Soft Computing Techniques for the Control of Switched Reluctance Generator in Wind Energy Systems: a Review

Abstract

The commercial use of switched reluctance machine as a wind generator is less popular compared to other alternatives such as induction or synchronous machines. This is due to the non-linear behavior and the complex control methods involved in controlling this machine. However, if the control techniques can be made simpler and easier to implement, switched reluctance machine can produce electricity with lower cost and wider operating range of speeds. In this paper, a comprehensive review of recent research trends in soft computing techniques used for the control of switched reluctance generator in wind energy production are discussed. This paper presents the state-of-the-art control techniques for switched reluctance generator as a good guidance for future research. The advantages of soft-computing techniques are reviewed, and this helps to overcome the non-linearity present in the generator. The highlighting features of various intelligent control techniques such as artificial neural networks, fuzzy logic, evolutionary algorithms, etc. are presented in order to encourage the use of SRG in renewable energy generation.