International Journal of Engineering Research and General Science

14-23

Authors: Martin Ogharandukun1 , Fidelis Ikechukwu Onah2, Anthony Lordson Amana3, Ngang Bassey Ngang 4

The increase in the demand for wind energy on a large scale also gives rise to increased demand for wind energy conversion machines (WECMs). one of these is the induction wind turbine generator otherwise referred to as the Doubly Fed Induction Machine. The doubly-fed induction generator (DFIG) is the preferred choice, however, due to the sensitive nature of this machine, it suffers setbacks as a result of speed variations and grid faults during operation. To overcome these undesirable characteristics, this paper proposes an adaptive control technique to regulate the machine speed when in operation. The sequence of this procedure is to first characterize the performance of the induction machine, design an adaptive control rule base to increase the efficiency of the wind turbine that drives the generator rotor, and train an artificial Neural Network(ANN) in the adaptive rule base to improve the energy generated through the speed control device. The next stage is to develop a conventional proportional Integral Control (PIC) system for Energy Efficiency.The outcomes showed that the conventional generator's efficiency is stable from 4 seconds to 10 seconds at 59.7%. On the other hand, when an adaptive controller is used, generator one gives efficiency of 60.77% over a stable time range of 4 to 10 seconds. When compared to the conventional method, the system's energy efficiency increases by 1.07% when an adaptive controller is used. The final results show that generator two has the highest conventional generator efficiency of 76.5% and the highest adaptive controller generator efficiency of 77.87%. The results show a 1.3% improvement when an adaptive controller is incorporated into the system compared to the traditional Approach Keyword- Energy efficiency, improvement, fed induction, generator, adaptive control The increase in the demand for wind energy on a large scale also gives rise to increased demand for wind energy conversion machines (WECMs). one of these is the induction wind turbine generator otherwise referred to as the Doubly Fed Induction Machine. The doubly-fed induction generator (DFIG) is the preferred choice, however, due to the sensitive nature of this machine, it suffers setbacks as a result of speed variations and grid faults during operation. To overcome these undesirable characteristics, this paper proposes an adaptive control technique to regulate the machine speed when in operation. The sequence of this procedure is to first characterize the performance of the induction machine, design an adaptive control rule base to increase the efficiency of the wind turbine that drives the generator rotor, and train an artificial Neural Network(ANN) in the adaptive rule base to improve the energy generated through the speed control device. The next stage is to develop a conventional proportional Integral Control (PIC) system for Energy Efficiency.The outcomes showed that the conventional generator's efficiency is stable from 4 seconds to 10 seconds at 59.7%. On the other hand, when an adaptive controller is used, generator one gives efficiency of 60.77% over a stable time range of 4 to 10 seconds. When compared to the conventional method, the system's energy efficiency increases by 1.07% when an adaptive controller is used. The final results show that generator two has the highest conventional generator efficiency of 76.5% and the highest adaptive controller generator efficiency of 77.87%. The results show a 1.3% improvement when an adaptive controller is incorporated into the system compared to the traditional Approach