zachary, and M. S. Adaramola, “A Comprehensive Review of Maximum Power Point Tracking (MPPT) Techniques Used in Solar PV Systems,” Mar. 01, 2023, MDPI. doi: 10.3390/en16052206
  10. M. S. Nkambule, A. N. Hasan, A. Ali, J. Hong, and Z. W. Geem, “Comprehensive Evaluation of Machine Learning MPPT Algorithms for a PV System Under Different Weather Conditions,” Journal of Electrical Engineering and Technology, vol. 16, no. 1, pp. 411–427, Jan. 2021, doi: 10.1007/s42835-020-00598-0
  11. M. G. Yahya and M. G. Yahya, “Modified PDPWM control with MPPT algorithm for equal power sharing in cascaded multilevel inverter for standalone PV system under partial shading,” International Journal of Power Electronics and Drive Systems, vol. 14, no. 1, pp. 533–545, Mar. 2023, doi: 10.11591/ijpeds.v14.i1.pp533-545
  12. A. W. Ibrahim et al., “PV maximum power-point tracking using modified particle swarm optimization under partial shading conditions,” Chinese Journal of Electrical Engineering, vol. 6, no. 4, pp. 106–121, Dec. 2020, doi: 10.23919/CJEE.2020.000035
  13. N. Pamuk, “Performance Analysis of Different Optimization Algorithms for MPPT Control Techniques under Complex Partial Shading Conditions in PV Systems,” Energies (Basel), vol. 16, no. 8, Apr. 2023, doi: 10.3390/en16083358
  14. K. Friansa, J. Pradipta, I. N. Haq, E. Leksono, and K. Ariwibawa, “Peningkatan Kinerja Modul PV Kanopi dengan Optimasi Pembayangan pada Area Terbatas,” Majalah Ilmiah Teknologi Elektro, vol. 21, no. 1, p. 41, Jul. 2022, doi: 10.24843/mite.2022.v21i01.p07
  15. R. B. Bollipo, S. Mikkili, and P. K. Bonthagorla, “Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation,” Jul. 06, 2020, Institution of Engineering and Technology. doi: 10.1049/iet-rpg.2019.1163
  16. N. A. Ahmed, S. Abdul Rahman, and B. N. Alajmi, “Optimal controller tuning for P&O maximum power point tracking of PV systems using genetic and cuckoo search algorithms,” in International Transactions on Electrical Energy Systems, John Wiley and Sons Ltd, Oct. 2021. doi: 10.1002/2050-7038.12624
  17. P. Motsoeneng, Bamukunde J., and S. Chowdhury, “Comparison of Perturb & Observe and Hill Climbing MPPT Schemes for PV Plant Under Cloud Cover and Varying Load,” The 10th International Renewable Energy Congress (IREC 2019), p. 123, 2019
  18. M. Kavya and S. Jayalalitha, “Developments in Perturb and Observe Algorithm for Maximum Power Point Tracking in Photo Voltaic Panel: A Review,” Archives of Computational Methods in Engineering, vol. 28, no. 4, pp. 2447–2457, Jun. 2021, doi: 10.1007/s11831-020-09461-x
  19. H. V. P. Nguyen, T. T. Huynh, and V. T. Nguyen, “INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH Comparative Efficiency Assessment of MPPT Algorithms in Photovoltaic Systems,” 2022
  20. I. O. Nyarko, M. A. Elgenedy, and K. Ahmed, “Combined Temprature and Irradiation Effects on the Open Circuit Voltage and Short Circuit Current Constants for Enhancing their Related PV-MPPT Algorithms,” IEEE Conference on Power Electronics and Renewable Energy 2019, pp. 343–348, 2019
  21. V. Jately, B. Azzopardi, J. Joshi, B. Venkateswaran V, A. Sharma, and S. Arora, “Experimental Analysis of hill-climbing MPPT algorithms under low irradiance levels,” Oct. 01, 2021, Elsevier Ltd. doi: 10.1016/j.rser.2021.111467
  22. B. Sabir, S. Der Lu, H. D. Liu, C. H. Lin, A. Sarwar, and L. Y. Huang, “A Novel Isolated Intelligent Adjustable Buck-Boost Converter with Hill Climbing MPPT Algorithm for Solar Power Systems,” Processes, vol. 11, no. 4, Apr. 2023, doi: 10.3390/pr11041010
  23. K. Y. Yap, C. R. Sarimuthu, and J. M. Y. Lim, “Artificial Intelligence Based MPPT Techniques for Solar Power System: A review,” Journal of Modern Power Systems and Clean Energy, vol. 8, no. 6, pp. 1043–1059, Nov. 2020, doi: 10.35833/MPCE.2020.000159
  24. R. Ahmad, A. F. Murtaza, and H. A. Sher, “Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review,” Mar. 01, 2019, Elsevier Ltd. doi: 10.1016/j.rser.2018.10.015
  25. M. A. Dirmawan, Suhariningsih, and R. Rakhmawati, “The Comparison Performance of MPPT Perturb and Observe, Fuzzy Logic Controller, and Flower Pollination Algorithm in Normal and Partial Shading Condition,” in IES 2020 - International Electronics Symposium: The Role of Autonomous and Intelligent Systems for Human Life and Comfort, Institute of Electrical and Electronics Engineers Inc., Sep. 2020, pp. 7–13. doi: 10.1109/IES50839.2020.9231753
  26. H. F. Hashim, M. M. Kareem, W. K. Al-Azzawi, and A. H. Ali, “Improving the performance of photovoltaic module during partial shading using ANN,” International Journal of Power Electronics and Drive Systems, vol. 12, no. 4, pp. 2435–2442, Dec. 2021, doi: 10.11591/ijpeds.v12.i4.pp2435-2442
  27. A. Ali, K. Irshad, M. F. Khan, M. M. Hossain, I. N. A. Al-Duais, and M. Z. Malik, “Artificial intelligence and bio-inspired soft computing-based maximum power plant tracking for a solar photovoltaic system under non-uniform solar irradiance shading conditions—A review,” Oct. 01, 2021, MDPI. doi: 10.3390/su131910575
  28. R. B. Bollipo, S. Mikkili, and P. K. Bonthagorla, “Hybrid, optimal, intelligent and classical PV MPPT techniques: A review,” Jan. 01, 2021, Institute of Electrical and Electronics Engineers Inc. doi: 10.17775/CSEEJPES.2019.02720
  29. M. Sameeullah and A. Swarup, “MPPT schemes for PV system under normal and partial shading condition: A review,” Jul. 01, 2016, Diponegoro university Indonesia - Center of Biomass and Renewable Energy (CBIORE). doi: 10.14710/ijred.5.2.79-94
  30. M. Brahmi, C. Ben Regaya, H. Hamdi, and A. Zaafouri, “Comparative Study Of P&O and PSO Particle Swarm Optimization MPPT Controllers Under Partial Shading,” International Journal of Electrical Engineering and Computer Science, vol. 4, pp. 45–50, Oct. 2022, doi: 10.37394/232027.2022.4.7
  31. M. Mao, Q. Duan, P. Duan, and B. Hu, “Comprehensive improvement of artificial fish swarm algorithm for global MPPT in PV system under partial shading conditions,” Transactions of the Institute of Measurement and Control, vol. 40, no. 7, pp. 2178–2199, Apr. 2018, doi: 10.1177/0142331217697374
  32. G. Liu, J. Zhu, H. Tao, W. Wang, and F. Blaabjerg, “A MPPT Algorithm based on PSO for PV Array Under Partially Shaded Condition,” International Conference on Electrical Machines and Systems (ICEMS), 2019
  33. Ç. B. OĞUZ, E. AVCI, and S. B. ÖZTÜRK, “Effects of PSO Algorithm Parameters on the MPPT System Under Partial Shading Condition,” PLUSBASE AKADEMI ORGANIZASYON VE DANISMANLIK LTD.STI, Mar. 2023, doi: 10.58190/imiens.2023.8
  34. M. A. Khazain, N. M. Hidayat, K. Burhanudin, and E. Abdullah, “Boost Converter of Maximum Power Point Tracking (MPPT) Using Particle Swarm Optimization (PSO) Method,” in 2021 IEEE 12th Control and System Graduate Research Colloquium, ICSGRC 2021 - Proceedings, Institute of Electrical and Electronics Engineers Inc., Aug. 2021, pp. 281–286. doi: 10.1109/ICSGRC53186.2021.9515228
  35. E. W. Mukti, A. Risdiyanto, Ant. A. Kristi, and R. Darussalam, “Particle Swarm Optimization (PSO) based Photovoltaic MPPT Algorithm under the Partial Shading Condition,” Jurnal Elektronika dan Telekomunikasi, vol. 23, no. 2, p. 99, Dec. 2023, doi: 10.55981/jet.552
  36. S. Obukhov, A. Ibrahim, A. A. Zaki Diab, A. S. Al-Sumaiti, and R. Aboelsaud, “Optimal Performance of Dynamic Particle Swarm Optimization Based Maximum Power Trackers for Stand-Alone PV System under Partial Shading Conditions,” IEEE Access, vol. 8, pp. 20770–20785, 2020, doi: 10.1109/ACCESS.2020.2966430
  37. S. A. Farooqui, R. A. Khan, N. Islam, and N. Ahmed, “Cuckoo Search Algorithm and Artificial Neural Network-based MPPT: A Comparative Analysis,” in 2021 IEEE 8th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering, UPCON 2021, Institute of Electrical and Electronics Engineers Inc., 2021. doi: 10.1109/UPCON52273.2021.9667651
  38. 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 Advances in Intelligent Systems and Computing, Springer, 2020, pp. 727–736. doi: 10.1007/978-981-15-0035-0_59
  39. Z. B. Hadj Salah et al., “A New Efficient Cuckoo Search MPPT Algorithm Based on a Super-Twisting Sliding Mode Controller for Partially Shaded Standalone Photovoltaic System,” Sustainability (Switzerland), vol. 15, no. 12, Jun. 2023, doi: 10.3390/su15129753
  40. A. soufyane Benyoucef, A. Chouder, K. Kara, S. Silvestre, and O. A. Sahed, “Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions,” Applied Soft Computing Journal, vol. 32, pp. 38–48, Jul. 2015, doi: 10.1016/j.asoc.2015.03.047
  41. S. Hassan, B. Abdelmajid, Z. Mourad, S. Aicha, and B. Abdenaceur, “An advanced MPPT based on artificial bee colony algorithm for MPPT photovoltaic system under partial shading condition,” International Journal of Power Electronics and Drive Systems, vol. 8, no. 2, pp. 647–653, 2017, doi: 10.11591/ijpeds.v8i2.pp647-653
  42. Pallavi TSawant, P CTejasvi LBhattar, and C LBhattar, “Enhancement of PV System Based on Artificial Bee Colony Algorithm under dynamic Conditions,” pp. 1251–1255, 2016
  43. J. Ahmed and Z. Salam, “A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability,” Appl Energy, vol. 119, pp. 118–130, Apr. 2014, doi: 10.1016/j.apenergy.2013.12.062
  44. A. M. Eltamaly, “An improved cuckoo search algorithm for maximum power point tracking of photovoltaic systems under partial shading conditions,” Energies (Basel), vol. 14, no. 4, Feb. 2021, doi: 10.3390/en14040953
  45. K. Bentata, A. Mohammedi, and T. Benslimane, “Development of rapid and reliable cuckoo search algorithm for global maximum power point tracking of solar PV systems in partial shading condition,” Archives of Control Sciences, vol. 31, no. 3, pp. 495–526, 2021, doi: 10.24425/acs.2021.138690
  46. D. Pilakkat and Kanthalakshmi, “Artificial Bee Colony Algorithm for Peak Power Point Tracking of a Photovoltaic System under Partial Shading Condition,” IEEE International Conference on Current Trends toward Converging Technologies, Coimbatore, India, pp. 1–7, 2018
  47. C. Gonzalez-Castano, C. Restrepo, S. Kouro, and J. Rodriguez, “MPPT Algorithm Based on Artificial Bee Colony for PV System,” IEEE Access, vol. 9, pp. 43121–43133, 2021, doi: 10.1109/ACCESS.2021.3066281
  48. L. L. Jiang, D. L. Maskell, and J. C. Patra, “A novel ant colony optimization-based maximum power point tracking for photovoltaic systems under partially shaded conditions,” Energy Build, vol. 58, pp. 227–236, 2013, doi: 10.1016/j.enbuild.2012.12.001
  49. S. Titri, C. Larbes, K. Y. Toumi, and K. Benatchba, “A new MPPT controller based on the Ant colony optimization algorithm for Photovoltaic systems under partial shading conditions,” Applied Soft Computing Journal, vol. 58, pp. 465–479, Sep. 2017, doi: 10.1016/j.asoc.2017.05.017
  50. E. G. Dada, S. B. Joseph, D. O. Oyewola, A. A. Fadele, H. Chiroma, and S. M. Abdulhamid, “Application of Grey Wolf Optimization Algorithm: Recent Trends, Issues, and Possible Horizons,” Gazi University Journal of Science, vol. 35, no. 2, pp. 485–504, Jun. 2022, doi: 10.35378/gujs.820885
  51. D. Suhardi, L. Syafaah, M. Irfan, M. Yusuf, M. Effendy, and I. Pakaya, “Improvement of maximum power point tracking (MPPT) efficiency using grey Wolf optimization (GWO) algorithm in photovoltaic (PV) system,” in IOP Conference Series: Materials Science and Engineering, Institute of Physics Publishing, Nov. 2019. doi: 10.1088/1757-899X/674/1/012038
  52. M. Y. Silaa, O. Barambones, A. Bencherif, and A. Rahmani, “A New MPPT-Based Extended Grey Wolf Optimizer for Stand-Alone PV System: A Performance Evaluation versus Four Smart MPPT Techniques in Diverse Scenarios,” Inventions, vol. 8, no. 6, Dec. 2023, doi: 10.3390/inventions8060142
  53. G. Satheesh Krishnan, S. Kinattingal, S. P. Simon, and P. S. R. Nayak, “MPPT in PV systems using ant colony optimisation with dwindling population,” IET Renewable Power Generation, vol. 14, no. 7, pp. 1105–1112, May 2020, doi: 10.1049/iet-rpg.2019.0875

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