Enhanced Active Power Improvement in Wind Energy Conversion Systems through Rotor Side Converter Current Control of Doubly Fed Induction Generator

2023 33rd Australasian Universities Power Engineering Conference (AUPEC)(2023)

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摘要
In order to keep up with the ever-increasing demand for energy, wind power generation is a viable and sustainable option. However, the variable wind speed results in variable output power, which adversely affects the stability of the power system. The transients in the wind energy conversion system (WECS) output power, such as greater value of overshoot, settling time, and steady-state error degrade the power system stability and need to be minimized as much as possible. To address this issue, various techniques have been proposed in the literature. In this study, we propose a novel state-of-the-art approach to design and implement controllers. Four different controllers are designed and implemented to optimize the efficiency of WECS by regulating the rotor current of the Doubly Fed Induction Generator (DFIG). To improve the system's efficiency and reduce transients, a proportional-integral (PI) controller is first developed and implemented to minimize steady-state errors. Then, a fuzzy controller is developed and implemented to control the overshoot to a minimum. Then a hybrid of PI and Fuzzy combines the effect of both controllers and provides effective control of the system output. Next, an adaptive neuro-fuzzy controller is developed and implemented to get control of the system. While operating in a range of variable wind speeds, controller performance is evaluated based on their ability to dampen rotor current transients such as percentage overshoot, settling time, and steady state error (SSE). The results reveal that ANFIS performs better.
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关键词
Deep Learning,Adaptive Neuro Fuzzy Inference System (ANFIS),Fuzzy-PI,DFIG,WECS,Active Power,SSE,Overshoot
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