Abstract
In traditional power systems, dominated by syn-chronous generators, the separation between time scales is well-known due to the physical response of the generating units. However, the fast-growing deployment of renewable energy resources (RERs) is bringing an increasing number of generating units based on fast-acting electronic power converters to modern power systems. Nowadays, having an islanded portion of the grid with 100 % electronic generation, at least temporarily, is not unthinkable and, in this case, time-scale separation among dynamics would depend on control design and would not be straightforward. Therefore, the classical model-reduction approach neglecting the dynamics of fast-varying state variables is, at least, questionable. This paper proposes a method to identify relevant states in a modern power system in order to have an accurate input-output response description in any reduced-order model. The method is based on the modal analysis of a balanced realisation of the system (i.e., a linear transformation in which the transformed states’ energies in the output response are known). The proposed method is illustrated on a microgrid with 100% grid-forming electronic power converters. Simulation results show that the proposed method can identify the system’s relevant states even in cases with unclear time-scale separation.
State relevance and modal analysis in electrical microgrids with 100% grid-forming converters
