Estimating power system inertia in the presence of static power converters

The increasing deployment of distributed energy resources, such as wind farms and solar power plants, connected to the grid via power electronic converters operating in grid-following mode, is playing a role in decreasing the inertia of power systems. This is primarily due to the non-rotating nature of these resources or the decoupling effects introduced by converters. In this context, the estimation of effective inertia emerges as a critical concern. This thesis proposes an algorithm for estimating the inertia of a power system based on a non linear least square optimization procedure. The algorithm is capable of estimating the overall inertia constant of the system and the main parameters of governors and turbines of units participating to the primary frequency control (PFC). To ensure computational efficiency, the algorithm employs a recursive procedure to estimate the convolution between the power variation and the system's transfer function inverse Laplace transform during PFC. The algorithm is tested by implementing different power system scenarios in EMTP, in presence of steam turbines, hydro generators and including converter-connected resources in grid following mode.