Dynamic load parameter assessment based on continuous recorder measurements

This paper proposes an original approach to assess the parameters of a dynamic load model. By taking advantage of continuous recorder measurements, the procedure can be fully automated. The idea is to exploit natural voltage variations caused by transformer tap changes. These variations are detected by a robust event detection algorithm. To deal with the huge stochastic variation of the load, an averaging process is used and its output is used in a nonlinear identification algorithm. Results given by this procedure on real measurements taken in a substation in the Belgian power system are shown. A review of the literature on load model and on parameter identification approaches is also presented, allowing a better understanding of the aim of the procedure developed.