This paper proposes constant active and reactive power control of a wind farm during gust using the supercapacitor (SC) and static synchronous compensator (STATCOM). The proposed technique is applied to Gabal El-Zayt wind farm which located in Red Sea region of Egypt with a capacity of 200 MW and equipped with doubly fed induction generators (DFIGs) and analyzed during gust wind. As the nature of wind is varying all time, the output power is changing continuously so energy storage system such as SC is required. SC is responsible for maintaining constant output active power by charging when there is excess in the output power of DFIG and discharging when there is a lack in the output power of DFIG. Reactive power compensation is achieved by connecting STATCOM to the power system. SC keeps reactive power constant however its value is improved by connecting STATCOM. Wind farm model is analyzed during gust with the proposed technique while active and reactive power performance is investigated. Firstly, the effect of connecting SC to each wind turbine is studied. Then the effect of connecting STATCOM to the electric power system is studied. Also, the effect of connecting SCs and STATCOM is studied. Finally, the impact of connecting additional STATCOM at different locations is investigated. Results show the proposed technique validity.
Wind energy is regarded as one of the oldest energy sources and has played a significant role. As the nature of wind changes continuously, the generated power varies accordingly. Generation of the pitch angle of a wind turbine’s blades is controlled to prevent damage during high wind speed. This paper presents the development and application of a fuzzy proportional integral control scheme combined with traditional proportional control in the dynamic behavior of pitch angle-regulated wind turbine blades. The combined control regulates rotor speed and output power, allowing control of the power while maintaining the desired rotor speed and avoiding equipment overloads. The studied model is a large-scale wind farm of 120 MW in the Gulf El-Zayt region, Red Sea, Egypt. The control system validity is substantiated by studying different cases of wind speed function: ramp, step, random, and extreme wind speed. The results are compared with the traditional combined control. The model is simulated using MATLAB/SIMULINK software. The simulation results proved the effectiveness of fuzzy tuned PI against traditional PI control.
Recently, the eniergeiice of neural networks as a promising tool for approximating complex system input-output mappings has generated a great (leal of interest in the area of inodeling, identification and control of noiiliiiear dynamical systeins. One specific research are8 that woiild tieiiteticlously beiiefit from this approach is the area of identification and control of Iiiglt performance aircraft, especially at high angles of attack. At those flight conditions, the control task becomes est.remclq dificult due to added design complexity and hard nonlinearities characterizing the system. In this paper, we investigate one type of neiiml iietworks, iianiely the Radial Basis Fniictioii (RBF) networks, and apply lliein to the identification and control problems of ari aircraft system. The RBI: network is used as an on-line appiosiniator of the aircraft pitch dynamics, conibinecl with a nonlinear cotit rol law to iiiipiove the closecl-loop system perforinanre. Tlie results are illustrated through simulations using a nonlinear model of the F-18 aircraft pitch dynamics.
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