Q. Ai and A. Domijan, Jr.
Load models, power system, transient stability, artificial neuralnetworks
Load models play an important role in the simulation and evaluation of power system performance. This article proposes a new load model, which is based on a particular form of artificial neural net- works we denote as adaptive back-propagation (ABP) network. ABP can overcome some of shortcomings of common back-propagation (BP), and the ABP load models offer several advantages over tra- ditional load models, as they are nonstructural and can be derived quickly. The application of the method is illustrated using actual field test data. The load models so obtained are shown to replicate the test measurements more closely than those based on traditional load models. Extension of the method to identification of the pa- rameters of the traditional load models is also 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.
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