An ANN-based load model for fast transient stability calculations

Load models play an important role in the simulation and calculation of power system performance. This paper presents a new load model which is based on a particular form of artificial neural networks we call adaptive back-propagation (ABP) network. ABP has can overcome some of short-comings of common back-propagation (BP) and ABP load models offer many advantages over traditional load models as they are non-structural and can be derived quickly. The application of the method in modeling loads is illustrated using actual field test data. The load models so obtained are shown to replicate the test measurements more closely than that based on traditional load models. Further extension of the method for the identification of the parameters of the traditional load models is proposed. It is based on linear back-propagation (LBP) network. The proposed LBP load model is incorporated in a transient stability program to show that the computational time is significantly reduced.