Processing and Filtering Digital Fault Recorder Events for Load Model Estimation

This paper focuses on the data post-processing stage of the measurement-based load modelling. Exponential load models are estimated from DFR (Digital Fault Recorder) measured events. The least squares algorithm is used for model estimation. The acquired set of models is used for investigating how the distribution of estimated values depends on the event filtering. Filtering based on voltage and current unbalance ratio, residual voltage of disturbance, voltage deviation, and estimated load model parameter values is analysed. In addition, two different methods for calculating representative model from a set of event based values are compared. One of the analysed methods is found to be less sensitive to event filtering.