Derivation and evaluation of generic measurement-based dynamic load models

Online recorded responses can be used for aggregate dynamic load modelling, taking advantage of the advent of smart grids and the growing installation of phasor measurement units. Although several measurement-based dynamic load models have been proposed in the literature, still most network utilities and system operators take advantage of well-known formulations such as the polynomial and the exponential recovery models. However, these types of load models are only valid for a specific range of operating conditions, thus minimizing their applicability and efficiency. This is mainly due to the fact that the model parameter estimation procedure relies on iterative processes. To this extent, the specific scope of this paper is to present a comprehensive identification procedure for evaluating load models under different loading conditions and further to propose two generic modelling approaches that can be used to derive robust load models that are suitable for dynamic simulations over a wide range. Towards achieving the scope of this paper, Monte Carlo simulations are used to train and validate the data of the loading conditions. Finally, several simulations are performed within the DIgSILENT PowerFactory software to assess the accuracy of the proposed models.