Recent advancements in Power Electronics have made it possible to regulate the SEIG in many ways, which has resulted in an increased interest in the use of induction generators for small scale power generation with wind power and low hydro heads .
Artificial Neural Networks have been used to evaluate the generated voltage and frequency of SEIG running at different speeds with different values of exciting capacitance and load.
Figure 1 gives per phase equivalent circuit of SEIG, showing voltage generated by rotor as an active source.
The ANN model of SEIG was implemented using Multilayer Perceptron (MLP) network.
The performance of SEIG at variable speed, exciting capacitance and with different loads was first evaluated experimentally to obtain four sets of input-output data required for training of ANN.
Further, ANN model of SEIG does not require any assumptions and complex mathematical computations unlike in conventional analytical techniques.