Design of educational tool for reactive power compensator based on artifical neural network

The reactive power drawn from the electrical power stations increases the cost of the energy produced and reduces the efficiency of energy systems. The reactive energy should be compensated at the load sides in order to reduce the consumption of the reactive power. In this thesis, an artificial neural network (ANN) model has been designed and implemented to control the reactive power compensator (RPC) with a synchronous motor. Since the ANN model obtained has a flexible structure, it can easily be adapted to the real time applications. Furthermore, the model developed can be used either educational purposes or different applications in which ANN algorithms and structures can be tested.