دانلود رایگان مقاله انگلیسی بهبود عملکرد دینامیکی سیستم تبدیل انرژی باد با استفاده از بهینه سازی پروانه (MFO) - الزویر 2018

ABSTRACT

Moth-Flame Optimization (MFO) technique has recently been explored to develop a novel algorithm for distributed optimization and control. In this paper, the MFO-based design of blade pitch controllers (BPCs) is proposed for wind energy conversion system (WECS) to enhance the damping of oscillations in the output power and voltage. The simple Proportional-Integral-Differential (PID) is used to realize the advantage of the proposed hybrid referential integrity MFO technique. The proposed blade pitch controllers are termed as BPC-PID (MFO). Single wind turbine system, equipped with BPC-PID (MFO), is considered to accomplish this study. The suggested WECS model considers small as well as large scale uncertainties. MFO is utilized to search for optimal controller parameters by minimizing a candidate time-domain based objective function. The performance of the proposed controller has been compared to those of the conventional PID controller based on Zeigler Nichols and simplex algorithm and the PID controller optimized by genetic algorithms (GA), to demonstrate the superior efficiency of the MFO-based BPC-PID. Simulation results emphasis on the better performance of the proposed BPC-PID (MFO) compared to conventional and GA-based BPC-PID controllers over a wide range of operating conditions and control system parameters uncertainties.

Conclusions

The parameters of blade pitch controller by MFO algorithm design is carried out to cope with system nonlinearities comprising the pitch servo motor, actuator, and blade torsional dynamics. A candidate timedomain based objective function has been considered to minimize both maximum overshooting and settling time. Comparing the proposed MFO-based BPC-PID to conventional BPC-PID (ZN), BPC-PID (SA), and GA-based PID controllers has proved the superiority of our design in capturing system nonlinearities and control system parameters variation. Consequently, the suggested design can guarantee system stability under increased mechanical torque perturbations and excessive wind speed with controller parameters uncertainties. The proposed approach (RI-MFO) showed accuracy in defining the most optimal BPC-PID. Simulation results have been carried out to reveal the robustness of the proposed design against system parameters uncertainties. Thus, the proposed approach succeeded in proving its capability to select the most robust controller.