Energy Efficiency Improvement of Doubly-fed Induction Generator Using SelfTuning Adaptive Control Technique

Industries suffer from an inconsistent power supply which has led to low production capacity in these industries. To overcome this ugly situation of inconsistent power supply in the industrial layout that has led to low production capacity, there is a need to introduce a new system which has an improvement as compared to the existing system. This project work, therefore, designed a doubly-fed induction generator using a self-tuning adaptive control technique for energy efficiency improvement. The following objectives guided the design of the system; characterizing the doubly-fed 50KVA induction generator, developing an adaptive control rule base for increasing energy efficiency in doubly-fed induction generator, training an intelligent artificial neural network in an adaptive rule base to enhance the energy and its control mechanism, designing a SIMULINK model of doubly-fed induction generator and finally, developing self-tuning adaptive control in SIMULINK. The results obtained showed that the conventional generator efficiency is stable at 4s through 10s at 65.5%. While the efficiency of the generator when the adaptive controller is incorporated in the system is 66.67% at a stable time of 4s through 10s. The percentage energy improvement when an adaptive controller is incorporated in the system when compared to the conventional method is 1.17%