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Abstract

Solar energy is a type of renewable energy whose capacity is tremendous and fast in increasing its capacity so that it can be used for energy sustainability in the future. Solar panels are the only devices that can be used to utilize solar energy. Maximum Power Point Tracking (MPPT) is a method to maximize the power generated by solar panels. However, the problem with solar panels is the condition of partial shading, this occurs due to something blocking the rate of solar irradiation to the solar panel. The result is that there are 2 or more maximum power points from solar panels, the highest power is the Global Maximum Power Point (GMPP) and the other is the Local Maximum Power Point (LMPP). This partial shading condition cannot use conventional MPPT methods due to the complexity of finding GMPP. So, MPPT optimization method is needed, one of which is the Improved Whale Optimization Algorithm (IWOA). IWOA is a development of the Whale Optimization Algorithm (WOA) by applying the Sine-Tent-Cosine Map for the first time the algorithm works to be more effective in the initialization process of the algorithm population and can ensure a more uniform distribution of population distribution throughout the search space. IWOA will be applied to the MPPT system to achieve the GMPP of the solar panel under partial shading conditions.

Keywords

Solar Panel MPPT IWOA Partial Shading Condition

Article Details

How to Cite
Habibi, M., Prakoso, R., Adila, A., Efendi, M., Windarko, N., & Eviningsih, R. (2025). Design and Implementation MPPT Improved Whale Optimization Algorithm to Overcome Partial Shading Condition on Solar Panel. INVOTEK: Jurnal Inovasi Vokasional Dan Teknologi, 24(2), 115-126. https://doi.org/https://doi.org/10.24036/invotek.v24i2.1219

References

  1. J. S. Setyono, F. H. Mardiansjah, and M. F. K. Astuti, “Potensi pengembangan energi baru dan energi terbarukan di kota semarang,” J. Riptek, vol. 13, no. 2, pp. 177–186, 2019, doi: https://doi.org/10.35475/riptek.v13i2.68.
  2. F. Afif and A. Martin, “Tinjauan potensi Dan Kebijakan energi surya di Indonesia,” J. Engine Energi, Manufaktur, dan Mater., vol. 6, no. 1, pp. 43–52, 2022, doi: https://doi.org/10.30588/jeemm.v6i1.997.
  3. M. S. Al Amin, E. Emidiana, I. K. Pebrianti, and Y. Irwansi, “Penggunaan Panel Surya Sebagai Pembangkit Listrik Pada Alat Pengering Makanan,” J. Ampere, vol. 7, no. 1, pp. 15–21, 2022, doi: https://doi.org/10.31851/ampere.v7i1.7703.
  4. S. W. Putri, G. Marausna, and E. E. Prasetiyo, “Analisis Pengaruh Intensitas Cahaya Matahari Terhadap Daya Keluaran Pada Panel Surya,” Tek. STTKD J. Tek. Elektron. Engine, vol. 8, no. 1, pp. 29–37, 2022, doi: https://doi.org/10.56521/teknika.v8i1.442.
  5. D. A. K. Wida, K. Sumaja, and P. P. H. Wiguna, “Analisis Hubungan Intensitas Radiasi Dan Lama Penyinaran Matahari Dengan Parameter Cuaca Di Stasiun Meteorologi Ngurah Rai Serta Pengaruhnya Terhadap Potensi Pembangkit Listrik Tenaga Surya Di Bali Selatan,” Meteo Ngurah Rai, vol. 5, no. 1, pp. 1–7, 2019.
  6. B.-R. Peng, K.-C. Ho, and Y.-H. Liu, “A novel and fast MPPT method suitable for both fast changing and partially shaded conditions,” IEEE Trans. Ind. Electron., vol. 65, no. 4, pp. 3240–3251, 2017, doi: 10.1109/TIE.2017.2736484.
  7. S. Motahhir, A. El Ghzizal, S. Sebti, and A. Derouich, “Modeling of photovoltaic system with modified incremental conductance algorithm for fast changes of irradiance,” Int. J. Photoenergy, vol. 2018, no. 1, p. 3286479, 2018, doi: https://doi.org/10.1155/2018/3286479.
  8. P. E. Broto and J. A. Hamonangan, “Review perbandingan teknik Maximum Power Point Tracker (MPPT) untuk sistem pengisian daya menggunakan sel surya,” J. Teknol. Dirgant., vol. 16, no. 2, 2018, doi: 10.30536/j.jtd.2018.v16.a2998.
  9. L. P. S. Raharja, R. P. Eviningsih, I. Ferdiansyah, and D. S. Yanaratri, “Penggunaan Daya Panel Surya Dengan MPPT Bisection Pada Proses Charging Baterai,” J. Teknol. Terpadu, vol. 9, no. 1, pp. 24–33, 2021.
  10. X. Yue, D. Geng, Q. Chen, Y. Zheng, G. Gao, and L. Xu, “2-D lookup table based MPPT: Another choice of improving the generating capacity of a wave power system,” Renew. Energy, vol. 179, pp. 625–640, 2021, doi: https://doi.org/10.1016/j.renene.2021.07.043.
  11. M. N. Habibi, M. S. W. Jati, N. A. Windarko, and A. Tjahjono, “Maximum Power Point Tracking Menggunakan Algoritma Artificial Neural Network Berbasis Arus Hubung Singkat Panel Surya,” J. Rekayasa Elektr., vol. 16, no. 2, 2020, doi: 10.17529/jre.v16i2.14860.
  12. U. Yilmaz, A. Kircay, and S. Borekci, “PV system fuzzy logic MPPT method and PI control as a charge controller,” Renew. Sustain. Energy Rev., vol. 81, pp. 994–1001, 2018, doi: https://doi.org/10.1016/j.rser.2017.08.048.
  13. V. Waghmare-Ujgare and M. D. Goudar, “Exploration of partial shading condition in photovoltaic array,” in 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), 2017, pp. 931–936. doi: 10.1109/ICECDS.2017.8389572.
  14. W. Hayder, E. Ogliari, A. Dolara, A. Abid, M. Ben Hamed, and L. Sbita, “Improved PSO: a comparative study in MPPT algorithm for PV system control under partial shading conditions,” Energies, vol. 13, no. 8, p. 2035, 2020, doi: https://doi.org/10.3390/en13082035.
  15. A. P. Firmanza, M. N. Habibi, N. A. Windarko, and D. S. Yanaratri, “Differential evolution-based mppt with dual mutation for pv array under partial shading condition,” in 2020 10th Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS), 2020, pp. 198–203. doi: 10.1109/EECCIS49483.2020.9263430.
  16. A. Tjahjono, D. O. Anggriawan, M. N. Habibi, and E. Prasetyono, “Modified grey wolf optimization for maximum power point tracking in photovoltaic system under partial shading conditions,” Int. J. Electr. Eng. Informatics, vol. 12, no. 1, pp. 94–104, 2020, doi: 10.15676/ijeei.2020.12.1.8.
  17. R. N. Prakoso, M. Z. Efendi, and M. N. Habibi, “Design and Implementation Mountaineering Team-Based Optimization Algorithm for MPPT on Partial Shading Conditions,” in 2024 International Electronics Symposium (IES), 2024, pp. 43–48. doi: 10.1109/IES63037.2024.10665787.
  18. Z. Liang, T. Shu, and Z. Ding, “A novel improved whale optimization algorithm for global optimization and engineering applications,” Mathematics, vol. 12, no. 5, p. 636, 2024, doi: https://doi.org/10.3390/math12050636.
  19. S. Mirjalili and A. Lewis, “The whale optimization algorithm,” Adv. Eng. Softw., vol. 95, pp. 51–67, 2016, doi: https://doi.org/10.1016/j.advengsoft.2016.01.008.
  20. M. H. Nadimi-Shahraki, H. Zamani, Z. Asghari Varzaneh, and S. Mirjalili, “A systematic review of the whale optimization algorithm: theoretical foundation, improvements, and hybridizations,” Arch. Comput. Methods Eng., vol. 30, no. 7, pp. 4113–4159, 2023, doi: 10.1007/s11831-023-09928-7.
  21. C. Olalla, C. Deline, and D. Maksimovic, “Performance of mismatched PV systems with submodule integrated converters,” IEEE J. Photovoltaics, vol. 4, no. 1, pp. 396–404, 2013, doi: 10.1109/JPHOTOV.2013.2281878.