Measurement-based load modeling using transfer functions for dynamic simulations

Measurement-based load modeling is a promising approach to reliably represent load behavior in dynamic simulations of large power systems. This paper presents a methodology that starts with the acquisition of voltages and currents from power quality monitoring systems and highlights the issues associated with selecting, processing and resampling the data to estimate the relationship between the power deviations as a function of the voltage deviations. The load model mathematical structure chosen is a second-order transfer function, whose parameters are estimated using a genetic algorithm (GA) as the optimization technique that minimizes the error between the real data that are measured and the data that are simulated with the proposed models. Some insights were achieved regarding the appropriate search space choice.