Composite neural network load models for power system stability analysis

Proper load models are essential to power system stability analysis. This paper proposes a methodology for the development of neural network (NN) based composite load models for power system stability analysis. A two-step modeling procedure is proposed. First knowledge is acquired from a test bed of power systems based on detail load models of a bus to the distribution level. Then, the test bed data is used to develop a composite NN model. The developed NN model is updated based on measurements. A case study on a power inverter controling an induction motor load is presented.