Design and implemented buck-boost converter based fuzzy logic control on wind power plant

R. D. Noriyati, Ali Musyafa*, A. Rahmadiansah, A. S. Utama, M. K. Asy'ari, M. Abdillah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Nowadays, the need for energy in Indonesia increases related to population growth rapidly where it leads to degrading the reliability of the power system operation. Meanwhile, conventional energy reserves such as oil, coal, and others are running low. Therefore, the usage of alternative energy that categorized as green technology and promising energy in the future is a must. One of the most potentials of those energy technologies is a wind power generation. Generator, a component of wind power plant, is having the function to convert mechanical energy into electrical energy. Due to the intermittent of wind power generator output affected by the weather circumstances, a converter device namely a buck-boost converter was utilized as control of the wind generator to increase or decrease the voltage depending on the desired voltage on the system. To enhance the performance of the buck-boost converter, intelligent control namely fuzzy logic controller (FLC) was employed as feedback control of the converter. Here, error and delta error signals of the converter were utilized as the input data of FLC while the duty cycle of the converter was employed as output data of FLC. In this research work, the proposed control model has designed to work for blade rotation within the range of 192-364 rpm. From the simulation results, the performance of the converter controlled by FLC had obtained the time delay of 0.037 s, found the time up of 0.159 s, produced the peak time on 0.354 s, attained the overshoot of 1.07 %, and reached the time for steady-state on 0.164 s. Meanwhile, when the proposed control model had connected to the hardware, it had resulted on 2.6 s for the delay time, produced the uptime of 3.5 s, found the peak time of 4.9 s, achieved the time for steady-state on 3.2s and generated the steady-state error of 1.92 %.

Original languageEnglish
Pages (from-to)115-122
Number of pages8
JournalInternational Journal of Mechanical and Mechatronics Engineering
Issue number1
Publication statusPublished - 1 Feb 2020


  • Blade
  • Control system
  • Neuro-fuzzy
  • Pitch angle
  • Wind turbine


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