Sensorless vector control of doubly fed induction generator based wind turbine using fuzzy fractional order adaptive disturbance rejection control

ABSTRACT

This paper represents a novel sensorless method for the vector control of doubly fed induction generator (DFIG) in a wind turbine system. The proposed method is based on the fuzzy fractional order adaptive disturbance rejection control (FFOADRC) estimating the rotor velocity. In this new method, there is no need to calculate the coupling terms and eliminate them by feed-forward compensation. In addition, all disturbances (internal and external) are estimated by a fractional order extended state observer (FESO). The effects of these disturbances are then neutralized by generating a suitable control command. The operation of the proposed system has been simulated in Matlab/Simulink environment. The comparisons were made between FFOADRC, adaptive disturbance rejection control (ADRC), fuzzy ADRC (FADRC), and proportional-integral (PI) controller under different operating conditions. The results show that: (1) After DFIG starts and under similar conditions, using FFOADRC, FADRC, and ADRC, the velocity reaches the steady state with the overshoot values of 0%, 3.64%, and 8.03%, respectively. (2) In the steady state after wind velocity variation, the %THD values of the stator current using FFOADRC, FADRC, and ADRC are, respectively, 1.47, 1.54, and 2.79. In this case, utilizing the PI controller, the control circuit has a slower performance than three other controllers. (3) The comparison between the aforementioned controllers during DFIG velocity control shows that using FFOADRC, the values of settling time, rise time, peak time, and delay time are smaller, and we have better performance that indicates the superiority of FFOADRC over ADRC, FADRC, and PI controller. Therefore, FFOADRC improves the wind turbine performance in different conditions

KEYWORDS:

• Doubly fed induction generator (DFIG)
• fuzzy fractional order adaptive disturbance rejection control (FFOADRC)
• maximum power point tracking (MPPT)
• vector control
• wind velocity

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Seyed Reza Mosayyebi

Seyed Reza Mosayyebi received the M.Sc. degree from Iran University of Science and Technology (IUST), Tehran, Iran. He is currently a PhD student in Power Engineering at the University of Guilan, Rasht, Iran. His research interests are power electronics and power systems control.

Hamed Mojallali

Hamed Mojallali received the Ph.D. degree from Iran University of Science and Technology (IUST), Tehran, Iran. He is currently an associate professor of electrical engineering and faculty member of the University of Guilan, Rasht, Iran. His research interests are modeling, system identification, optimization algorithms and control theory.

Seyed Hamid Shahalami

Seyed Hamid Shahalami received the Ph.D. degree from University of Henri Poincare, Nancy 1, France. He is currently an assistant professor of electrical engineering and faculty member of the University of Guilan, Rasht, Iran. His research interests are power electronics, electric drives, passive and active filters, FACTS devices and power quality control.