Low-Frequency and Small-Signal Aggregate Load Model Estimation using Ambient Measurements

Load modeling is a challenging problem even today due to the diverse, time-varying and complex nature of loads. The paper investigates the use of the well-known ARMAX method for obtaining a low-frequency, small-signal, aggregate, and dynamic load model using ambient measurements. A realistic model of a 16-machine system driven by random low-level load switching is used to analyze the accuracy of this method. The paper highlights the limitations of the method and the conditions under which it is suitable for identifying the load models. It is shown that the influence of the local load switching noise on the local bus voltage and frequency is a critical factor for accurate estimation. The method works well only if this feedback or the level of local load switching noise is low. An indicator to flag the estimates that are likely to be unreliable is proposed and validated.