Flower Polination Algorithm Sebagai Optimalisasi LFC Pada Hybrid Pembangkit Wind-Diesel

Authors

  • Machrus Ali Universitas Darul Ulum
  • Agus Siswanto Universitas 17 Agustus 1945, Cirebon
  • Mudofar Baehaqi Universitas 17 Agustus 1945 Cirebon

DOI:

https://doi.org/10.56795/fortech.v5i1.5106

Keywords:

Wind Diesel, PID, LFC, FPA

Abstract

As input power, the amount of wind and wind speed greatly influences the wind power generation system. A combination of a wind-diesel power generation system is needed to obtain optimal power quality. A hybrid system is a controlled network of multiple renewable energy generators such as wind turbines, solar cells, micro-hydro, and so on. Gain settings that are not optimal and the time constant is small in Load Frequency Control (LFC), causing its ability to be weak (weak line). In practice, the wind-diesel system is controlled with a PID controller. Setting the gain value of the PID is still in the conventional method, so it is difficult to get the optimal value. In this research, a control design was implemented using the Smart Method to find the optimum value of the Proportional Integral Derivative (PID) based on the FPA (Flower Pollination Algorithm). For comparison, methods were used without control methods, conventional PID methods, PID Auto tuning methods, and FPA (Flower Pollination Algorithm) methods. Wind-diesel modeling uses transfer function diagrams of wind and diesel turbines. This study compares several uncontrolled methods and conventional PID, PID-Auto tuning, and PID-FPA. The results of the research that has been carried out show that the smallest undershoot is -1.187.10-04 for PID-FPA, the smallest overshot is 0 for PID-FPA, and the fastest settling time is 9.827 s for PID-FPA. So it can be concluded that PID-FPA is the best controller in this research. This research can later be continued using other artificial intelligence methods.

References

I. C. Gunadin et al., “Stability Margin When Wind Turbine Large Scale Penetrated to South Sulawesi-Indonesia Power System Using Optimally Pruned Extreme Learning Machine (OPELM),” 2024, pp. 224–234. doi: 10.2991/978-94-6463-366-5_21.

K. Kavadias and P. Triantafyllou, “2.23 - Wind-Based Stand-Alone Hybrid Energy Systems,” in Comprehensive Renewable Energy, Second Edition: Volume 1-9, vol. 1–2, 2022, pp. 749–793. doi: 10.1016/B978-0-12-819727-1.00162-X.

G. A. P. P, O. Penangsang, A. Priyadi, A. S. Sistem, and T. Listrik, “Analisis Stabilitas Transient Pada Sistem Tenaga Listrik dengan Mempertimbangkan Beban Non - Linear,” vol. 1, no. 1, pp. 1–6, 2012.

M. M. Gulzar, M. Iqbal, S. Shahzad, H. A. Muqeet, M. Shahzad, and M. M. Hussain, “Load Frequency Control (LFC) Strategies in Renewable Energy‐Based Hybrid Power Systems: A Review,” Energies, vol. 15, no. 10, 2022, doi: 10.3390/en15103488.

Mansur, S. Pranoto, A. Siswanto, and L. Pagiling, “Analisis Pembangkit Hybrid Energi Terbarukan Dengan Metode Particle Swarm Optimization (Pso),” Pros. Semin. Nas. Tek. Elektro dan Inform., pp. 372–375, 2022.

M. Ali et al., “The comparison of dual axis photovoltaic tracking system using artificial intelligence techniques,” IAES Int. J. Artif. Intell., vol. 10, no. 4, p. 901, Dec. 2021, doi: 10.11591/ijai.v10.i4.pp901-909.

Muhammad Agil Haikal, Dandy Tulus Herlambang, Machrus Ali, and Muhlasin, “Desain Optimasi PID Controller Pada Heating Furnace Temperature Menggunakan Metode Particle Swarm Optimization (PSO),” ALINIER J. Artif. Intell. Appl., vol. 2, no. 2, pp. 77–82, Nov. 2021, doi: 10.36040/alinier.v2i2.5162.

M. Ali, “Optimasi Pemograman Sistem Pengendalian Mesin CNC Pengebor PCB Berdasar Metode Firefly Algorithm,” ALINIER J. Artif. Intell. Appl., vol. 3, no. 2, pp. 28–37, 2022, doi: 10.36040/alinier.v3i2.5840.

M. Ali, H. Suyono, M. A. Muslim, M. R. Djalal, Y. M. Safarudin, and A. A. Firdaus, “Determination of the parameters of the firefly method for PID parameters in solar panel applications,” SINERGI, vol. 26, no. 2, p. 265, Jun. 2022, doi: 10.22441/sinergi.2022.2.016.

M. Ali et al., “Determining firefly ideal parameter for tuning Kp, Ki, And Kd parameter in photovoltaic application,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1034, no. 1, p. 12078, Feb. 2021, doi: 10.1088/1757-899X/1034/1/012078.

M. Siswanto, S. Arfaah, R. Rukslin, M. Muhlasin, and M. Ali, “Rekonfigurasi 33 Kanal Irigasi Menggunakan Metode Firefly Algorithm (MFA),” J. FORTECH, vol. 4, no. 1, pp. 43–47, Jun. 2023, doi: 10.56795/fortech.v4i1.4106.

M. Ali, A. Raikhani, H. Sopian, and I. Umami, “Optimasi Pengaturan Kecepatan Motor Shunt Berbasis Imperalist Competitive Algorithm (ICA),” J. Intake J. Penelit. Ilmu Tek. dan Terap., vol. 9, no. 1, pp. 26–31, Apr. 2020, doi: 10.32492/jintake.v9i1.756.

M. Ali, Muhlasin, H. Nurohmah, A. Raikhani, H. Sopian, and N. Sutantra, “Combined ANFIS method with FA, PSO, and ICA as Steering Control Optimization on Electric Car,” in 2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS), IEEE, Oct. 2018, pp. 299–304. doi: 10.1109/EECCIS.2018.8692885.

M. Ali and H. Sucipto, “Ant Colony Optimization Algorithm Implementation for Distribution of Natural Disaster Relief Logistics in Jombang Regency Web Base,” IOP Conf. Ser. Earth Environ. Sci., vol. 704, no. 1, p. 12008, Mar. 2021, doi: 10.1088/1755-1315/704/1/012008.

B. Budiman and M. Ali, “PID Controller Design for Heating Furnace Temperature Based on Bat Algorithm (BA),” JEEMECS (Journal Electr. Eng. Mechatron. Comput. Sci., vol. 6, no. 1, pp. 45–50, 2023, doi: 10.26905/jeemecs.v6i1.9307.

M. Arrohman, R. Fajardika, M. Muhlasin, and M. Ali, “Optimasi Frekuensi Kontrol pada Sistem Hybrid Wind-Diesel Menggunakan PID Kontroler Berbasis ACO dan MFA,” J. Rekayasa Mesin, vol. 9, no. 1, pp. 65–68, May 2018, doi: 10.21776/ub.jrm.2018.009.01.10.

M. Ali, M. R. Djalal, S. Arfaah, Muhlasin, M. Fakhrurozi, and R. Hidayat, “Application of Energy Storage-PID For Load Frequency Control In Micro-hydro Using Flower Pollination Algorithm,” in 2021 3rd International Conference on Research and Academic Community Services (ICRACOS), IEEE, Oct. 2021, pp. 281–285. doi: 10.1109/ICRACOS53680.2021.9702063.

M. Ali, M. R. Djalal, M. Fakhrurozi, Kadaryono, Budiman, and D. Ajiatmo, “Optimal Design Capacitive Energy Storage (CES) for Load Frequency Control in Micro Hydro Power Plant Using Flower Pollination Algorithm,” in 2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS), IEEE, Oct. 2018, pp. 21–26. doi: 10.1109/EECCIS.2018.8692997.

M. R. Djalal, M. Ali, H. Nurohmah, and D. Ajiatmo, “Aplikasi Algoritma Differential Evolution untuk Desain Optimal Load Frequency Control pada Pembangkit Listrik Tenaga Hibrid Angin dan Diesel,” J. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 5, p. 511, 2018, doi: 10.25126/jtiik.201855430.

M. Ali, Budiman, A. R. Sujatmika, and A. A. Firdaus, “Optimization of controller frequency in wind-turbine based on hybrid PSO-ANFIS,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1034, no. 1, p. 12070, Feb. 2021, doi: 10.1088/1757-899X/1034/1/012070.

Downloads

Published

2024-05-26

How to Cite

Ali, M., Siswanto, A., & Baehaqi, M. (2024). Flower Polination Algorithm Sebagai Optimalisasi LFC Pada Hybrid Pembangkit Wind-Diesel. Jurnal FORTECH, 5(1), 41–47. https://doi.org/10.56795/fortech.v5i1.5106