Load model parameter derivation using an automated algorithm and measured data

Abstract

This paper summaries some of the key results achieved in the second phase of a multi-year collaborative load modeling research project. After having identified suitable types of load monitoring devices, actual field data for load model development and validation were collected at appropriate locations for several months to more than a year in three different utilities. This data was post-processed using an automated methodology to filter out events suitable for load model parameter estimation. Two load model structures were then used with an automated parameter estimation algorithm to fit model parameters using the field data collected. The models thus developed were then validated using Siemens PTI PSS/ETM dynamic simulation program. This whole process resulted in some key insights and valuable conclusions for future load modeling research efforts.