Strategi Manajemen Energi PV dan Baterai Pada Mikrogrid Dengan Kendali Zelio Logic

Strategi Manajemen Energi PV dan Baterai Pada Mikrogrid Dengan Kendali Zelio Logic

Authors

  • Adhi Kusmantoro Universitas PGRI Semarang

DOI:

https://doi.org/10.51903/juritek.v6i1.7089

Keywords:

Mikrogrid, Baterai, Photovoltaik (PV), Manajemen Energi, Zelio Logic

Abstract

Kebutuhan energi listrik yang terus meningkat serta ketergantungan terhadap sumber energi konvensional mendorong perlunya pemanfaatan energi terbarukan yang lebih efisien dan berkelanjutan. Solusi yang dapat diterapkan dengan sistem mikrogrid berbasis Photovoltaic (PV) dan baterai. Namun perubahan iradiasi matahari memerlukan strategi manajemen energi yang tepat agar suplai daya stabil. Tujuan penelitian ini adalah untuk mengatur aliran daya PV dan baterai secara otomatis, dengan kapasitas PV 5 kWp dan baterai 3000 Ah, serta beban sebesar 2000 W. Metode penelitian dilakukan dengan perancangan sistem mikrogrid, dan penyusunan algoritma kontrol manajemen energi. Strategi kendali yang diterapkan memakai prioritas sumber daya utama PV, baterai sebagai cadangan kedua, dan PLN sebagai sumber cadangan lainnya. Pengaturan dilakukan berdasarkan nilai State of Charge (SOC) baterai, dengan batas maksimum 95% dan batas minimum 20%. Ketika daya PV melebihi kebutuhan beban, energi digunakan untuk menyuplai beban dan mengisi baterai. Sebaliknya, saat daya PV lebih rendah dari beban, baterai akan digunakan hingga mencapai batas minimum SOC, kemudian sistem akan beralih secara otomatis ke PLN. Hasil penelitian memperlihatkan bahwa kendali zelio logic mampu melakukan pengaturan aliran daya secara otomatis pada berbagai kondisi operasi seperti intensitas PV tinggi, intensitas PV rendah, beban puncak, kondisi baterai penuh, kondisi baterai minimum, serta perpindahan otomatis ke PLN. Sistem juga mampu melindungi baterai dari kondisi overcharge dan overdischarge melalui pengaturan batas SOC. Efisiensi diperoleh nilai sebesar 85,7% atau sekitar 86%, yang menunjukkan bahwa energi dari PV dapat dimanfaatkan secara optimal dan penggunaan PLN dapat diminimalkan.

References

[1] M. Hamidi, A. Raihani, and O. Bouattane, “Sustainable Intelligent Energy Management System for Microgrid Using Multi-Agent Systems: A Case Study,” Sustain., vol. 15, no. 16, August 2023, doi: 10.3390/su151612546.

[2] K. Sayed, “Buildings Energy Management System,” Energy Conserv. in Resid., Commercial and Industrial, pp. 15–81, 2016, doi: 10.1002/9781119422099.ch2.

[3] Y. Qi, R. Liu, H. Lin, J. Zhong, and Z. Chen, “Distributed hybrid energy storage photovoltaic microgrid control based on MPPT algorithm and equilibrium control strategy,” Energy Informatics, vol. 7, no. 1, December 2024, doi: 10.1186/s42162-024-00454-9.

[4] M. Alsolami, A. Alferidi, and B. Lami, “Real-Time Energy Management of a Microgrid Using MPC-DDQN-Controlled V2H and H2V Operations with Renewable Energy Integration,” Energies, vol. 18, no. 17, August 2025, doi: 10.3390/en18174622.

[5] Z. Cabrane, M. Ouassaid, D. Choi, and S. H. Lee, “Control and Management of Multi-Agent Systems Using Fuzzy Logic for Microgrids,” Batteries, vol. 11, no. 7, pp. 1–16, July 2025, doi: 10.3390/batteries11070279.

[6] C. H. Yoo, I. Y. Chung, H. J. Lee, and S. S. Hong, “Intelligent control of battery energy storage for multi-agent based microgrid energy management,” Energies, vol. 6, no. 10, pp. 4956–4979, September 2016, doi: 10.3390/en6104956.

[7] J. A. Rodriguez-Gil et al., Energy management system in networked microgrids: an overview, vol. 17, no. 1. Springer Berlin Heidelberg, July July 2024. doi: 10.1007/s12667-024-00676-6.

[8] S. Behera and N. B. Dev Choudhury, “Optimal battery management in PV + WT micro-grid using MSMA on fuzzy-PID controller: a real-time study,” Sustain. Energy Res., vol. 11, no. 1, November 2024, doi: 10.1186/s40807-024-00136-w.

[9] N. Castañeda-Arias, N. L. Díaz-Aldana, A. L. Hernandez, and A. L. Jutinico, “Energy Management in Microgrid Systems: A Comprehensive Review Toward Bio-Inspired Approaches for Enhancing Resilience and Sustainability,” Electricity, vol. 6, no. 4, pp. 1–42, December 2025, doi: 10.3390/electricity6040073.

[10] O. Kucukkor, U. Durak, and T. H. Karakoc, “Evaluation of P&O algorithm efficiency under varying conditions for solar powered unmanned aerial vehicle,” CEAS Aeronaut. J., November 2025, doi: 10.1007/s13272-025-00918-y.

[11] A. Kusmantoro and I. Farikhah, “Power management on DC microgrid with new DC coupling based on fuzzy logic,” Indones. J. Electr. Eng. Comput. Sci., vol. 32, no. 2, pp. 620–631, November 2023, doi: 10.11591/ijeecs.v32.i2.pp620-631.

[12] Adhi Kusmantoro and Ardyono Priyadi, “Strategi Peningkatan Kinerja DC Microgrid dengan Konfigurasi DC/AC Coupling,” J. Nas. Tek. Elektro dan Teknol. Inf., vol. 12, no. 3, pp. 175–180, Agustus 2023, doi: 10.22146/jnteti.v12i3.7151.

[13] A. Kusmantoro, “Multi-Inverter Coordinated Control on AC Microgrid for Increased Load Power,” 2023 6th Int. Conf. Vocat. Educ. Electr. Eng. Integr. Scalable Digit. Connect. Intell. Syst. Green Technol. Educ. Sustain. Community Dev. ICVEE 2023 - Proceeding, pp. 90–95, December 2023, doi: 10.1109/ICVEE59738.2023.10348326.

[14] A. Kusmantoro and T. Hiyama, “Effect of fuzzy logic controller on voltage stability of parallel boost converter configuration,” J. Soft Comput. Explor., vol. 4, no. 2, pp. 87–98, June 2023, doi: 10.52465/joscex.v4i2.153.

[15] A. Kusmantoro and I. Farikhah, “Real-Time Microgrid Centralized Control For Consuming Water Pump,” E3S Web Conf., vol. 465, December 2023, doi: 10.1051/e3sconf/202346502003.

[16] A. Kusmantoro, A. Priyadi, V. L. Budiharto Putri, and M. Hery Purnomo, “Coordinated Control of Battery Energy Storage System Based on Fuzzy Logic for Microgrid with Modified AC Coupling Configuration,” Int. J. Intell. Eng. Syst., vol. 14, no. 2, pp. 495–510, May 2021, doi: 10.22266/ijies2021.0430.45.

[17] A. Kusmantoro, Ardyono Priyadi, Vita Lystianingrum Budiharto Putri, and Mauridhi Hery Purnomo, “Kinerja Micro Grid Menggunakan Photovoltaic-Baterai dengan Sistem Off-Grid,” J. Nas. Tek. Elektro dan Teknol. Inf., vol. 9, no. 2, pp. 211–217, Mei 2020, doi: 10.22146/jnteti.v9i2.155.

[18] A. Kusmantoro and T. Hiyama, “Simulation Coordination Control of PVAnd Battery on Microgrid With PI Controller,” Sci. J. Informatics, vol. 10, no. 2, pp. 187–198, May 2023, doi: 10.15294/sji.v10i2.43929.

[19] D. Azuatalam, K. Paridari, Y. Ma, M. Förstl, A. C. Chapman, and G. Verbič, “Energy management of small-scale PV-battery systems: A systematic review considering practical implementation, computational requirements, quality of input data and battery degradation,” Renew. Sustain. Energy Rev., vol. 112, no. April, pp. 555–570, June 2019, doi: 10.1016/j.rser.2019.06.007.

[20] N. Altin, S. E. Eyimaya, and A. Nasiri, “Multi-Agent-Based Controller for Microgrids: An Overview and Case Study,” Energies, vol. 16, no. 5, March 2023, doi: 10.3390/en16052445.

[21] Y. Gupta and M. Amin, “A Neural Network-Based Energy Management System for PV-Battery Based Microgrids,” no. Ml, pp. 1–10, June 2022, [Online]. Available: http://arxiv.org/abs/2206.06716

[22] S. E. Eyimaya and N. Altin, “Review of Energy Management Systems in Microgrids,” Appl. Sci., vol. 14, no. 3, pp. 1–20, February 2024, doi: 10.3390/app14031249.

Published

2026-03-28

How to Cite

Kusmantoro, A. (2026). Strategi Manajemen Energi PV dan Baterai Pada Mikrogrid Dengan Kendali Zelio Logic: Strategi Manajemen Energi PV dan Baterai Pada Mikrogrid Dengan Kendali Zelio Logic. Jurnal Ilmiah Teknik Mesin, Elektro Dan Komputer, 6(1), 226–242. https://doi.org/10.51903/juritek.v6i1.7089